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201 Commits
Author SHA1 Message Date
Sebastian SchmidtandCopybara-Service 85b19383b9 Fixes iOS hand landmarker connections
PiperOrigin-RevId: 565442497
2023-09-14 12:24:25 -07:00
MediaPipe TeamandCopybara-Service 124a4de08d Clean up TensorConverterCalculator flipping behavior
Returns an error if
- gpu_origin is specified for a CPU image, and
- gpu_origin and flip_vertically are both specified.
Adds a test for an IMAGE_GPU input to validate flipping.

PiperOrigin-RevId: 565311456
2023-09-14 02:56:02 -07:00
Daniel ChengandCopybara-Service 21646008d5 Don't define field in ExternalFileHandler that's not used on Windows.
This fixes:
```
error: private field 'buffer_aligned_size_' is not used [-Werror,-Wunused-private-field]
   87 |   int64 buffer_aligned_size_{};
      |         ^
```
in the downstream Chrome build.
PiperOrigin-RevId: 565221813
2023-09-13 18:42:32 -07:00
MediaPipe TeamandCopybara-Service 7333329470 No public description
PiperOrigin-RevId: 565215664
2023-09-13 18:11:03 -07:00
MediaPipe TeamandCopybara-Service e1d1877e07 Modifying tensor_to_vector_float_calculator to take in D_BFLOAT16 values
PiperOrigin-RevId: 565189254
2023-09-13 16:10:35 -07:00
MediaPipe TeamandCopybara-Service 6dc1239aa9 No public description
PiperOrigin-RevId: 565167086
2023-09-13 14:48:48 -07:00
Sebastian SchmidtandCopybara-Service 50bd79a317 Add exports to ImageSegmenterResult and InteractiveSegmenterResult
PiperOrigin-RevId: 565138661
2023-09-13 13:11:25 -07:00
Sebastian SchmidtandCopybara-Service 7b091dbe53 Fix missing exports for FilesetResolver and static constants
PiperOrigin-RevId: 565113006
2023-09-13 11:40:36 -07:00
MediaPipe TeamandCopybara-Service d6ee884200 No public description
PiperOrigin-RevId: 565087299
2023-09-13 10:23:00 -07:00
MediaPipe TeamandCopybara-Service 8c9cd8a2fb fixes the non-unicode path of file_helpers on windows
Macros can't start with ##, this fixes it.

PiperOrigin-RevId: 565066376
2023-09-13 09:04:33 -07:00
MediaPipe TeamandCopybara-Service 90e18eab91 Internal change.
PiperOrigin-RevId: 565062314
2023-09-13 08:49:16 -07:00
MediaPipe TeamandCopybara-Service 38f421acf0 This will fix multiple typos in the tasks internal files.
PiperOrigin-RevId: 565055843
2023-09-13 08:22:19 -07:00
Sebastian SchmidtandCopybara-Service a5a3e9d36b No public description
PiperOrigin-RevId: 564894013
2023-09-12 18:41:10 -07:00
MediaPipe TeamandCopybara-Service df211d211e Internal update.
PiperOrigin-RevId: 564883563
2023-09-12 17:40:28 -07:00
MediaPipe TeamandCopybara-Service 1d8dda3337 Remove uncoditional texture params reset to make float textures handled correctly.
PiperOrigin-RevId: 564869245
2023-09-12 16:40:13 -07:00
MediaPipe TeamandCopybara-Service 5b08a09446 Fixes two issues with file handling on windows:
. If UNICODE is set, then win32 functions taking file paths use wide
  (utf-16) strings. For example, FindFirstFile really calls to
  FindFirstFileW, which takes a wchar_t*. This adds support for
  the unicode path.
. SetContents() changes from "w" to "wb". This is necessary as
  windows will do some amount of encoding without "b", which results
  in much different values being written.

PiperOrigin-RevId: 564842317
2023-09-12 15:00:05 -07:00
MediaPipe TeamandCopybara-Service dbcdb44f7c Move loading tasks-vision-jni to individual vision task class
PiperOrigin-RevId: 564840343
2023-09-12 14:52:58 -07:00
MediaPipe TeamandCopybara-Service 4ba1dadf92 Add option for nearest neighbor interpolation.
PiperOrigin-RevId: 564786213
2023-09-12 11:41:58 -07:00
MediaPipe TeamandCopybara-Service 5daed78844 No public description
PiperOrigin-RevId: 564775970
2023-09-12 11:10:11 -07:00
MediaPipe TeamandCopybara-Service dd692c2395 Internal update
PiperOrigin-RevId: 564740487
2023-09-12 09:17:13 -07:00
MediaPipe TeamandCopybara-Service 26a67f4424 No public description
PiperOrigin-RevId: 564651554
2023-09-12 02:15:53 -07:00
Sebastian SchmidtandCopybara-Service 12502b6f96 Add Handedness to JS, C++ and Android API
PiperOrigin-RevId: 564559718
2023-09-11 18:27:05 -07:00
MediaPipe TeamandCopybara-Service 02bd0d95e7 Splitting GraphRunner into public API declared interfaces and private TS impls
PiperOrigin-RevId: 564551973
2023-09-11 17:48:21 -07:00
Sebastian SchmidtandCopybara-Service 0fec532ebe Add API exports for MPMask and MPImage
PiperOrigin-RevId: 564527405
2023-09-11 16:03:07 -07:00
Sebastian SchmidtandCopybara-Service 56c26dba84 Update WASM files for 10.5 release
PiperOrigin-RevId: 564511761
2023-09-11 15:07:51 -07:00
MediaPipe TeamandCopybara-Service 7a04d60134 Set the default running model to Image for face stylizer.
PiperOrigin-RevId: 564511316
2023-09-11 15:03:07 -07:00
Sebastian SchmidtandCopybara-Service 81481df304 No public description
PiperOrigin-RevId: 564461274
2023-09-11 12:09:11 -07:00
Sebastian SchmidtandCopybara-Service 315982df0f Ensure that C header don't import C++ types
PiperOrigin-RevId: 564435119
2023-09-11 10:47:27 -07:00
Sebastian SchmidtandCopybara-Service e206f9acdb No public description
PiperOrigin-RevId: 564429453
2023-09-11 10:36:06 -07:00
Copybara-Service cdf199cf96 Merge pull request #4775 from priankakariatyml:ios-doc-updates-part2
PiperOrigin-RevId: 564429285
2023-09-11 10:31:13 -07:00
Chris McClanahanandCopybara-Service e51b923bda internal fix
PiperOrigin-RevId: 564404269
2023-09-11 09:11:49 -07:00
MediaPipe TeamandCopybara-Service 7f245bc84b Internal Change
PiperOrigin-RevId: 564316003
2023-09-11 02:39:40 -07:00
MediaPipe TeamandCopybara-Service b2494fe3c1 This will fix multiple typos in the tasks internal files.
PiperOrigin-RevId: 564264998
2023-09-10 21:56:57 -07:00
MediaPipe TeamandCopybara-Service d1b04a9309 Set enableFlowLimiting to false since only Image model is supported for face stylizer.
PiperOrigin-RevId: 563939653
2023-09-08 22:46:15 -07:00
Sebastian SchmidtandCopybara-Service 7accc79018 Internal
PiperOrigin-RevId: 563907673
2023-09-08 19:16:14 -07:00
Copybara-Service 1514304ab3 Merge pull request #4767 from priankakariatyml:ios-vision-task-refactoring-impl3
PiperOrigin-RevId: 563859728
2023-09-08 15:00:36 -07:00
Sebastian SchmidtandCopybara-Service 6df05b7d2a Internal
PiperOrigin-RevId: 563843599
2023-09-08 13:55:19 -07:00
Copybara-Service b89ca28fe1 Merge pull request #4751 from kuaashish:master
PiperOrigin-RevId: 563840414
2023-09-08 13:44:20 -07:00
Prianka Liz Kariat 9d31827de8 Moved iOS MPPHandLandmark enum to MPPHandLandmarker.h 2023-09-08 20:06:47 +05:30
Prianka Liz Kariat 75daf4e756 Updated iOS hand landmarker documentation to use swift names 2023-09-08 19:16:15 +05:30
Prianka Liz Kariat 18f16f6bb5 Updated iOS gesture recognizer documentation to use Swift names 2023-09-08 19:15:56 +05:30
Prianka Liz Kariat 900e637b6a Fixed typos in iOS documentation 2023-09-08 19:15:32 +05:30
MediaPipe TeamandCopybara-Service 886a118232 landmarks_to_detection stream utility function.
PiperOrigin-RevId: 563633314
2023-09-07 21:40:45 -07:00
MediaPipe TeamandCopybara-Service 7549677408 Internal update
PiperOrigin-RevId: 563553758
2023-09-07 14:58:39 -07:00
MediaPipe TeamandCopybara-Service 80b762a281 No public description
PiperOrigin-RevId: 563543098
2023-09-07 14:19:08 -07:00
Sebastian SchmidtandCopybara-Service 6c38483b37 Add externs to js_library targets
PiperOrigin-RevId: 563500180
2023-09-07 11:52:30 -07:00
vrabaudandCopybara-Service 55536c4382 No public description
PiperOrigin-RevId: 563333271
2023-09-07 00:00:38 -07:00
MediaPipe TeamandCopybara-Service 5f4a6e313e Format improvement.
PiperOrigin-RevId: 563321343
2023-09-06 23:02:05 -07:00
MediaPipe TeamandCopybara-Service 3ce457006f Remove video and streaming mode for face stylizer.
PiperOrigin-RevId: 563312344
2023-09-06 22:20:43 -07:00
MediaPipe TeamandCopybara-Service a9da6d325c Move stream API landmarks_projection to third_party.
PiperOrigin-RevId: 563246209
2023-09-06 16:21:09 -07:00
MediaPipe TeamandCopybara-Service 7252f6f2e7 Remove video and stream model in face stylizer.
PiperOrigin-RevId: 563233996
2023-09-06 15:33:58 -07:00
MediaPipe TeamandCopybara-Service b40b3973fb Add notes/warnings for calculators which use dedicated GL contexts.
PiperOrigin-RevId: 563167765
2023-09-06 11:40:21 -07:00
MediaPipe TeamandCopybara-Service e58ec2d039 No public description
PiperOrigin-RevId: 563163901
2023-09-06 11:30:53 -07:00
MediaPipe TeamandCopybara-Service 967007f250 No public description
PiperOrigin-RevId: 563145860
2023-09-06 10:35:52 -07:00
Prianka Liz Kariat 1ffa999abb Replaced the old iOS vision task runner with the refactored task runner 2023-09-06 18:55:03 +05:30
MediaPipe TeamandCopybara-Service e39119ae53 Add missing cache writing implementation in InferenceCalculatorAdvancedGL
Add missing implementation for absl::Status SaveGpuCachesBasedOnBehavior(tflite::gpu::TFLiteGPURunner* gpu_runner) const for non android/chromeos.

PiperOrigin-RevId: 562973338
2023-09-05 20:51:36 -07:00
MediaPipe TeamandCopybara-Service bf32d1acb2 No public description
PiperOrigin-RevId: 562915674
2023-09-05 15:52:21 -07:00
MediaPipe TeamandCopybara-Service 4e52e96973 No public description
PiperOrigin-RevId: 562865700
2023-09-05 13:03:27 -07:00
Sebastian SchmidtandCopybara-Service 2aefa2308b Internal
PiperOrigin-RevId: 562834129
2023-09-05 11:10:55 -07:00
Copybara-Service a87613aa6c Merge pull request #4750 from priankakariatyml:ios-vision-task-runner-refactor-impl-part2
PiperOrigin-RevId: 562823970
2023-09-05 10:39:19 -07:00
Fergus HendersonandCopybara-Service a19da25565 Some spelling and grammar fixes in the comments.
PiperOrigin-RevId: 562802023
2023-09-05 09:28:50 -07:00
MediaPipe TeamandCopybara-Service be0cde8c2e No public description
PiperOrigin-RevId: 562724334
2023-09-05 03:39:37 -07:00
MediaPipe TeamandCopybara-Service 223544ca4b No public description
PiperOrigin-RevId: 562711473
2023-09-05 02:35:24 -07:00
Ayush GuptaandGitHub 4f5069b402 Merge pull request #4751 from kuaashish/master
Updated Issue Templates
2023-09-04 12:15:58 +05:30
MediaPipe TeamandCopybara-Service cac462c486 Add allow_custom_ops to model_util.convert_to_tflite and enable custom ops for face stylizer.
PiperOrigin-RevId: 562212965
2023-09-02 09:56:40 -07:00
MediaPipe TeamandCopybara-Service 2b5e281c27 internal update
PiperOrigin-RevId: 562090520
2023-09-01 17:52:50 -07:00
MediaPipe TeamandCopybara-Service d6119957a4 No public description
PiperOrigin-RevId: 562075110
2023-09-01 16:31:33 -07:00
MediaPipe TeamandCopybara-Service ab70d92752 No public description
PiperOrigin-RevId: 562071599
2023-09-01 16:14:06 -07:00
MediaPipe TeamandCopybara-Service 23057ac146 Update PackMediaSequenceCalculator to support setting clip/media/string, clip/media/confidence and clip/label/index.
The input stream is provided as drishti::Detection.

PiperOrigin-RevId: 562070790
2023-09-01 16:08:52 -07:00
Copybara-Service e7d071ab39 Merge pull request #4745 from priankakariatyml:ios-image-segmenter-impl
PiperOrigin-RevId: 562020873
2023-09-01 12:34:30 -07:00
MediaPipe TeamandCopybara-Service 6c43d37e5a Provide API/options to show intermediate results and generating progress for Java Image Generator.
PiperOrigin-RevId: 562014712
2023-09-01 12:32:26 -07:00
MediaPipe TeamandCopybara-Service ceb8cd3c78 internal update.
PiperOrigin-RevId: 561995330
2023-09-01 10:57:40 -07:00
MediaPipe TeamandCopybara-Service 823493ee82 Internal update.
PiperOrigin-RevId: 561995055
2023-09-01 10:53:00 -07:00
MediaPipe TeamandCopybara-Service 007824594b Rollback of "Enable defining and using internal executors in subgraphs."
PiperOrigin-RevId: 561921927
2023-09-01 04:57:34 -07:00
Prianka Liz Kariat 40da111ba7 Updated iOS object detector to use refactored vision task runner 2023-09-01 14:07:42 +05:30
Prianka Liz Kariat 188321ace4 Updated iOS hand landmarker to use refactored vision task runner 2023-09-01 14:07:25 +05:30
Prianka Liz Kariat 020ca5eb77 Updated iOS gesture recognizer to use refactored vision task runner 2023-09-01 14:07:07 +05:30
Prianka Liz Kariat fe9c7a47e9 Updated iOS face landmarker to use refactored vision task runner 2023-09-01 14:06:50 +05:30
kuaashishandGitHub b60355dee9 Update 18-solution-legacy-issue-template.yaml 2023-09-01 14:06:47 +05:30
kuaashishandGitHub f371f8f4ea Update 16-bug-issue-template.yaml 2023-09-01 14:04:24 +05:30
kuaashishandGitHub 8642a22985 Update 15-build-install-issue-template.yaml 2023-09-01 14:03:49 +05:30
kuaashishandGitHub d8a9f3ac8e Update 14-feature-request-issue-template.yaml 2023-09-01 14:03:07 +05:30
kuaashishandGitHub 1378fb63a7 Update 12-studio-issue-template.yaml 2023-09-01 14:01:20 +05:30
kuaashishandGitHub 0e8f5c168a Update 11-model-maker-issue-template.yaml 2023-09-01 14:00:48 +05:30
kuaashishandGitHub e060824cd7 Merge branch 'google:master' into master 2023-09-01 13:59:13 +05:30
MediaPipe TeamandCopybara-Service de0c7f2a30 Make cache writes optional in InferenceCalculatorAdvancedGL
Previously, caches were always written, and an error would cause the graph to close abruptly. This prevented services with read-only access to the cache from using the calculator.

The new behavior allows services to choose whether or not to write caches.

PiperOrigin-RevId: 561866791
2023-08-31 23:31:27 -07:00
MediaPipe TeamandCopybara-Service dea6ccba25 Remove unnecessary includes in threadpool_std_thread_impl.cc.
The windows.h was causing conflicts with LOG. Also the the posix headers weren't needed because the code doesn't use OS specific code anymore.

PiperOrigin-RevId: 561848229
2023-08-31 21:52:22 -07:00
Sebastian SchmidtandCopybara-Service 9bb852c33d Add libimagegenerator_gpu.so
PiperOrigin-RevId: 561800710
2023-08-31 17:10:00 -07:00
Copybara-Service 827c2983bd Merge pull request #4743 from priankakariatyml:ios-vision-task-runner-refactor-impl
PiperOrigin-RevId: 561796747
2023-08-31 16:53:14 -07:00
MediaPipe TeamandCopybara-Service 81732944c4 No public description
PiperOrigin-RevId: 561775271
2023-08-31 15:22:43 -07:00
MediaPipe TeamandCopybara-Service afcb9c4216 No public description
PiperOrigin-RevId: 561773992
2023-08-31 15:17:51 -07:00
MediaPipe TeamandCopybara-Service 62e682363c Remove reference pointer to prevent using a constant reference in the looped iteration variable
PiperOrigin-RevId: 561758116
2023-08-31 14:17:51 -07:00
MediaPipe TeamandCopybara-Service 7c2d654d67 Convert CHECK macro to ABSL_CHECK.
Chrome can't use Absl's CHECK because of collisions with its own version.

PiperOrigin-RevId: 561740965
2023-08-31 13:20:29 -07:00
Prianka Liz Kariat d16cb72438 Fixed method call in MPPImageSegmenter.mm 2023-08-31 18:04:09 +05:30
Prianka Liz Kariat 9f01540191 Changed order of methods in MPPImageSegmenter.mm 2023-08-31 18:02:34 +05:30
Prianka Liz Kariat ba685567dd Updated iOS image classifier to use refactored vision task runner 2023-08-31 17:56:36 +05:30
Prianka Liz Kariat e7a0ed84e6 Updated iOS face detector to use refactored vision task runner 2023-08-31 17:37:15 +05:30
Prianka Liz Kariat ec87f068c1 Renamed option in MPPImageSegmenterOptions 2023-08-31 17:31:54 +05:30
Prianka Liz Kariat bac3efdf6a Fixed typo in MPPImageSegmenter.h 2023-08-31 17:31:17 +05:30
Prianka Liz Kariat 5a1564e04c Updated image segmenter bazel target to add MPPImageSegmenter.mm 2023-08-31 14:22:17 +05:30
Prianka Liz Kariat 0863d8def5 Added iOS image segmenter implementation file 2023-08-31 14:04:34 +05:30
Prianka Liz Kariat f74f7b8657 Fixed typo 2023-08-31 14:04:17 +05:30
Prianka Liz Kariat 47e7ec47a2 Changed delegate method to optional 2023-08-31 14:04:09 +05:30
kuaashishandGitHub 15c8e4b087 Update 00-task-issue-template.yaml 2023-08-31 11:02:09 +05:30
kuaashishandGitHub fdc1207a40 Update 00-task-issue-template.yaml 2023-08-31 11:00:45 +05:30
kuaashishandGitHub 74ebb89dec Update 00-task-issue-template.yaml 2023-08-31 10:51:16 +05:30
kuaashishandGitHub f88db254da Update 00-task-issue-template.yaml 2023-08-31 10:50:44 +05:30
Copybara-Service 30802b80cd Merge pull request #4735 from priankakariatyml:ios-doc-updates
PiperOrigin-RevId: 561469442
2023-08-30 15:39:20 -07:00
MediaPipe TeamandCopybara-Service 612162d765 Check if the image contains valid face that can be aligned for stylization. If not, throw an exception for invalid input image. This is applied to both input stylized face and raw face.
PiperOrigin-RevId: 561439600
2023-08-30 13:54:11 -07:00
MediaPipe TeamandCopybara-Service c92570f844 Use ABSL_LOG in MediaPipe.
This is needed in Chrome builds to avoid collisions with its own LOG.

PiperOrigin-RevId: 561436864
2023-08-30 13:43:49 -07:00
Jiuqiang TangandCopybara-Service f60da2120d Internal changes
PiperOrigin-RevId: 561398473
2023-08-30 11:26:57 -07:00
MediaPipe TeamandCopybara-Service 5434b840f6 Improving throttling logs by providing a node info corresponding to a throttling stream.
PiperOrigin-RevId: 561396272
2023-08-30 11:21:31 -07:00
MediaPipe TeamandCopybara-Service 45b0271ded No public description
PiperOrigin-RevId: 561379537
2023-08-30 10:27:02 -07:00
Prianka Liz Kariat 3e90e8d464 Fixed directory creation issues in build_ios_framework.sh 2023-08-30 16:28:17 +05:30
Prianka Liz Kariat 763bc8c71c Fixed typos 2023-08-30 16:27:52 +05:30
Prianka Liz Kariat 298578e10e Added gesture recognizer and hand landmarker to iOS vision framework 2023-08-30 14:51:05 +05:30
MediaPipe TeamandCopybara-Service 6c2638592e Internal update.
PiperOrigin-RevId: 561184322
2023-08-29 17:34:35 -07:00
MediaPipe TeamandCopybara-Service e18e749e3e Internal update
PiperOrigin-RevId: 561148365
2023-08-29 15:04:33 -07:00
MediaPipe TeamandCopybara-Service 01fbbd9f67 No public description
PiperOrigin-RevId: 561067189
2023-08-29 10:18:06 -07:00
MediaPipe TeamandCopybara-Service f56b8a13a3 Add a custom op resolver for fused batch norm.
PiperOrigin-RevId: 560795170
2023-08-28 13:04:10 -07:00
MediaPipe TeamandCopybara-Service 442940cd55 No public description
PiperOrigin-RevId: 560743684
2023-08-28 10:08:49 -07:00
MediaPipe TeamandCopybara-Service 1aa5e0d46f No public description
PiperOrigin-RevId: 560689326
2023-08-28 06:21:09 -07:00
MediaPipe TeamandCopybara-Service b22dcf9ce6 No public description
PiperOrigin-RevId: 560652313
2023-08-28 02:50:07 -07:00
Sebastian SchmidtandCopybara-Service d0bf0dd021 Update TF to solve OneDNN build
PiperOrigin-RevId: 560241320
2023-08-25 18:05:50 -07:00
MediaPipe TeamandCopybara-Service d6dce193fc Internal update
PiperOrigin-RevId: 560147650
2023-08-25 11:22:58 -07:00
Copybara-Service 5d2d8f9ab2 Merge pull request #4721 from priankakariatyml:ios-doc-updates
PiperOrigin-RevId: 560133185
2023-08-25 10:37:51 -07:00
Prianka Liz Kariat 3f0ec5969b Updated iOS docs to use swift names in place of objective c names 2023-08-25 18:06:50 +05:30
MediaPipe TeamandCopybara-Service 6e6978cdbf New image test utilities and memory management fixes.
PiperOrigin-RevId: 559926378
2023-08-24 18:02:55 -07:00
MediaPipe TeamandCopybara-Service dd09c8d3f7 Update port includes with IWYU to fix clang warnings in code where corresponding ports are used.
PiperOrigin-RevId: 559920115
2023-08-24 17:33:34 -07:00
Zu KimandCopybara-Service c56f45bce5 Change the image label input from Classification to Detection.
PiperOrigin-RevId: 559828139
2023-08-24 12:08:25 -07:00
Richard LevasseurandCopybara-Service f2e9a553d6 No public description
PiperOrigin-RevId: 559787614
2023-08-24 10:06:00 -07:00
Sebastian SchmidtandCopybara-Service 4fb52bb7ef Add 'types' to package.json
Fixes gttps://github.com/google/mediapipe/issues/4659

PiperOrigin-RevId: 559785635
2023-08-24 09:58:44 -07:00
MediaPipe TeamandCopybara-Service 4b1b6ae7fb Move stream API rect_transformation to third_party.
PiperOrigin-RevId: 559652775
2023-08-23 23:11:47 -07:00
MediaPipe TeamandCopybara-Service b2446c6ca8 No public description
PiperOrigin-RevId: 559566037
2023-08-23 15:50:34 -07:00
Sebastian SchmidtandCopybara-Service f3d069175c Add C++ converters for C Text Classifier API
PiperOrigin-RevId: 559519880
2023-08-23 13:08:40 -07:00
MediaPipe TeamandCopybara-Service f645c59746 Move stream API image_size to third_party.
PiperOrigin-RevId: 559475476
2023-08-23 10:45:18 -07:00
Nevena KotlajaandCopybara-Service 8689f4f595 No public description
PiperOrigin-RevId: 559466191
2023-08-23 10:21:28 -07:00
MediaPipe TeamandCopybara-Service 2ebdb01d43 ImageGenerator Java API
PiperOrigin-RevId: 559310074
2023-08-22 21:42:16 -07:00
MediaPipe TeamandCopybara-Service 90781669cb No public description
PiperOrigin-RevId: 559275983
2023-08-22 18:04:11 -07:00
Sebastian SchmidtandCopybara-Service 1dfdeb6ebb No public description
PiperOrigin-RevId: 559239912
2023-08-22 15:25:03 -07:00
MediaPipe TeamandCopybara-Service 3443fe4c8e No public description
PiperOrigin-RevId: 559211117
2023-08-22 13:43:27 -07:00
MediaPipe TeamandCopybara-Service 8c4b971c14 Add an API in model_task_graph to create or use cached model resources.
PiperOrigin-RevId: 559174528
2023-08-22 11:34:54 -07:00
MediaPipe TeamandCopybara-Service bcb83302bf Add pose landmarks constants
PiperOrigin-RevId: 559153433
2023-08-22 10:32:10 -07:00
MediaPipe TeamandCopybara-Service 7517b56476 No public description
PiperOrigin-RevId: 559133490
2023-08-22 09:26:33 -07:00
MediaPipe TeamandCopybara-Service edb0a64d0e Move stream API loopback to third_party.
PiperOrigin-RevId: 559037020
2023-08-22 01:44:24 -07:00
MediaPipe TeamandCopybara-Service 9bc8b3bb4f Update the header information for EnsureMinimumDefaultExecutorStackSize.
PiperOrigin-RevId: 558981535
2023-08-21 21:26:32 -07:00
MediaPipe TeamandCopybara-Service 7ba4edc372 Internal Change
PiperOrigin-RevId: 558937644
2023-08-21 16:55:44 -07:00
MediaPipe TeamandCopybara-Service 7f8150776a Add an API to run inference with face stylizer TF model.
PiperOrigin-RevId: 558926645
2023-08-21 16:08:58 -07:00
MediaPipe TeamandCopybara-Service bbf168ddda Add a new from_image API to create face stylizer dataset from a single image. Also deprecate the from_folder API since we only support one-shot use case now.
PiperOrigin-RevId: 558912896
2023-08-21 15:14:36 -07:00
MediaPipe TeamandCopybara-Service ae9e945e0c Change SegmentationOptions.builder() to be public
PiperOrigin-RevId: 558864872
2023-08-21 12:18:17 -07:00
MediaPipe TeamandCopybara-Service 737c103940 Add output size as parameters in Java ImageSegmenter
PiperOrigin-RevId: 558834692
2023-08-21 10:45:08 -07:00
MediaPipe TeamandCopybara-Service cd9d32e797 update pose rendering
PiperOrigin-RevId: 558424354
2023-08-19 10:40:26 -07:00
MediaPipe TeamandCopybara-Service a44c810921 Update PackMediaSequenceCalculator to support adding clip/media/id to the MediaSequence.
As the media ID is usually a video ID which is provided to the graph as a side packet, in this graph it expects it to be provided as as a input side packet instead of an input stream.

PiperOrigin-RevId: 558266967
2023-08-18 15:48:40 -07:00
MediaPipe TeamandCopybara-Service fda0d19337 Adds option to use tensor_ahwb in Android vendor processes
PiperOrigin-RevId: 558086646
2023-08-18 02:31:58 -07:00
Chris McClanahanandCopybara-Service a04a3a1c81 internal fix
PiperOrigin-RevId: 557934477
2023-08-17 14:20:58 -07:00
Copybara-Service 6866d338e0 Merge pull request #4645 from priankakariatyml:ios-vision-task-runner-refactoring
PiperOrigin-RevId: 557894034
2023-08-17 12:02:07 -07:00
MediaPipe TeamandCopybara-Service b213256cbd Change supported_ops to a Tuple instead of List to match the API definition.
PiperOrigin-RevId: 557890361
2023-08-17 11:48:56 -07:00
Sebastian SchmidtandCopybara-Service 990bfd2e3e Don't access "document" in WebWorker
Fixes https://github.com/google/mediapipe/issues/4694

PiperOrigin-RevId: 557885230
2023-08-17 11:32:55 -07:00
Prianka Liz Kariat 22dc08be0e Removed convenience initializer from refactored MPPVisionTaskRunner 2023-08-17 14:15:14 +05:30
MediaPipe TeamandCopybara-Service ed0c8d8d8b Swap left and right hand labels.
PiperOrigin-RevId: 557625660
2023-08-16 15:51:19 -07:00
MediaPipe TeamandCopybara-Service 13bb65db96 Internal Changes
PiperOrigin-RevId: 557563669
2023-08-16 12:16:16 -07:00
MediaPipe TeamandCopybara-Service 9e45e2b6e9 Setting training for the encoder and decoder when converting to TFLite.
Also add selected TF ops to TFLite converter.

PiperOrigin-RevId: 557520277
2023-08-16 10:02:29 -07:00
MediaPipe TeamandCopybara-Service ee217ceb67 Fix MediaPipe build in Chromium.
When building Chromium with Clang on Windows, it needs the template specializations to be declared as well.

PiperOrigin-RevId: 557508703
2023-08-16 09:23:15 -07:00
Sebastian SchmidtandCopybara-Service 251ffc21c8 No public description
PiperOrigin-RevId: 557501469
2023-08-16 08:58:14 -07:00
MediaPipe TeamandCopybara-Service ff17846c6a No public description
PiperOrigin-RevId: 557490568
2023-08-16 08:16:30 -07:00
MediaPipe TeamandCopybara-Service ff3f0433d3 Fix image_util shortcut import line
PiperOrigin-RevId: 557311617
2023-08-15 18:19:13 -07:00
MediaPipe TeamandCopybara-Service 1c98270ef0 Import image_util for using it in mediapipe face stylizer open sourcing.
PiperOrigin-RevId: 557254489
2023-08-15 14:41:57 -07:00
MediaPipe TeamandCopybara-Service cda0ba04ed Dry-Run mode for static registration to make it easier to find all required static registrations
PiperOrigin-RevId: 557185347
2023-08-15 11:03:18 -07:00
MediaPipe TeamandCopybara-Service c1d7e6023a Expose tool calculators in headers to enable dynamic registration by superusers.
PiperOrigin-RevId: 557174440
2023-08-15 10:32:45 -07:00
MediaPipe TeamandCopybara-Service a392561b31 Internal change
PiperOrigin-RevId: 557015628
2023-08-14 22:16:20 -07:00
MediaPipe TeamandCopybara-Service 0da296536b Expose stream handlers in headers to allow dynamic registration for superusers
PiperOrigin-RevId: 556988288
2023-08-14 20:01:50 -07:00
MediaPipe TeamandCopybara-Service b6f5414b3d Support more GPU formats in tensor converter calculator.
PiperOrigin-RevId: 556987807
2023-08-14 19:57:05 -07:00
MediaPipe TeamandCopybara-Service a183212a13 Header for callback_packet_calculator to allow dynamic registration for superusers
PiperOrigin-RevId: 556977122
2023-08-14 18:50:11 -07:00
MediaPipe TeamandCopybara-Service 9c5bdd2eb9 Clarify deprecated GraphStatus usage in Close documentation
PiperOrigin-RevId: 556963967
2023-08-14 17:53:32 -07:00
MediaPipe TeamandCopybara-Service dd940707ca Provide a way to disable static registration using MEDIAPIPE_DISABLE_STATIC_REGISTRATION
PiperOrigin-RevId: 556963956
2023-08-14 17:48:25 -07:00
MediaPipe TeamandCopybara-Service 6605fdb16f add end loop calculator for image size
PiperOrigin-RevId: 556955370
2023-08-14 17:09:02 -07:00
MediaPipe TeamandCopybara-Service a8bee6baf3 Updates the runners to support wasm-style binary assets files, and allows their URLs to be explicitly specified as part of the WasmFileset.
PiperOrigin-RevId: 556903356
2023-08-14 13:59:53 -07:00
MediaPipe TeamandCopybara-Service c8ad606e7c Refactor text_classifier preprocessor to move away from using classifier_data_lib
PiperOrigin-RevId: 556859900
2023-08-14 11:41:09 -07:00
MediaPipe TeamandCopybara-Service 3ac3b03ed5 Migrate packet messages auto registration to rely on MEDIAPIPE_STATIC_REGISTRATOR_TEMPLATE
PiperOrigin-RevId: 556063007
2023-08-11 13:14:29 -07:00
Yuqi LiandCopybara-Service c448d54aa7 add metadata writer into face stylizer.
PiperOrigin-RevId: 555596257
2023-08-10 12:09:27 -07:00
MediaPipe TeamandCopybara-Service 91f15d8e4a Enable run inference with a TFLite model containing multiple subgraphs. It uses the subgraph 0 as the default primary subgraph for inference. It will also log a warning in the case that there are more than one subgraph in the model.
PiperOrigin-RevId: 555579131
2023-08-10 11:30:32 -07:00
MediaPipe TeamandCopybara-Service a9c7e22ca4 apply affine transform before drawing, in order to keep constant line width regardless of face cropping.
PiperOrigin-RevId: 555173659
2023-08-09 08:42:57 -07:00
MediaPipe TeamandCopybara-Service 00e0314040 Remove unsafe cast.
PiperOrigin-RevId: 555007705
2023-08-08 18:50:11 -07:00
MediaPipe TeamandCopybara-Service f9a0244c5b No public description
PiperOrigin-RevId: 555005770
2023-08-08 18:38:34 -07:00
MediaPipe TeamandCopybara-Service e558a71597 Include calculator_context.h and calculator_contract.h from calculator_framework.h
PiperOrigin-RevId: 554931086
2023-08-08 13:54:59 -07:00
MediaPipe TeamandCopybara-Service 39b31e51a9 No public description
PiperOrigin-RevId: 554673463
2023-08-07 20:15:34 -07:00
MediaPipe TeamandCopybara-Service 032ed973b6 Add setGpuBufferVerticalFlip to GraphRunner TS API
PiperOrigin-RevId: 554667869
2023-08-07 19:44:21 -07:00
MediaPipe TeamandCopybara-Service c1c51c2fe7 Internal
PiperOrigin-RevId: 554595324
2023-08-07 14:36:42 -07:00
Zu KimandCopybara-Service 22054cd468 Set confidence score of the bounding box label.
PiperOrigin-RevId: 554508925
2023-08-07 10:01:59 -07:00
MediaPipe TeamandCopybara-Service e10bcd1bfd No public description
PiperOrigin-RevId: 554084475
2023-08-05 08:36:24 -07:00
Zu KimandCopybara-Service 460346ed13 Add a support for label annotations (image/label/string and image/label/confidence). Also fixed some clang tidy issues.
PiperOrigin-RevId: 553900667
2023-08-04 13:43:44 -07:00
MediaPipe TeamandCopybara-Service 11508f2291 Internal Change
PiperOrigin-RevId: 553652444
2023-08-03 18:49:35 -07:00
MediaPipe TeamandCopybara-Service 360959e325 Replace some size EXPECTs by ASSERTs
PiperOrigin-RevId: 553555650
2023-08-03 12:27:52 -07:00
MediaPipe TeamandCopybara-Service a0b91e4062 Add a GpuOrigin parameter to TensorConverterCalculator
The parameter superseeds flip_vertically. GpuOrigin works more generally than flip_vertically because CONVENTIONAL works on both iOS (no flip) and Android (yes flip). If not set, the calculator falls back to flip_vertically for backwards compatibility.

Note that web demos actually use TOP_LEFT image orientation, so they shouldn't be flipped, but they still are by CONVENTIONAL. That's being discussed right now.

PiperOrigin-RevId: 553400525
2023-08-03 01:40:13 -07:00
MediaPipe TeamandCopybara-Service 9325af0af3 vlog default executor and its config usage
PiperOrigin-RevId: 553298440
2023-08-02 17:01:05 -07:00
MediaPipe TeamandCopybara-Service e56636b6d1 internal change
PiperOrigin-RevId: 553250547
2023-08-02 14:06:16 -07:00
MediaPipe TeamandCopybara-Service 366a3290cf Change to add the w_avg latent code to style encoding before layer swapping. This is a bug in the previous code. Also set training=True for encoder since this affect the encoding performance.
PiperOrigin-RevId: 553234376
2023-08-02 13:11:22 -07:00
MediaPipe TeamandCopybara-Service 6e54d8c204 Log stack traces for combined CalculatorGraph statuses
PiperOrigin-RevId: 553111356
2023-08-02 05:10:52 -07:00
MediaPipe TeamandCopybara-Service 557ed0b1ea Add tensorflow-addons to model_maker requirements.txt
PiperOrigin-RevId: 552610011
2023-07-31 15:36:25 -07:00
MediaPipe TeamandCopybara-Service 6f916a001c Fix crash in SavePngTestOutput
Do not call SavePngTestOutput in CompareAndSaveImageOutput in case diff_img is null. This can happen if for instance the expected and the actual image have non-matching format or size. Currently, this crashes.
Support single channel golden images.

PiperOrigin-RevId: 552519834
2023-07-31 10:20:06 -07:00
Prianka Liz Kariat d2a86341bd Added refactored iOS vision task runner sources 2023-07-26 20:02:00 +05:30
691 changed files with 20585 additions and 7516 deletions
@@ -40,18 +40,16 @@ body:
label: Programming Language and version (e.g. C++, Python, Java)
validations:
required: true
- type: textarea
- type: input
id: current_model
attributes:
label: Describe the actual behavior
render: shell
validations:
required: true
- type: textarea
- type: input
id: expected_model
attributes:
label: Describe the expected behaviour
render: shell
validations:
required: true
- type: textarea
@@ -41,18 +41,16 @@ body:
label: Task name (e.g. Image classification, Gesture recognition etc.)
validations:
required: true
- type: textarea
- type: input
id: current_model
attributes:
label: Describe the actual behavior
render: shell
validations:
required: true
- type: textarea
- type: input
id: expected_model
attributes:
label: Describe the expected behaviour
render: shell
validations:
required: true
- type: textarea
@@ -31,18 +31,16 @@ body:
label: URL that shows the problem
validations:
required: false
- type: textarea
- type: input
id: current_model
attributes:
label: Describe the actual behavior
render: shell
validations:
required: false
- type: textarea
- type: input
id: expected_model
attributes:
label: Describe the expected behaviour
render: shell
validations:
required: false
- type: textarea
@@ -28,37 +28,33 @@ body:
- 'No'
validations:
required: false
- type: textarea
- type: input
id: behaviour
attributes:
label: Describe the feature and the current behaviour/state
render: shell
validations:
required: true
- type: textarea
- type: input
id: api_change
attributes:
label: Will this change the current API? How?
render: shell
validations:
required: false
- type: textarea
- type: input
id: benifit
attributes:
label: Who will benefit with this feature?
validations:
required: false
- type: textarea
- type: input
id: use_case
attributes:
label: Please specify the use cases for this feature
render: shell
validations:
required: true
- type: textarea
- type: input
id: info_other
attributes:
label: Any Other info
render: shell
validations:
required: false
@@ -87,14 +87,13 @@ body:
placeholder:
validations:
required: false
- type: textarea
- type: input
id: what-happened
attributes:
label: Describe the problem
description: Provide the exact sequence of commands / steps that you executed before running into the [problem](https://google.github.io/mediapipe/getting_started/getting_started.html)
placeholder: Tell us what you see!
value: "A bug happened!"
render: shell
validations:
required: true
- type: textarea
@@ -80,18 +80,16 @@ body:
label: Xcode & Tulsi version (if issue is related to building for iOS)
validations:
required: false
- type: textarea
- type: input
id: current_model
attributes:
label: Describe the actual behavior
render: shell
validations:
required: true
- type: textarea
- type: input
id: expected_model
attributes:
label: Describe the expected behaviour
render: shell
validations:
required: true
- type: textarea
@@ -48,18 +48,16 @@ body:
placeholder: e.g. C++, Python, Java
validations:
required: false
- type: textarea
- type: input
id: current_model
attributes:
label: Describe the actual behavior
render: shell
validations:
required: false
- type: textarea
- type: input
id: expected_model
attributes:
label: Describe the expected behaviour
render: shell
validations:
required: false
- type: textarea
+7 -9
View File
@@ -73,12 +73,9 @@ http_archive(
http_archive(
name = "zlib",
build_file = "@//third_party:zlib.BUILD",
sha256 = "c3e5e9fdd5004dcb542feda5ee4f0ff0744628baf8ed2dd5d66f8ca1197cb1a1",
strip_prefix = "zlib-1.2.11",
urls = [
"http://mirror.bazel.build/zlib.net/fossils/zlib-1.2.11.tar.gz",
"http://zlib.net/fossils/zlib-1.2.11.tar.gz", # 2017-01-15
],
sha256 = "b3a24de97a8fdbc835b9833169501030b8977031bcb54b3b3ac13740f846ab30",
strip_prefix = "zlib-1.2.13",
url = "http://zlib.net/fossils/zlib-1.2.13.tar.gz",
patches = [
"@//third_party:zlib.diff",
],
@@ -485,10 +482,10 @@ http_archive(
)
# TensorFlow repo should always go after the other external dependencies.
# TF on 2023-06-13.
_TENSORFLOW_GIT_COMMIT = "491681a5620e41bf079a582ac39c585cc86878b9"
# TF on 2023-07-26.
_TENSORFLOW_GIT_COMMIT = "e92261fd4cec0b726692081c4d2966b75abf31dd"
# curl -L https://github.com/tensorflow/tensorflow/archive/<TENSORFLOW_GIT_COMMIT>.tar.gz | shasum -a 256
_TENSORFLOW_SHA256 = "9f76389af7a2835e68413322c1eaabfadc912f02a76d71dc16be507f9ca3d3ac"
_TENSORFLOW_SHA256 = "478a229bd4ec70a5b568ac23b5ea013d9fca46a47d6c43e30365a0412b9febf4"
http_archive(
name = "org_tensorflow",
urls = [
@@ -496,6 +493,7 @@ http_archive(
],
patches = [
"@//third_party:org_tensorflow_compatibility_fixes.diff",
"@//third_party:org_tensorflow_system_python.diff",
# Diff is generated with a script, don't update it manually.
"@//third_party:org_tensorflow_custom_ops.diff",
],
+2 -2
View File
@@ -50,7 +50,7 @@ as the primary developer documentation site for MediaPipe as of April 3, 2023.*
3. The [`hello world`] example uses a simple MediaPipe graph in the
`PrintHelloWorld()` function, defined in a [`CalculatorGraphConfig`] proto.
```C++
```c++
absl::Status PrintHelloWorld() {
// Configures a simple graph, which concatenates 2 PassThroughCalculators.
CalculatorGraphConfig config = ParseTextProtoOrDie<CalculatorGraphConfig>(R"(
@@ -126,7 +126,7 @@ as the primary developer documentation site for MediaPipe as of April 3, 2023.*
```c++
mediapipe::Packet packet;
while (poller.Next(&packet)) {
LOG(INFO) << packet.Get<string>();
ABSL_LOG(INFO) << packet.Get<string>();
}
```
+1 -1
View File
@@ -138,7 +138,7 @@ Create a `BUILD` file in the `$APPLICATION_PATH` and add the following build
rules:
```
MIN_IOS_VERSION = "11.0"
MIN_IOS_VERSION = "12.0"
load(
"@build_bazel_rules_apple//apple:ios.bzl",
+54 -43
View File
@@ -14,57 +14,54 @@
licenses(["notice"]) # Apache 2.0
# Note: yes, these need to use "//external:android/crosstool", not
# @androidndk//:default_crosstool.
load("@mediapipe//mediapipe:platforms.bzl", "config_setting_and_platform")
# Generic Android
config_setting(
name = "android",
values = {"crosstool_top": "//external:android/crosstool"},
constraint_values = [
"@platforms//os:android",
],
visibility = ["//visibility:public"],
)
config_setting(
# Android x86 32-bit.
config_setting_and_platform(
name = "android_x86",
values = {
"crosstool_top": "//external:android/crosstool",
"cpu": "x86",
},
constraint_values = [
"@platforms//os:android",
"@platforms//cpu:x86_32",
],
visibility = ["//visibility:public"],
)
config_setting(
# Android x86 64-bit.
config_setting_and_platform(
name = "android_x86_64",
values = {
"crosstool_top": "//external:android/crosstool",
"cpu": "x86_64",
},
constraint_values = [
"@platforms//os:android",
"@platforms//cpu:x86_64",
],
visibility = ["//visibility:public"],
)
config_setting(
name = "android_armeabi",
values = {
"crosstool_top": "//external:android/crosstool",
"cpu": "armeabi",
},
visibility = ["//visibility:public"],
)
config_setting(
# Android ARMv7.
config_setting_and_platform(
name = "android_arm",
values = {
"crosstool_top": "//external:android/crosstool",
"cpu": "armeabi-v7a",
},
constraint_values = [
"@platforms//os:android",
"@platforms//cpu:armv7",
],
visibility = ["//visibility:public"],
)
config_setting(
# Android ARM64.
config_setting_and_platform(
name = "android_arm64",
values = {
"crosstool_top": "//external:android/crosstool",
"cpu": "arm64-v8a",
},
constraint_values = [
"@platforms//os:android",
"@platforms//cpu:arm64",
],
visibility = ["//visibility:public"],
)
@@ -78,7 +75,7 @@ config_setting(
)
# MacOS x86 64-bit.
config_setting(
config_setting_and_platform(
name = "macos_x86_64",
constraint_values = [
"@platforms//os:macos",
@@ -88,7 +85,7 @@ config_setting(
)
# MacOS ARM64.
config_setting(
config_setting_and_platform(
name = "macos_arm64",
constraint_values = [
"@platforms//os:macos",
@@ -107,7 +104,7 @@ config_setting(
)
# iOS device ARM32.
config_setting(
config_setting_and_platform(
name = "ios_armv7",
constraint_values = [
"@platforms//os:ios",
@@ -117,7 +114,7 @@ config_setting(
)
# iOS device ARM64.
config_setting(
config_setting_and_platform(
name = "ios_arm64",
constraint_values = [
"@platforms//os:ios",
@@ -127,7 +124,7 @@ config_setting(
)
# iOS device ARM64E.
config_setting(
config_setting_and_platform(
name = "ios_arm64e",
constraint_values = [
"@platforms//os:ios",
@@ -137,7 +134,7 @@ config_setting(
)
# iOS simulator x86 32-bit.
config_setting(
config_setting_and_platform(
name = "ios_i386",
constraint_values = [
"@platforms//os:ios",
@@ -148,7 +145,7 @@ config_setting(
)
# iOS simulator x86 64-bit.
config_setting(
config_setting_and_platform(
name = "ios_x86_64",
constraint_values = [
"@platforms//os:ios",
@@ -159,7 +156,7 @@ config_setting(
)
# iOS simulator ARM64.
config_setting(
config_setting_and_platform(
name = "ios_sim_arm64",
constraint_values = [
"@platforms//os:ios",
@@ -169,7 +166,6 @@ config_setting(
visibility = ["//visibility:public"],
)
# Generic Apple.
alias(
name = "apple",
actual = select({
@@ -180,9 +176,24 @@ alias(
visibility = ["//visibility:public"],
)
config_setting(
# Windows 64-bit.
config_setting_and_platform(
name = "windows",
values = {"cpu": "x64_windows"},
constraint_values = [
"@platforms//os:windows",
"@platforms//cpu:x86_64",
],
visibility = ["//visibility:public"],
)
# Linux 64-bit.
config_setting_and_platform(
name = "linux",
constraint_values = [
"@platforms//os:linux",
"@platforms//cpu:x86_64",
],
visibility = ["//visibility:public"],
)
exports_files(
+9 -1
View File
@@ -12,6 +12,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
# Placeholder: load py_proto_library
load("//mediapipe/framework/port:build_config.bzl", "mediapipe_cc_proto_library")
licenses(["notice"])
@@ -145,6 +146,7 @@ cc_library(
"//mediapipe/framework/port:logging",
"//mediapipe/framework/port:status",
"//mediapipe/util:time_series_util",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/strings",
"@com_google_audio_tools//audio/dsp/mfcc",
"@eigen_archive//:eigen3",
@@ -163,8 +165,9 @@ cc_library(
"//mediapipe/framework/formats:matrix",
"//mediapipe/framework/formats:time_series_header_cc_proto",
"//mediapipe/framework/port:integral_types",
"//mediapipe/framework/port:logging",
"//mediapipe/util:time_series_util",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/log:absl_log",
"@com_google_absl//absl/strings",
"@com_google_audio_tools//audio/dsp:resampler",
"@com_google_audio_tools//audio/dsp:resampler_q",
@@ -185,6 +188,7 @@ cc_library(
"//mediapipe/framework/port:core_proto",
"//mediapipe/framework/port:status",
"//mediapipe/util:time_series_util",
"@com_google_absl//absl/log:absl_check",
],
alwayslink = 1,
)
@@ -224,6 +228,7 @@ cc_library(
"//mediapipe/framework/formats:time_series_header_cc_proto",
"//mediapipe/framework/port:ret_check",
"//mediapipe/util:time_series_util",
"@com_google_absl//absl/log:absl_check",
"@com_google_audio_tools//audio/dsp:window_functions",
"@eigen_archive//:eigen3",
],
@@ -294,6 +299,7 @@ cc_test(
"//mediapipe/framework/port:integral_types",
"//mediapipe/framework/port:status",
"//mediapipe/util:time_series_test_util",
"@com_google_absl//absl/log:absl_log",
"@com_google_audio_tools//audio/dsp:number_util",
"@eigen_archive//:eigen3",
],
@@ -327,6 +333,7 @@ cc_binary(
"//mediapipe/framework:packet",
"//mediapipe/framework/formats:matrix",
"//mediapipe/framework/formats:time_series_header_cc_proto",
"@com_google_absl//absl/log:absl_check",
"@com_google_benchmark//:benchmark",
],
)
@@ -345,6 +352,7 @@ cc_test(
"//mediapipe/framework/port:integral_types",
"//mediapipe/framework/port:status",
"//mediapipe/util:time_series_test_util",
"@com_google_absl//absl/log:absl_log",
"@com_google_audio_tools//audio/dsp:window_functions",
"@eigen_archive//:eigen3",
],
@@ -23,6 +23,7 @@
#include <vector>
#include "Eigen/Core"
#include "absl/log/absl_check.h"
#include "absl/strings/str_cat.h"
#include "absl/strings/string_view.h"
#include "absl/strings/substitute.h"
@@ -138,7 +139,7 @@ absl::Status FramewiseTransformCalculatorBase::Process(CalculatorContext* cc) {
TransformFrame(input_frame, &output_frame);
// Copy output from vector<float> to Eigen::Vector.
CHECK_EQ(output_frame.size(), num_output_channels_);
ABSL_CHECK_EQ(output_frame.size(), num_output_channels_);
Eigen::Map<const Eigen::MatrixXd> output_frame_map(&output_frame[0],
output_frame.size(), 1);
output->col(frame) = output_frame_map.cast<float>();
@@ -16,6 +16,8 @@
#include "mediapipe/calculators/audio/rational_factor_resample_calculator.h"
#include "absl/log/absl_check.h"
#include "absl/log/absl_log.h"
#include "audio/dsp/resampler_q.h"
using audio_dsp::Resampler;
@@ -45,9 +47,9 @@ void CopyVectorToChannel(const std::vector<float>& vec, Matrix* matrix,
if (matrix->cols() == 0) {
matrix->resize(matrix->rows(), vec.size());
} else {
CHECK_EQ(vec.size(), matrix->cols());
ABSL_CHECK_EQ(vec.size(), matrix->cols());
}
CHECK_LT(channel, matrix->rows());
ABSL_CHECK_LT(channel, matrix->rows());
matrix->row(channel) =
Eigen::Map<const Eigen::ArrayXf>(vec.data(), vec.size());
}
@@ -77,7 +79,7 @@ absl::Status RationalFactorResampleCalculator::Open(CalculatorContext* cc) {
r = ResamplerFromOptions(source_sample_rate_, target_sample_rate_,
resample_options);
if (!r) {
LOG(ERROR) << "Failed to initialize resampler.";
ABSL_LOG(ERROR) << "Failed to initialize resampler.";
return absl::UnknownError("Failed to initialize resampler.");
}
}
@@ -27,7 +27,6 @@
#include "mediapipe/framework/formats/matrix.h"
#include "mediapipe/framework/formats/time_series_header.pb.h"
#include "mediapipe/framework/port/integral_types.h"
#include "mediapipe/framework/port/logging.h"
#include "mediapipe/util/time_series_util.h"
namespace mediapipe {
@@ -22,6 +22,7 @@
#include <vector>
#include "Eigen/Core"
#include "absl/log/absl_log.h"
#include "audio/dsp/number_util.h"
#include "mediapipe/calculators/audio/spectrogram_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
@@ -882,11 +883,11 @@ void BM_ProcessDC(benchmark::State& state) {
const CalculatorRunner::StreamContents& output = runner.Outputs().Index(0);
const Matrix& output_matrix = output.packets[0].Get<Matrix>();
LOG(INFO) << "Output matrix=" << output_matrix.rows() << "x"
<< output_matrix.cols();
LOG(INFO) << "First values=" << output_matrix(0, 0) << ", "
<< output_matrix(1, 0) << ", " << output_matrix(2, 0) << ", "
<< output_matrix(3, 0);
ABSL_LOG(INFO) << "Output matrix=" << output_matrix.rows() << "x"
<< output_matrix.cols();
ABSL_LOG(INFO) << "First values=" << output_matrix(0, 0) << ", "
<< output_matrix(1, 0) << ", " << output_matrix(2, 0) << ", "
<< output_matrix(3, 0);
}
BENCHMARK(BM_ProcessDC);
@@ -18,6 +18,7 @@
#include <memory>
#include <string>
#include "absl/log/absl_check.h"
#include "mediapipe/calculators/audio/stabilized_log_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/formats/matrix.h"
@@ -59,7 +60,7 @@ class StabilizedLogCalculator : public CalculatorBase {
output_scale_ = stabilized_log_calculator_options.output_scale();
check_nonnegativity_ =
stabilized_log_calculator_options.check_nonnegativity();
CHECK_GE(stabilizer_, 0.0)
ABSL_CHECK_GE(stabilizer_, 0.0)
<< "stabilizer must be >= 0.0, received a value of " << stabilizer_;
// If the input packets have a header, propagate the header to the output.
@@ -18,6 +18,7 @@
#include <vector>
#include "Eigen/Core"
#include "absl/log/absl_check.h"
#include "audio/dsp/window_functions.h"
#include "mediapipe/calculators/audio/time_series_framer_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
@@ -104,7 +105,7 @@ class TimeSeriesFramerCalculator : public CalculatorBase {
// All numbers are in input samples.
const int64_t current_output_frame_start = static_cast<int64_t>(
round(cumulative_output_frames_ * average_frame_step_samples_));
CHECK_EQ(current_output_frame_start, cumulative_completed_samples_);
ABSL_CHECK_EQ(current_output_frame_start, cumulative_completed_samples_);
const int64_t next_output_frame_start = static_cast<int64_t>(
round((cumulative_output_frames_ + 1) * average_frame_step_samples_));
return next_output_frame_start - current_output_frame_start;
@@ -17,6 +17,7 @@
#include <random>
#include <vector>
#include "absl/log/absl_check.h"
#include "benchmark/benchmark.h"
#include "mediapipe/calculators/audio/time_series_framer_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
@@ -70,7 +71,7 @@ void BM_TimeSeriesFramerCalculator(benchmark::State& state) {
}
// Initialize graph.
mediapipe::CalculatorGraph graph;
CHECK_OK(graph.Initialize(config));
ABSL_CHECK_OK(graph.Initialize(config));
// Prepare input header.
auto header = std::make_unique<mediapipe::TimeSeriesHeader>();
header->set_sample_rate(kSampleRate);
@@ -78,13 +79,13 @@ void BM_TimeSeriesFramerCalculator(benchmark::State& state) {
state.ResumeTiming(); // Resume benchmark timing.
CHECK_OK(graph.StartRun({}, {{"input", Adopt(header.release())}}));
ABSL_CHECK_OK(graph.StartRun({}, {{"input", Adopt(header.release())}}));
for (auto& packet : input_packets) {
CHECK_OK(graph.AddPacketToInputStream("input", packet));
ABSL_CHECK_OK(graph.AddPacketToInputStream("input", packet));
}
CHECK(!graph.HasError());
CHECK_OK(graph.CloseAllInputStreams());
CHECK_OK(graph.WaitUntilIdle());
ABSL_CHECK(!graph.HasError());
ABSL_CHECK_OK(graph.CloseAllInputStreams());
ABSL_CHECK_OK(graph.WaitUntilIdle());
}
}
BENCHMARK(BM_TimeSeriesFramerCalculator);
@@ -19,6 +19,7 @@
#include <vector>
#include "Eigen/Core"
#include "absl/log/absl_log.h"
#include "audio/dsp/window_functions.h"
#include "mediapipe/calculators/audio/time_series_framer_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
@@ -186,11 +187,12 @@ class TimeSeriesFramerCalculatorTest
const int num_unique_output_samples =
round((output().packets.size() - 1) * frame_step_samples) +
frame_duration_samples;
LOG(INFO) << "packets.size()=" << output().packets.size()
<< " frame_duration_samples=" << frame_duration_samples
<< " frame_step_samples=" << frame_step_samples
<< " num_input_samples_=" << num_input_samples_
<< " num_unique_output_samples=" << num_unique_output_samples;
ABSL_LOG(INFO) << "packets.size()=" << output().packets.size()
<< " frame_duration_samples=" << frame_duration_samples
<< " frame_step_samples=" << frame_step_samples
<< " num_input_samples_=" << num_input_samples_
<< " num_unique_output_samples="
<< num_unique_output_samples;
const int num_padding_samples =
num_unique_output_samples - num_input_samples_;
if (options_.pad_final_packet()) {
+9 -1
View File
@@ -582,6 +582,7 @@ cc_library(
"//mediapipe/framework/port:logging",
"//mediapipe/framework/port:status",
"//mediapipe/framework/tool:options_util",
"@com_google_absl//absl/log:absl_check",
],
alwayslink = 1,
)
@@ -597,6 +598,7 @@ cc_test(
"//mediapipe/framework/formats:video_stream_header",
"//mediapipe/framework/port:gtest_main",
"//mediapipe/framework/port:integral_types",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/strings",
],
)
@@ -629,6 +631,7 @@ cc_library(
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_log",
],
alwayslink = 1,
)
@@ -776,10 +779,11 @@ cc_library(
"//mediapipe/framework/deps:random",
"//mediapipe/framework/formats:video_stream_header",
"//mediapipe/framework/port:integral_types",
"//mediapipe/framework/port:logging",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"//mediapipe/framework/tool:options_util",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/log:absl_log",
"@com_google_absl//absl/strings",
],
alwayslink = 1,
@@ -835,6 +839,7 @@ cc_test(
"//mediapipe/framework/port:gtest_main",
"//mediapipe/framework/port:logging",
"//mediapipe/framework/tool:validate_type",
"@com_google_absl//absl/log:absl_check",
"@eigen_archive//:eigen3",
],
)
@@ -1022,6 +1027,7 @@ cc_library(
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework/api2:node",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_log",
],
alwayslink = 1,
)
@@ -1060,6 +1066,7 @@ cc_test(
"//mediapipe/framework:calculator_runner",
"//mediapipe/framework/port:gtest_main",
"//mediapipe/framework/port:parse_text_proto",
"@com_google_absl//absl/log:absl_log",
],
)
@@ -1106,6 +1113,7 @@ cc_library(
"//mediapipe/framework/api2:node",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_log",
],
alwayslink = 1,
)
@@ -14,6 +14,8 @@
#include "mediapipe/calculators/core/end_loop_calculator.h"
#include <array>
#include <utility>
#include <vector>
#include "mediapipe/framework/formats/classification.pb.h"
@@ -84,4 +86,8 @@ typedef EndLoopCalculator<std::vector<std::array<float, 16>>>
EndLoopAffineMatrixCalculator;
REGISTER_CALCULATOR(EndLoopAffineMatrixCalculator);
typedef EndLoopCalculator<std::vector<std::pair<int, int>>>
EndLoopImageSizeCalculator;
REGISTER_CALCULATOR(EndLoopImageSizeCalculator);
} // namespace mediapipe
@@ -12,6 +12,7 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "absl/log/absl_log.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/calculator_runner.h"
#include "mediapipe/framework/port/gtest.h"
@@ -356,18 +357,18 @@ TEST_F(GateCalculatorTest, AllowWithStateChangeNoDataStreams) {
RunTimeStepWithoutDataStream(kTimestampValue2, "ALLOW", true);
constexpr int64_t kTimestampValue3 = 45;
RunTimeStepWithoutDataStream(kTimestampValue3, "ALLOW", false);
LOG(INFO) << "a";
ABSL_LOG(INFO) << "a";
const std::vector<Packet>& output =
runner()->Outputs().Get("STATE_CHANGE", 0).packets;
LOG(INFO) << "s";
ABSL_LOG(INFO) << "s";
ASSERT_EQ(2, output.size());
LOG(INFO) << "d";
ABSL_LOG(INFO) << "d";
EXPECT_EQ(kTimestampValue1, output[0].Timestamp().Value());
EXPECT_EQ(kTimestampValue3, output[1].Timestamp().Value());
LOG(INFO) << "f";
ABSL_LOG(INFO) << "f";
EXPECT_EQ(true, output[0].Get<bool>()); // Allow.
EXPECT_EQ(false, output[1].Get<bool>()); // Disallow.
LOG(INFO) << "g";
ABSL_LOG(INFO) << "g";
}
TEST_F(GateCalculatorTest, DisallowWithStateChange) {
@@ -12,6 +12,7 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "absl/log/absl_log.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/port/ret_check.h"
#include "mediapipe/framework/port/status.h"
@@ -78,7 +79,7 @@ absl::Status ImmediateMuxCalculator::Process(CalculatorContext* cc) {
if (packet.Timestamp() >= cc->Outputs().Index(0).NextTimestampBound()) {
cc->Outputs().Index(0).AddPacket(packet);
} else {
LOG_FIRST_N(WARNING, 5)
ABSL_LOG_FIRST_N(WARNING, 5)
<< "Dropping a packet with timestamp " << packet.Timestamp();
}
if (cc->Outputs().NumEntries() >= 2) {
@@ -16,6 +16,7 @@
#include <vector>
#include "Eigen/Core"
#include "absl/log/absl_check.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/calculator_runner.h"
#include "mediapipe/framework/formats/matrix.h"
@@ -209,7 +210,7 @@ TEST(MatrixMultiplyCalculatorTest, Multiply) {
MatrixFromTextProto(kSamplesText, &samples);
Matrix expected;
MatrixFromTextProto(kExpectedText, &expected);
CHECK_EQ(samples.cols(), expected.cols());
ABSL_CHECK_EQ(samples.cols(), expected.cols());
for (int i = 0; i < samples.cols(); ++i) {
// Take a column from samples and produce a packet with just that
@@ -12,6 +12,7 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "absl/log/absl_log.h"
#include "mediapipe/framework/api2/node.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/port/ret_check.h"
@@ -53,7 +54,7 @@ class MergeCalculator : public Node {
static absl::Status UpdateContract(CalculatorContract* cc) {
RET_CHECK_GT(kIn(cc).Count(), 0) << "Needs at least one input stream";
if (kIn(cc).Count() == 1) {
LOG(WARNING)
ABSL_LOG(WARNING)
<< "MergeCalculator expects multiple input streams to merge but is "
"receiving only one. Make sure the calculator is configured "
"correctly or consider removing this calculator to reduce "
@@ -72,8 +73,8 @@ class MergeCalculator : public Node {
}
}
LOG(WARNING) << "Empty input packets at timestamp "
<< cc->InputTimestamp().Value();
ABSL_LOG(WARNING) << "Empty input packets at timestamp "
<< cc->InputTimestamp().Value();
return absl::OkStatus();
}
@@ -16,6 +16,9 @@
#include <memory>
#include "absl/log/absl_check.h"
#include "absl/log/absl_log.h"
namespace {
// Reflect an integer against the lower and upper bound of an interval.
int64_t ReflectBetween(int64_t ts, int64_t ts_min, int64_t ts_max) {
@@ -177,7 +180,7 @@ PacketResamplerCalculator::GetSamplingStrategy(
const PacketResamplerCalculatorOptions& options) {
if (options.reproducible_sampling()) {
if (!options.jitter_with_reflection()) {
LOG(WARNING)
ABSL_LOG(WARNING)
<< "reproducible_sampling enabled w/ jitter_with_reflection "
"disabled. "
<< "reproducible_sampling always uses jitter with reflection, "
@@ -200,15 +203,15 @@ PacketResamplerCalculator::GetSamplingStrategy(
Timestamp PacketResamplerCalculator::PeriodIndexToTimestamp(
int64_t index) const {
CHECK_EQ(jitter_, 0.0);
CHECK_NE(first_timestamp_, Timestamp::Unset());
ABSL_CHECK_EQ(jitter_, 0.0);
ABSL_CHECK_NE(first_timestamp_, Timestamp::Unset());
return first_timestamp_ + TimestampDiffFromSeconds(index / frame_rate_);
}
int64_t PacketResamplerCalculator::TimestampToPeriodIndex(
Timestamp timestamp) const {
CHECK_EQ(jitter_, 0.0);
CHECK_NE(first_timestamp_, Timestamp::Unset());
ABSL_CHECK_EQ(jitter_, 0.0);
ABSL_CHECK_NE(first_timestamp_, Timestamp::Unset());
return MathUtil::SafeRound<int64_t, double>(
(timestamp - first_timestamp_).Seconds() * frame_rate_);
}
@@ -229,13 +232,15 @@ absl::Status LegacyJitterWithReflectionStrategy::Open(CalculatorContext* cc) {
if (resampler_options.output_header() !=
PacketResamplerCalculatorOptions::NONE) {
LOG(WARNING) << "VideoHeader::frame_rate holds the target value and not "
"the actual value.";
ABSL_LOG(WARNING)
<< "VideoHeader::frame_rate holds the target value and not "
"the actual value.";
}
if (calculator_->flush_last_packet_) {
LOG(WARNING) << "PacketResamplerCalculatorOptions.flush_last_packet is "
"ignored, because we are adding jitter.";
ABSL_LOG(WARNING)
<< "PacketResamplerCalculatorOptions.flush_last_packet is "
"ignored, because we are adding jitter.";
}
const auto& seed = cc->InputSidePackets().Tag(kSeedTag).Get<std::string>();
@@ -254,7 +259,7 @@ absl::Status LegacyJitterWithReflectionStrategy::Open(CalculatorContext* cc) {
}
absl::Status LegacyJitterWithReflectionStrategy::Close(CalculatorContext* cc) {
if (!packet_reservoir_->IsEmpty()) {
LOG(INFO) << "Emitting pack from reservoir.";
ABSL_LOG(INFO) << "Emitting pack from reservoir.";
calculator_->OutputWithinLimits(cc, packet_reservoir_->GetSample());
}
return absl::OkStatus();
@@ -285,7 +290,7 @@ absl::Status LegacyJitterWithReflectionStrategy::Process(
if (calculator_->frame_time_usec_ <
(cc->InputTimestamp() - calculator_->last_packet_.Timestamp()).Value()) {
LOG_FIRST_N(WARNING, 2)
ABSL_LOG_FIRST_N(WARNING, 2)
<< "Adding jitter is not very useful when upsampling.";
}
@@ -340,8 +345,8 @@ void LegacyJitterWithReflectionStrategy::UpdateNextOutputTimestampWithJitter() {
next_output_timestamp_ = Timestamp(ReflectBetween(
next_output_timestamp_.Value(), next_output_timestamp_min_.Value(),
next_output_timestamp_max_.Value()));
CHECK_GE(next_output_timestamp_, next_output_timestamp_min_);
CHECK_LT(next_output_timestamp_, next_output_timestamp_max_);
ABSL_CHECK_GE(next_output_timestamp_, next_output_timestamp_min_);
ABSL_CHECK_LT(next_output_timestamp_, next_output_timestamp_max_);
}
absl::Status ReproducibleJitterWithReflectionStrategy::Open(
@@ -352,13 +357,15 @@ absl::Status ReproducibleJitterWithReflectionStrategy::Open(
if (resampler_options.output_header() !=
PacketResamplerCalculatorOptions::NONE) {
LOG(WARNING) << "VideoHeader::frame_rate holds the target value and not "
"the actual value.";
ABSL_LOG(WARNING)
<< "VideoHeader::frame_rate holds the target value and not "
"the actual value.";
}
if (calculator_->flush_last_packet_) {
LOG(WARNING) << "PacketResamplerCalculatorOptions.flush_last_packet is "
"ignored, because we are adding jitter.";
ABSL_LOG(WARNING)
<< "PacketResamplerCalculatorOptions.flush_last_packet is "
"ignored, because we are adding jitter.";
}
const auto& seed = cc->InputSidePackets().Tag(kSeedTag).Get<std::string>();
@@ -411,7 +418,7 @@ absl::Status ReproducibleJitterWithReflectionStrategy::Process(
// Note, if the stream is upsampling, this could lead to the same packet
// being emitted twice. Upsampling and jitter doesn't make much sense
// but does technically work.
LOG_FIRST_N(WARNING, 2)
ABSL_LOG_FIRST_N(WARNING, 2)
<< "Adding jitter is not very useful when upsampling.";
}
@@ -499,13 +506,15 @@ absl::Status JitterWithoutReflectionStrategy::Open(CalculatorContext* cc) {
if (resampler_options.output_header() !=
PacketResamplerCalculatorOptions::NONE) {
LOG(WARNING) << "VideoHeader::frame_rate holds the target value and not "
"the actual value.";
ABSL_LOG(WARNING)
<< "VideoHeader::frame_rate holds the target value and not "
"the actual value.";
}
if (calculator_->flush_last_packet_) {
LOG(WARNING) << "PacketResamplerCalculatorOptions.flush_last_packet is "
"ignored, because we are adding jitter.";
ABSL_LOG(WARNING)
<< "PacketResamplerCalculatorOptions.flush_last_packet is "
"ignored, because we are adding jitter.";
}
const auto& seed = cc->InputSidePackets().Tag(kSeedTag).Get<std::string>();
@@ -555,7 +564,7 @@ absl::Status JitterWithoutReflectionStrategy::Process(CalculatorContext* cc) {
if (calculator_->frame_time_usec_ <
(cc->InputTimestamp() - calculator_->last_packet_.Timestamp()).Value()) {
LOG_FIRST_N(WARNING, 2)
ABSL_LOG_FIRST_N(WARNING, 2)
<< "Adding jitter is not very useful when upsampling.";
}
@@ -13,7 +13,6 @@
#include "mediapipe/framework/deps/random_base.h"
#include "mediapipe/framework/formats/video_stream_header.h"
#include "mediapipe/framework/port/integral_types.h"
#include "mediapipe/framework/port/logging.h"
#include "mediapipe/framework/port/ret_check.h"
#include "mediapipe/framework/port/status.h"
#include "mediapipe/framework/port/status_macros.h"
@@ -17,6 +17,7 @@
#include <cmath> // for ceil
#include <memory>
#include "absl/log/absl_check.h"
#include "mediapipe/calculators/core/packet_thinner_calculator.pb.h"
#include "mediapipe/framework/calculator_context.h"
#include "mediapipe/framework/calculator_framework.h"
@@ -160,8 +161,8 @@ absl::Status PacketThinnerCalculator::Open(CalculatorContext* cc) {
thinner_type_ = options.thinner_type();
// This check enables us to assume only two thinner types exist in Process()
CHECK(thinner_type_ == PacketThinnerCalculatorOptions::ASYNC ||
thinner_type_ == PacketThinnerCalculatorOptions::SYNC)
ABSL_CHECK(thinner_type_ == PacketThinnerCalculatorOptions::ASYNC ||
thinner_type_ == PacketThinnerCalculatorOptions::SYNC)
<< "Unsupported thinner type.";
if (thinner_type_ == PacketThinnerCalculatorOptions::ASYNC) {
@@ -177,7 +178,8 @@ absl::Status PacketThinnerCalculator::Open(CalculatorContext* cc) {
} else {
period_ = TimestampDiff(options.period());
}
CHECK_LT(TimestampDiff(0), period_) << "Specified period must be positive.";
ABSL_CHECK_LT(TimestampDiff(0), period_)
<< "Specified period must be positive.";
if (options.has_start_time()) {
start_time_ = Timestamp(options.start_time());
@@ -189,7 +191,7 @@ absl::Status PacketThinnerCalculator::Open(CalculatorContext* cc) {
end_time_ =
options.has_end_time() ? Timestamp(options.end_time()) : Timestamp::Max();
CHECK_LT(start_time_, end_time_)
ABSL_CHECK_LT(start_time_, end_time_)
<< "Invalid PacketThinner: start_time must be earlier than end_time";
sync_output_timestamps_ = options.sync_output_timestamps();
@@ -232,7 +234,7 @@ absl::Status PacketThinnerCalculator::Close(CalculatorContext* cc) {
// Emit any saved packets before quitting.
if (!saved_packet_.IsEmpty()) {
// Only sync thinner should have saved packets.
CHECK_EQ(PacketThinnerCalculatorOptions::SYNC, thinner_type_);
ABSL_CHECK_EQ(PacketThinnerCalculatorOptions::SYNC, thinner_type_);
if (sync_output_timestamps_) {
cc->Outputs().Index(0).AddPacket(
saved_packet_.At(NearestSyncTimestamp(saved_packet_.Timestamp())));
@@ -269,7 +271,7 @@ absl::Status PacketThinnerCalculator::SyncThinnerProcess(
const Timestamp saved_sync = NearestSyncTimestamp(saved);
const Timestamp now = cc->InputTimestamp();
const Timestamp now_sync = NearestSyncTimestamp(now);
CHECK_LE(saved_sync, now_sync);
ABSL_CHECK_LE(saved_sync, now_sync);
if (saved_sync == now_sync) {
// Saved Packet is in same interval as current packet.
// Replace saved packet with current if it is at least as
@@ -295,7 +297,7 @@ absl::Status PacketThinnerCalculator::SyncThinnerProcess(
}
Timestamp PacketThinnerCalculator::NearestSyncTimestamp(Timestamp now) const {
CHECK_NE(start_time_, Timestamp::Unset())
ABSL_CHECK_NE(start_time_, Timestamp::Unset())
<< "Method only valid for sync thinner calculator.";
// Computation is done using int64 arithmetic. No easy way to avoid
@@ -303,12 +305,12 @@ Timestamp PacketThinnerCalculator::NearestSyncTimestamp(Timestamp now) const {
const int64_t now64 = now.Value();
const int64_t start64 = start_time_.Value();
const int64_t period64 = period_.Value();
CHECK_LE(0, period64);
ABSL_CHECK_LE(0, period64);
// Round now64 to its closest interval (units of period64).
int64_t sync64 =
(now64 - start64 + period64 / 2) / period64 * period64 + start64;
CHECK_LE(abs(now64 - sync64), period64 / 2)
ABSL_CHECK_LE(abs(now64 - sync64), period64 / 2)
<< "start64: " << start64 << "; now64: " << now64
<< "; sync64: " << sync64;
@@ -16,6 +16,7 @@
#include <string>
#include <vector>
#include "absl/log/absl_check.h"
#include "absl/strings/str_cat.h"
#include "mediapipe/calculators/core/packet_thinner_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
@@ -70,7 +71,7 @@ class SimpleRunner : public CalculatorRunner {
}
double GetFrameRate() const {
CHECK(!Outputs().Index(0).header.IsEmpty());
ABSL_CHECK(!Outputs().Index(0).header.IsEmpty());
return Outputs().Index(0).header.Get<VideoHeader>().frame_rate;
}
};
@@ -14,6 +14,7 @@
#include <deque>
#include "absl/log/absl_log.h"
#include "mediapipe/calculators/core/sequence_shift_calculator.pb.h"
#include "mediapipe/framework/api2/node.h"
#include "mediapipe/framework/calculator_framework.h"
@@ -101,7 +102,7 @@ void SequenceShiftCalculator::ProcessPositiveOffset(CalculatorContext* cc) {
kOut(cc).Send(packet_cache_.front().At(cc->InputTimestamp()));
packet_cache_.pop_front();
} else if (emit_empty_packets_before_first_packet_) {
LOG(FATAL) << "Not supported yet";
ABSL_LOG(FATAL) << "Not supported yet";
}
// Store current packet for later output.
packet_cache_.push_back(kIn(cc).packet());
+44 -2
View File
@@ -97,6 +97,7 @@ cc_library(
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:source_location",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_check",
],
alwayslink = 1,
)
@@ -125,6 +126,7 @@ cc_library(
"//mediapipe/framework/port:opencv_imgcodecs",
"//mediapipe/framework/port:opencv_imgproc",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_check",
],
alwayslink = 1,
)
@@ -151,11 +153,11 @@ cc_library(
"//mediapipe/framework/formats:image_format_cc_proto",
"//mediapipe/framework/formats:image_frame",
"//mediapipe/framework/formats:image_frame_opencv",
"//mediapipe/framework/port:logging",
"//mediapipe/framework/port:opencv_core",
"//mediapipe/framework/port:opencv_imgproc",
"//mediapipe/framework/port:status",
"//mediapipe/framework/port:vector",
"@com_google_absl//absl/log:absl_log",
] + select({
"//mediapipe/gpu:disable_gpu": [],
"//conditions:default": [
@@ -202,6 +204,7 @@ cc_library(
"//mediapipe/framework/port:opencv_imgproc",
"//mediapipe/framework/port:status",
"//mediapipe/framework/port:vector",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/strings",
] + select({
"//mediapipe/gpu:disable_gpu": [],
@@ -261,9 +264,12 @@ cc_library(
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"//mediapipe/gpu:scale_mode_cc_proto",
"@com_google_absl//absl/status",
"@com_google_absl//absl/strings",
] + select({
"//mediapipe/gpu:disable_gpu": [],
"//conditions:default": [
"//mediapipe/gpu:gl_base_hdr",
"//mediapipe/gpu:gl_calculator_helper",
"//mediapipe/gpu:gl_quad_renderer",
"//mediapipe/gpu:gl_simple_shaders",
@@ -273,6 +279,36 @@ cc_library(
alwayslink = 1,
)
cc_test(
name = "image_transformation_calculator_test",
srcs = ["image_transformation_calculator_test.cc"],
data = ["//mediapipe/calculators/image/testdata:test_images"],
tags = [
"desktop_only_test",
],
deps = [
":image_transformation_calculator",
"//mediapipe/framework:calculator_cc_proto",
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework:calculator_runner",
"//mediapipe/framework/deps:file_path",
"//mediapipe/framework/formats:image_format_cc_proto",
"//mediapipe/framework/formats:image_frame",
"//mediapipe/framework/formats:image_frame_opencv",
"//mediapipe/framework/port:gtest",
"//mediapipe/framework/port:opencv_imgcodecs",
"//mediapipe/framework/port:opencv_imgproc",
"//mediapipe/framework/port:parse_text_proto",
"//mediapipe/gpu:gpu_buffer_to_image_frame_calculator",
"//mediapipe/gpu:image_frame_to_gpu_buffer_calculator",
"//third_party:opencv",
"@com_google_absl//absl/container:flat_hash_set",
"@com_google_absl//absl/flags:flag",
"@com_google_absl//absl/strings",
"@com_google_googletest//:gtest_main",
],
)
cc_library(
name = "image_cropping_calculator",
srcs = ["image_cropping_calculator.cc"],
@@ -300,6 +336,7 @@ cc_library(
"//mediapipe/framework/port:opencv_imgproc",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_log",
] + select({
"//mediapipe/gpu:disable_gpu": [],
"//conditions:default": [
@@ -396,6 +433,7 @@ cc_library(
"//mediapipe/framework/port:logging",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/strings",
],
)
@@ -420,6 +458,8 @@ cc_library(
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"//mediapipe/util:image_frame_util",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/log:absl_log",
"@com_google_absl//absl/strings",
"@libyuv",
],
@@ -625,9 +665,9 @@ cc_library(
"//mediapipe/framework/formats:image",
"//mediapipe/framework/formats:image_format_cc_proto",
"//mediapipe/framework/formats:image_frame",
"//mediapipe/framework/port:logging",
"//mediapipe/framework/port:status",
"//mediapipe/framework/port:vector",
"@com_google_absl//absl/log:absl_log",
] + select({
"//mediapipe/gpu:disable_gpu": [],
"//conditions:default": [
@@ -665,6 +705,7 @@ cc_test(
"//mediapipe/framework/port:opencv_imgcodecs",
"//mediapipe/framework/port:opencv_imgproc",
"//mediapipe/framework/port:parse_text_proto",
"@com_google_absl//absl/log:absl_log",
],
)
@@ -687,6 +728,7 @@ cc_library(
"//mediapipe/gpu:gpu_buffer",
"//mediapipe/gpu:gpu_origin_cc_proto",
"//mediapipe/gpu:shader_util",
"@com_google_absl//absl/log:absl_log",
"@com_google_absl//absl/memory",
"@com_google_absl//absl/status",
"@com_google_absl//absl/status:statusor",
@@ -20,6 +20,7 @@
#include "Eigen/Core"
#include "Eigen/Geometry"
#include "Eigen/LU"
#include "absl/log/absl_log.h"
#include "absl/memory/memory.h"
#include "absl/status/status.h"
#include "absl/status/statusor.h"
@@ -53,6 +54,10 @@ bool IsMatrixVerticalFlipNeeded(GpuOrigin::Mode gpu_origin) {
#endif // __APPLE__
case GpuOrigin::TOP_LEFT:
return false;
default:
ABSL_LOG(ERROR) << "Incorrect GpuOrigin: "
<< static_cast<int>(gpu_origin);
return true;
}
}
@@ -384,6 +389,8 @@ class GlTextureWarpAffineRunner
glActiveTexture(GL_TEXTURE0);
glBindTexture(GL_TEXTURE_2D, 0);
glFlush();
return absl::OkStatus();
}
@@ -15,6 +15,7 @@
#include <memory>
#include <string>
#include "absl/log/absl_check.h"
#include "absl/strings/str_replace.h"
#include "mediapipe/calculators/image/bilateral_filter_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
@@ -183,8 +184,8 @@ absl::Status BilateralFilterCalculator::Open(CalculatorContext* cc) {
sigma_color_ = options_.sigma_color();
sigma_space_ = options_.sigma_space();
CHECK_GE(sigma_color_, 0.0);
CHECK_GE(sigma_space_, 0.0);
ABSL_CHECK_GE(sigma_color_, 0.0);
ABSL_CHECK_GE(sigma_space_, 0.0);
if (!use_gpu_) sigma_color_ *= 255.0;
if (use_gpu_) {
@@ -12,6 +12,7 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "absl/log/absl_check.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/formats/image_frame.h"
#include "mediapipe/framework/formats/image_frame_opencv.h"
@@ -25,8 +26,8 @@
namespace mediapipe {
namespace {
void SetColorChannel(int channel, uint8 value, cv::Mat* mat) {
CHECK(mat->depth() == CV_8U);
CHECK(channel < mat->channels());
ABSL_CHECK(mat->depth() == CV_8U);
ABSL_CHECK(channel < mat->channels());
const int step = mat->channels();
for (int r = 0; r < mat->rows; ++r) {
uint8* row_ptr = mat->ptr<uint8>(r);
@@ -16,6 +16,7 @@
#include <cmath>
#include "absl/log/absl_log.h"
#include "mediapipe/framework/formats/image_frame.h"
#include "mediapipe/framework/formats/image_frame_opencv.h"
#include "mediapipe/framework/formats/rect.pb.h"
@@ -202,8 +203,9 @@ absl::Status ImageCroppingCalculator::ValidateBorderModeForGPU(
switch (options.border_mode()) {
case mediapipe::ImageCroppingCalculatorOptions::BORDER_ZERO:
LOG(WARNING) << "BORDER_ZERO mode is not supported by GPU "
<< "implementation and will fall back into BORDER_REPLICATE";
ABSL_LOG(WARNING)
<< "BORDER_ZERO mode is not supported by GPU "
<< "implementation and will fall back into BORDER_REPLICATE";
break;
case mediapipe::ImageCroppingCalculatorOptions::BORDER_REPLICATE:
break;
@@ -12,6 +12,7 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "absl/status/status.h"
#include "mediapipe/calculators/image/image_transformation_calculator.pb.h"
#include "mediapipe/calculators/image/rotation_mode.pb.h"
#include "mediapipe/framework/calculator_framework.h"
@@ -27,6 +28,7 @@
#include "mediapipe/gpu/scale_mode.pb.h"
#if !MEDIAPIPE_DISABLE_GPU
#include "mediapipe/gpu/gl_base.h"
#include "mediapipe/gpu/gl_calculator_helper.h"
#include "mediapipe/gpu/gl_quad_renderer.h"
#include "mediapipe/gpu/gl_simple_shaders.h"
@@ -60,42 +62,42 @@ constexpr char kVideoPrestreamTag[] = "VIDEO_PRESTREAM";
int RotationModeToDegrees(mediapipe::RotationMode_Mode rotation) {
switch (rotation) {
case mediapipe::RotationMode_Mode_UNKNOWN:
case mediapipe::RotationMode_Mode_ROTATION_0:
case mediapipe::RotationMode::UNKNOWN:
case mediapipe::RotationMode::ROTATION_0:
return 0;
case mediapipe::RotationMode_Mode_ROTATION_90:
case mediapipe::RotationMode::ROTATION_90:
return 90;
case mediapipe::RotationMode_Mode_ROTATION_180:
case mediapipe::RotationMode::ROTATION_180:
return 180;
case mediapipe::RotationMode_Mode_ROTATION_270:
case mediapipe::RotationMode::ROTATION_270:
return 270;
}
}
mediapipe::RotationMode_Mode DegreesToRotationMode(int degrees) {
switch (degrees) {
case 0:
return mediapipe::RotationMode_Mode_ROTATION_0;
return mediapipe::RotationMode::ROTATION_0;
case 90:
return mediapipe::RotationMode_Mode_ROTATION_90;
return mediapipe::RotationMode::ROTATION_90;
case 180:
return mediapipe::RotationMode_Mode_ROTATION_180;
return mediapipe::RotationMode::ROTATION_180;
case 270:
return mediapipe::RotationMode_Mode_ROTATION_270;
return mediapipe::RotationMode::ROTATION_270;
default:
return mediapipe::RotationMode_Mode_UNKNOWN;
return mediapipe::RotationMode::UNKNOWN;
}
}
mediapipe::ScaleMode_Mode ParseScaleMode(
mediapipe::ScaleMode_Mode scale_mode,
mediapipe::ScaleMode_Mode default_mode) {
switch (scale_mode) {
case mediapipe::ScaleMode_Mode_DEFAULT:
case mediapipe::ScaleMode::DEFAULT:
return default_mode;
case mediapipe::ScaleMode_Mode_STRETCH:
case mediapipe::ScaleMode::STRETCH:
return scale_mode;
case mediapipe::ScaleMode_Mode_FIT:
case mediapipe::ScaleMode::FIT:
return scale_mode;
case mediapipe::ScaleMode_Mode_FILL_AND_CROP:
case mediapipe::ScaleMode::FILL_AND_CROP:
return scale_mode;
default:
return default_mode;
@@ -208,6 +210,8 @@ class ImageTransformationCalculator : public CalculatorBase {
bool use_gpu_ = false;
cv::Scalar padding_color_;
ImageTransformationCalculatorOptions::InterpolationMode interpolation_mode_;
#if !MEDIAPIPE_DISABLE_GPU
GlCalculatorHelper gpu_helper_;
std::unique_ptr<QuadRenderer> rgb_renderer_;
@@ -343,6 +347,11 @@ absl::Status ImageTransformationCalculator::Open(CalculatorContext* cc) {
options_.padding_color().green(),
options_.padding_color().blue());
interpolation_mode_ = options_.interpolation_mode();
if (options_.interpolation_mode() ==
ImageTransformationCalculatorOptions::DEFAULT) {
interpolation_mode_ = ImageTransformationCalculatorOptions::LINEAR;
}
if (use_gpu_) {
#if !MEDIAPIPE_DISABLE_GPU
// Let the helper access the GL context information.
@@ -457,26 +466,48 @@ absl::Status ImageTransformationCalculator::RenderCpu(CalculatorContext* cc) {
ComputeOutputDimensions(input_width, input_height, &output_width,
&output_height);
int opencv_interpolation_mode = cv::INTER_LINEAR;
if (output_width_ > 0 && output_height_ > 0) {
cv::Mat scaled_mat;
if (scale_mode_ == mediapipe::ScaleMode_Mode_STRETCH) {
int scale_flag =
input_mat.cols > output_width_ && input_mat.rows > output_height_
? cv::INTER_AREA
: cv::INTER_LINEAR;
if (scale_mode_ == mediapipe::ScaleMode::STRETCH) {
if (interpolation_mode_ == ImageTransformationCalculatorOptions::LINEAR) {
// Use INTER_AREA for downscaling if interpolation mode is set to
// LINEAR.
if (input_mat.cols > output_width_ && input_mat.rows > output_height_) {
opencv_interpolation_mode = cv::INTER_AREA;
} else {
opencv_interpolation_mode = cv::INTER_LINEAR;
}
} else {
opencv_interpolation_mode = cv::INTER_NEAREST;
}
cv::resize(input_mat, scaled_mat, cv::Size(output_width_, output_height_),
0, 0, scale_flag);
0, 0, opencv_interpolation_mode);
} else {
const float scale =
std::min(static_cast<float>(output_width_) / input_width,
static_cast<float>(output_height_) / input_height);
const int target_width = std::round(input_width * scale);
const int target_height = std::round(input_height * scale);
int scale_flag = scale < 1.0f ? cv::INTER_AREA : cv::INTER_LINEAR;
if (scale_mode_ == mediapipe::ScaleMode_Mode_FIT) {
if (interpolation_mode_ == ImageTransformationCalculatorOptions::LINEAR) {
// Use INTER_AREA for downscaling if interpolation mode is set to
// LINEAR.
if (scale < 1.0f) {
opencv_interpolation_mode = cv::INTER_AREA;
} else {
opencv_interpolation_mode = cv::INTER_LINEAR;
}
} else {
opencv_interpolation_mode = cv::INTER_NEAREST;
}
if (scale_mode_ == mediapipe::ScaleMode::FIT) {
cv::Mat intermediate_mat;
cv::resize(input_mat, intermediate_mat,
cv::Size(target_width, target_height), 0, 0, scale_flag);
cv::Size(target_width, target_height), 0, 0,
opencv_interpolation_mode);
const int top = (output_height_ - target_height) / 2;
const int bottom = output_height_ - target_height - top;
const int left = (output_width_ - target_width) / 2;
@@ -488,7 +519,7 @@ absl::Status ImageTransformationCalculator::RenderCpu(CalculatorContext* cc) {
padding_color_);
} else {
cv::resize(input_mat, scaled_mat, cv::Size(target_width, target_height),
0, 0, scale_flag);
0, 0, opencv_interpolation_mode);
output_width = target_width;
output_height = target_height;
}
@@ -514,17 +545,17 @@ absl::Status ImageTransformationCalculator::RenderCpu(CalculatorContext* cc) {
cv::warpAffine(input_mat, rotated_mat, rotation_mat, rotated_size);
} else {
switch (rotation_) {
case mediapipe::RotationMode_Mode_UNKNOWN:
case mediapipe::RotationMode_Mode_ROTATION_0:
case mediapipe::RotationMode::UNKNOWN:
case mediapipe::RotationMode::ROTATION_0:
rotated_mat = input_mat;
break;
case mediapipe::RotationMode_Mode_ROTATION_90:
case mediapipe::RotationMode::ROTATION_90:
cv::rotate(input_mat, rotated_mat, cv::ROTATE_90_COUNTERCLOCKWISE);
break;
case mediapipe::RotationMode_Mode_ROTATION_180:
case mediapipe::RotationMode::ROTATION_180:
cv::rotate(input_mat, rotated_mat, cv::ROTATE_180);
break;
case mediapipe::RotationMode_Mode_ROTATION_270:
case mediapipe::RotationMode::ROTATION_270:
cv::rotate(input_mat, rotated_mat, cv::ROTATE_90_CLOCKWISE);
break;
}
@@ -561,7 +592,7 @@ absl::Status ImageTransformationCalculator::RenderGpu(CalculatorContext* cc) {
ComputeOutputDimensions(input_width, input_height, &output_width,
&output_height);
if (scale_mode_ == mediapipe::ScaleMode_Mode_FILL_AND_CROP) {
if (scale_mode_ == mediapipe::ScaleMode::FILL_AND_CROP) {
const float scale =
std::min(static_cast<float>(output_width_) / input_width,
static_cast<float>(output_height_) / input_height);
@@ -628,6 +659,12 @@ absl::Status ImageTransformationCalculator::RenderGpu(CalculatorContext* cc) {
glActiveTexture(GL_TEXTURE1);
glBindTexture(src1.target(), src1.name());
if (interpolation_mode_ == ImageTransformationCalculatorOptions::NEAREST) {
// TODO: revert texture params.
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_NEAREST);
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST);
}
MP_RETURN_IF_ERROR(renderer->GlRender(
src1.width(), src1.height(), dst.width(), dst.height(), scale_mode,
rotation, flip_horizontally_, flip_vertically_,
@@ -652,8 +689,8 @@ void ImageTransformationCalculator::ComputeOutputDimensions(
if (output_width_ > 0 && output_height_ > 0) {
*output_width = output_width_;
*output_height = output_height_;
} else if (rotation_ == mediapipe::RotationMode_Mode_ROTATION_90 ||
rotation_ == mediapipe::RotationMode_Mode_ROTATION_270) {
} else if (rotation_ == mediapipe::RotationMode::ROTATION_90 ||
rotation_ == mediapipe::RotationMode::ROTATION_270) {
*output_width = input_height;
*output_height = input_width;
} else {
@@ -666,9 +703,9 @@ void ImageTransformationCalculator::ComputeOutputLetterboxPadding(
int input_width, int input_height, int output_width, int output_height,
std::array<float, 4>* padding) {
padding->fill(0.f);
if (scale_mode_ == mediapipe::ScaleMode_Mode_FIT) {
if (rotation_ == mediapipe::RotationMode_Mode_ROTATION_90 ||
rotation_ == mediapipe::RotationMode_Mode_ROTATION_270) {
if (scale_mode_ == mediapipe::ScaleMode::FIT) {
if (rotation_ == mediapipe::RotationMode::ROTATION_90 ||
rotation_ == mediapipe::RotationMode::ROTATION_270) {
std::swap(input_width, input_height);
}
const float input_aspect_ratio =
@@ -54,4 +54,15 @@ message ImageTransformationCalculatorOptions {
// The color for the padding. This option is only used when the scale mode is
// FIT. Default is black. This is for CPU only.
optional Color padding_color = 8;
// Interpolation method to use. Note that on CPU when LINEAR is specified,
// INTER_LINEAR is used for upscaling and INTER_AREA is used for downscaling.
enum InterpolationMode {
DEFAULT = 0;
LINEAR = 1;
NEAREST = 2;
}
// Mode DEFAULT will use LINEAR interpolation.
optional InterpolationMode interpolation_mode = 9;
}
@@ -0,0 +1,315 @@
#include <string>
#include <utility>
#include <vector>
#include "absl/container/flat_hash_set.h"
#include "absl/flags/flag.h"
#include "absl/strings/substitute.h"
#include "mediapipe/framework/calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/calculator_runner.h"
#include "mediapipe/framework/deps/file_path.h"
#include "mediapipe/framework/formats/image_format.pb.h"
#include "mediapipe/framework/formats/image_frame.h"
#include "mediapipe/framework/formats/image_frame_opencv.h"
#include "mediapipe/framework/port/gtest.h"
#include "mediapipe/framework/port/opencv_imgcodecs_inc.h"
#include "mediapipe/framework/port/opencv_imgproc_inc.h"
#include "mediapipe/framework/port/parse_text_proto.h"
#include "testing/base/public/gmock.h"
#include "testing/base/public/googletest.h"
#include "third_party/OpenCV/core.hpp" // IWYU pragma: keep
#include "third_party/OpenCV/core/mat.hpp"
namespace mediapipe {
namespace {
absl::flat_hash_set<int> computeUniqueValues(const cv::Mat& mat) {
// Compute the unique values in cv::Mat
absl::flat_hash_set<int> unique_values;
for (int i = 0; i < mat.rows; i++) {
for (int j = 0; j < mat.cols; j++) {
unique_values.insert(mat.at<unsigned char>(i, j));
}
}
return unique_values;
}
TEST(ImageTransformationCalculatorTest, NearestNeighborResizing) {
cv::Mat input_mat;
cv::cvtColor(cv::imread(file::JoinPath("./",
"/mediapipe/calculators/"
"image/testdata/binary_mask.png")),
input_mat, cv::COLOR_BGR2GRAY);
Packet input_image_packet = MakePacket<ImageFrame>(
ImageFormat::GRAY8, input_mat.size().width, input_mat.size().height);
input_mat.copyTo(formats::MatView(&(input_image_packet.Get<ImageFrame>())));
std::vector<std::pair<int, int>> output_dims{
{256, 333}, {512, 512}, {1024, 1024}};
for (auto& output_dim : output_dims) {
Packet input_output_dim_packet =
MakePacket<std::pair<int, int>>(output_dim);
std::vector<std::string> scale_modes{"FIT", "STRETCH"};
for (const auto& scale_mode : scale_modes) {
CalculatorGraphConfig::Node node_config =
ParseTextProtoOrDie<CalculatorGraphConfig::Node>(
absl::Substitute(R"(
calculator: "ImageTransformationCalculator"
input_stream: "IMAGE:input_image"
input_stream: "OUTPUT_DIMENSIONS:image_size"
output_stream: "IMAGE:output_image"
options: {
[mediapipe.ImageTransformationCalculatorOptions.ext]: {
scale_mode: $0
interpolation_mode: NEAREST
}
})",
scale_mode));
CalculatorRunner runner(node_config);
runner.MutableInputs()->Tag("IMAGE").packets.push_back(
input_image_packet.At(Timestamp(0)));
runner.MutableInputs()
->Tag("OUTPUT_DIMENSIONS")
.packets.push_back(input_output_dim_packet.At(Timestamp(0)));
MP_ASSERT_OK(runner.Run());
const auto& outputs = runner.Outputs();
ASSERT_EQ(outputs.NumEntries(), 1);
const std::vector<Packet>& packets = outputs.Tag("IMAGE").packets;
ASSERT_EQ(packets.size(), 1);
const auto& result = packets[0].Get<ImageFrame>();
ASSERT_EQ(output_dim.first, result.Width());
ASSERT_EQ(output_dim.second, result.Height());
auto unique_input_values = computeUniqueValues(input_mat);
auto unique_output_values =
computeUniqueValues(formats::MatView(&result));
EXPECT_THAT(unique_input_values,
::testing::ContainerEq(unique_output_values));
}
}
}
TEST(ImageTransformationCalculatorTest,
NearestNeighborResizingWorksForFloatInput) {
cv::Mat input_mat;
cv::cvtColor(cv::imread(file::JoinPath("./",
"/mediapipe/calculators/"
"image/testdata/binary_mask.png")),
input_mat, cv::COLOR_BGR2GRAY);
Packet input_image_packet = MakePacket<ImageFrame>(
ImageFormat::VEC32F1, input_mat.size().width, input_mat.size().height);
cv::Mat packet_mat_view =
formats::MatView(&(input_image_packet.Get<ImageFrame>()));
input_mat.convertTo(packet_mat_view, CV_32FC1, 1 / 255.f);
std::vector<std::pair<int, int>> output_dims{
{256, 333}, {512, 512}, {1024, 1024}};
for (auto& output_dim : output_dims) {
Packet input_output_dim_packet =
MakePacket<std::pair<int, int>>(output_dim);
std::vector<std::string> scale_modes{"FIT", "STRETCH"};
for (const auto& scale_mode : scale_modes) {
CalculatorGraphConfig::Node node_config =
ParseTextProtoOrDie<CalculatorGraphConfig::Node>(
absl::Substitute(R"(
calculator: "ImageTransformationCalculator"
input_stream: "IMAGE:input_image"
input_stream: "OUTPUT_DIMENSIONS:image_size"
output_stream: "IMAGE:output_image"
options: {
[mediapipe.ImageTransformationCalculatorOptions.ext]: {
scale_mode: $0
interpolation_mode: NEAREST
}
})",
scale_mode));
CalculatorRunner runner(node_config);
runner.MutableInputs()->Tag("IMAGE").packets.push_back(
input_image_packet.At(Timestamp(0)));
runner.MutableInputs()
->Tag("OUTPUT_DIMENSIONS")
.packets.push_back(input_output_dim_packet.At(Timestamp(0)));
MP_ASSERT_OK(runner.Run());
const auto& outputs = runner.Outputs();
ASSERT_EQ(outputs.NumEntries(), 1);
const std::vector<Packet>& packets = outputs.Tag("IMAGE").packets;
ASSERT_EQ(packets.size(), 1);
const auto& result = packets[0].Get<ImageFrame>();
ASSERT_EQ(output_dim.first, result.Width());
ASSERT_EQ(output_dim.second, result.Height());
auto unique_input_values = computeUniqueValues(packet_mat_view);
auto unique_output_values =
computeUniqueValues(formats::MatView(&result));
EXPECT_THAT(unique_input_values,
::testing::ContainerEq(unique_output_values));
}
}
}
TEST(ImageTransformationCalculatorTest, NearestNeighborResizingGpu) {
cv::Mat input_mat;
cv::cvtColor(cv::imread(file::JoinPath("./",
"/mediapipe/calculators/"
"image/testdata/binary_mask.png")),
input_mat, cv::COLOR_BGR2RGBA);
std::vector<std::pair<int, int>> output_dims{
{256, 333}, {512, 512}, {1024, 1024}};
for (auto& output_dim : output_dims) {
std::vector<std::string> scale_modes{"FIT"}; //, "STRETCH"};
for (const auto& scale_mode : scale_modes) {
CalculatorGraphConfig graph_config =
ParseTextProtoOrDie<CalculatorGraphConfig>(
absl::Substitute(R"(
input_stream: "input_image"
input_stream: "image_size"
output_stream: "output_image"
node {
calculator: "ImageFrameToGpuBufferCalculator"
input_stream: "input_image"
output_stream: "input_image_gpu"
}
node {
calculator: "ImageTransformationCalculator"
input_stream: "IMAGE_GPU:input_image_gpu"
input_stream: "OUTPUT_DIMENSIONS:image_size"
output_stream: "IMAGE_GPU:output_image_gpu"
options: {
[mediapipe.ImageTransformationCalculatorOptions.ext]: {
scale_mode: $0
interpolation_mode: NEAREST
}
}
}
node {
calculator: "GpuBufferToImageFrameCalculator"
input_stream: "output_image_gpu"
output_stream: "output_image"
})",
scale_mode));
ImageFrame input_image(ImageFormat::SRGBA, input_mat.size().width,
input_mat.size().height);
input_mat.copyTo(formats::MatView(&input_image));
std::vector<Packet> output_image_packets;
tool::AddVectorSink("output_image", &graph_config, &output_image_packets);
CalculatorGraph graph(graph_config);
MP_ASSERT_OK(graph.StartRun({}));
MP_ASSERT_OK(graph.AddPacketToInputStream(
"input_image",
MakePacket<ImageFrame>(std::move(input_image)).At(Timestamp(0))));
MP_ASSERT_OK(graph.AddPacketToInputStream(
"image_size",
MakePacket<std::pair<int, int>>(output_dim).At(Timestamp(0))));
MP_ASSERT_OK(graph.WaitUntilIdle());
ASSERT_THAT(output_image_packets, testing::SizeIs(1));
const auto& output_image = output_image_packets[0].Get<ImageFrame>();
ASSERT_EQ(output_dim.first, output_image.Width());
ASSERT_EQ(output_dim.second, output_image.Height());
auto unique_input_values = computeUniqueValues(input_mat);
auto unique_output_values =
computeUniqueValues(formats::MatView(&output_image));
EXPECT_THAT(unique_input_values,
::testing::ContainerEq(unique_output_values));
}
}
}
TEST(ImageTransformationCalculatorTest,
NearestNeighborResizingWorksForFloatTexture) {
cv::Mat input_mat;
cv::cvtColor(cv::imread(file::JoinPath("./",
"/mediapipe/calculators/"
"image/testdata/binary_mask.png")),
input_mat, cv::COLOR_BGR2GRAY);
Packet input_image_packet = MakePacket<ImageFrame>(
ImageFormat::VEC32F1, input_mat.size().width, input_mat.size().height);
cv::Mat packet_mat_view =
formats::MatView(&(input_image_packet.Get<ImageFrame>()));
input_mat.convertTo(packet_mat_view, CV_32FC1, 1 / 255.f);
std::vector<std::pair<int, int>> output_dims{
{256, 333}, {512, 512}, {1024, 1024}};
for (auto& output_dim : output_dims) {
std::vector<std::string> scale_modes{"FIT"}; //, "STRETCH"};
for (const auto& scale_mode : scale_modes) {
CalculatorGraphConfig graph_config =
ParseTextProtoOrDie<CalculatorGraphConfig>(
absl::Substitute(R"(
input_stream: "input_image"
input_stream: "image_size"
output_stream: "output_image"
node {
calculator: "ImageFrameToGpuBufferCalculator"
input_stream: "input_image"
output_stream: "input_image_gpu"
}
node {
calculator: "ImageTransformationCalculator"
input_stream: "IMAGE_GPU:input_image_gpu"
input_stream: "OUTPUT_DIMENSIONS:image_size"
output_stream: "IMAGE_GPU:output_image_gpu"
options: {
[mediapipe.ImageTransformationCalculatorOptions.ext]: {
scale_mode: $0
interpolation_mode: NEAREST
}
}
}
node {
calculator: "GpuBufferToImageFrameCalculator"
input_stream: "output_image_gpu"
output_stream: "output_image"
})",
scale_mode));
std::vector<Packet> output_image_packets;
tool::AddVectorSink("output_image", &graph_config, &output_image_packets);
CalculatorGraph graph(graph_config);
MP_ASSERT_OK(graph.StartRun({}));
MP_ASSERT_OK(graph.AddPacketToInputStream(
"input_image", input_image_packet.At(Timestamp(0))));
MP_ASSERT_OK(graph.AddPacketToInputStream(
"image_size",
MakePacket<std::pair<int, int>>(output_dim).At(Timestamp(0))));
MP_ASSERT_OK(graph.WaitUntilIdle());
ASSERT_THAT(output_image_packets, testing::SizeIs(1));
const auto& output_image = output_image_packets[0].Get<ImageFrame>();
ASSERT_EQ(output_dim.first, output_image.Width());
ASSERT_EQ(output_dim.second, output_image.Height());
auto unique_input_values = computeUniqueValues(packet_mat_view);
auto unique_output_values =
computeUniqueValues(formats::MatView(&output_image));
EXPECT_THAT(unique_input_values,
::testing::ContainerEq(unique_output_values));
}
}
}
} // namespace
} // namespace mediapipe
@@ -12,6 +12,7 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "absl/log/absl_check.h"
#include "mediapipe/calculators/image/opencv_image_encoder_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/formats/image_frame_opencv.h"
@@ -61,7 +62,7 @@ absl::Status OpenCvImageEncoderCalculator::Open(CalculatorContext* cc) {
absl::Status OpenCvImageEncoderCalculator::Process(CalculatorContext* cc) {
const ImageFrame& image_frame = cc->Inputs().Index(0).Get<ImageFrame>();
CHECK_EQ(1, image_frame.ByteDepth());
ABSL_CHECK_EQ(1, image_frame.ByteDepth());
std::unique_ptr<OpenCvImageEncoderCalculatorResults> encoded_result =
absl::make_unique<OpenCvImageEncoderCalculatorResults>();
@@ -18,6 +18,8 @@
#include <memory>
#include <string>
#include "absl/log/absl_check.h"
#include "absl/log/absl_log.h"
#include "absl/strings/str_cat.h"
#include "absl/strings/substitute.h"
#include "libyuv/scale.h"
@@ -293,7 +295,7 @@ absl::Status ScaleImageCalculator::InitializeFrameInfo(CalculatorContext* cc) {
header->width = output_width_;
header->height = output_height_;
header->format = output_format_;
LOG(INFO) << "OUTPUTTING HEADER on stream";
ABSL_LOG(INFO) << "OUTPUTTING HEADER on stream";
cc->Outputs()
.Tag("VIDEO_HEADER")
.Add(header.release(), Timestamp::PreStream());
@@ -393,10 +395,11 @@ absl::Status ScaleImageCalculator::Open(CalculatorContext* cc) {
.SetHeader(Adopt(output_header.release()));
has_header_ = true;
} else {
LOG(WARNING) << "Stream had a VideoHeader which didn't have sufficient "
"information. "
"Dropping VideoHeader and trying to deduce needed "
"information.";
ABSL_LOG(WARNING)
<< "Stream had a VideoHeader which didn't have sufficient "
"information. "
"Dropping VideoHeader and trying to deduce needed "
"information.";
input_width_ = 0;
input_height_ = 0;
if (!options_.has_input_format()) {
@@ -507,7 +510,7 @@ absl::Status ScaleImageCalculator::ValidateImageFrame(
absl::Status ScaleImageCalculator::ValidateYUVImage(CalculatorContext* cc,
const YUVImage& yuv_image) {
CHECK_EQ(input_format_, ImageFormat::YCBCR420P);
ABSL_CHECK_EQ(input_format_, ImageFormat::YCBCR420P);
if (!has_header_) {
if (input_width_ != yuv_image.width() ||
input_height_ != yuv_image.height()) {
@@ -18,6 +18,7 @@
#include <string>
#include "absl/log/absl_check.h"
#include "absl/strings/str_split.h"
#include "mediapipe/framework/port/logging.h"
#include "mediapipe/framework/port/ret_check.h"
@@ -40,10 +41,10 @@ absl::Status FindCropDimensions(int input_width, int input_height, //
const std::string& max_aspect_ratio, //
int* crop_width, int* crop_height, //
int* col_start, int* row_start) {
CHECK(crop_width);
CHECK(crop_height);
CHECK(col_start);
CHECK(row_start);
ABSL_CHECK(crop_width);
ABSL_CHECK(crop_height);
ABSL_CHECK(col_start);
ABSL_CHECK(row_start);
double min_aspect_ratio_q = 0.0;
double max_aspect_ratio_q = 0.0;
@@ -83,8 +84,8 @@ absl::Status FindCropDimensions(int input_width, int input_height, //
}
}
CHECK_LE(*crop_width, input_width);
CHECK_LE(*crop_height, input_height);
ABSL_CHECK_LE(*crop_width, input_width);
ABSL_CHECK_LE(*crop_height, input_height);
return absl::OkStatus();
}
@@ -96,8 +97,8 @@ absl::Status FindOutputDimensions(int input_width, //
bool preserve_aspect_ratio, //
int scale_to_multiple_of, //
int* output_width, int* output_height) {
CHECK(output_width);
CHECK(output_height);
ABSL_CHECK(output_width);
ABSL_CHECK(output_height);
if (target_max_area > 0 && input_width * input_height > target_max_area) {
preserve_aspect_ratio = true;
@@ -15,13 +15,13 @@
#include <algorithm>
#include <memory>
#include "absl/log/absl_log.h"
#include "mediapipe/calculators/image/segmentation_smoothing_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/calculator_options.pb.h"
#include "mediapipe/framework/formats/image.h"
#include "mediapipe/framework/formats/image_format.pb.h"
#include "mediapipe/framework/formats/image_frame.h"
#include "mediapipe/framework/port/logging.h"
#include "mediapipe/framework/port/status.h"
#include "mediapipe/framework/port/vector.h"
@@ -273,7 +273,7 @@ absl::Status SegmentationSmoothingCalculator::RenderGpu(CalculatorContext* cc) {
const auto& previous_frame = cc->Inputs().Tag(kPreviousMaskTag).Get<Image>();
if (previous_frame.format() != current_frame.format()) {
LOG(ERROR) << "Warning: mixing input format types. ";
ABSL_LOG(ERROR) << "Warning: mixing input format types. ";
}
auto previous_texture = gpu_helper_.CreateSourceTexture(previous_frame);
@@ -14,6 +14,7 @@
#include <memory>
#include "absl/log/absl_log.h"
#include "mediapipe/calculators/image/segmentation_smoothing_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/calculator_runner.h"
@@ -169,7 +170,7 @@ void RunTest(bool use_gpu, float mix_ratio, cv::Mat& test_result) {
}
}
} else {
LOG(ERROR) << "invalid ratio";
ABSL_LOG(ERROR) << "invalid ratio";
}
}
@@ -14,13 +14,13 @@
#include <memory>
#include "absl/log/absl_log.h"
#include "mediapipe/calculators/image/set_alpha_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/calculator_options.pb.h"
#include "mediapipe/framework/formats/image_format.pb.h"
#include "mediapipe/framework/formats/image_frame.h"
#include "mediapipe/framework/formats/image_frame_opencv.h"
#include "mediapipe/framework/port/logging.h"
#include "mediapipe/framework/port/opencv_core_inc.h"
#include "mediapipe/framework/port/opencv_imgproc_inc.h"
#include "mediapipe/framework/port/status.h"
@@ -268,7 +268,7 @@ absl::Status SetAlphaCalculator::RenderCpu(CalculatorContext* cc) {
const auto& input_frame = cc->Inputs().Tag(kInputFrameTag).Get<ImageFrame>();
const cv::Mat input_mat = formats::MatView(&input_frame);
if (!(input_mat.type() == CV_8UC3 || input_mat.type() == CV_8UC4)) {
LOG(ERROR) << "Only 3 or 4 channel 8-bit input image supported";
ABSL_LOG(ERROR) << "Only 3 or 4 channel 8-bit input image supported";
}
// Setup destination image
@@ -328,7 +328,7 @@ absl::Status SetAlphaCalculator::RenderGpu(CalculatorContext* cc) {
cc->Inputs().Tag(kInputFrameTagGpu).Get<mediapipe::GpuBuffer>();
if (!(input_frame.format() == mediapipe::GpuBufferFormat::kBGRA32 ||
input_frame.format() == mediapipe::GpuBufferFormat::kRGB24)) {
LOG(ERROR) << "Only RGB or RGBA input image supported";
ABSL_LOG(ERROR) << "Only RGB or RGBA input image supported";
}
auto input_texture = gpu_helper_.CreateSourceTexture(input_frame);
+1
View File
@@ -18,6 +18,7 @@ licenses(["notice"])
filegroup(
name = "test_images",
srcs = [
"binary_mask.png",
"dino.jpg",
"dino_quality_50.jpg",
"dino_quality_80.jpg",
Binary file not shown.

After

Width:  |  Height:  |  Size: 771 B

+2
View File
@@ -31,12 +31,14 @@ mediapipe_proto_library(
cc_library(
name = "callback_packet_calculator",
srcs = ["callback_packet_calculator.cc"],
hdrs = ["callback_packet_calculator.h"],
visibility = ["//mediapipe/framework:__subpackages__"],
deps = [
":callback_packet_calculator_cc_proto",
"//mediapipe/framework:calculator_base",
"//mediapipe/framework:calculator_registry",
"//mediapipe/framework:output_side_packet",
"@com_google_absl//absl/status",
],
alwayslink = 1,
)
@@ -11,10 +11,12 @@
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "mediapipe/calculators/internal/callback_packet_calculator.h"
#include <functional>
#include <string>
#include "absl/status/status.h"
#include "mediapipe/calculators/internal/callback_packet_calculator.pb.h" // NOLINT
#include "mediapipe/framework/calculator_base.h"
#include "mediapipe/framework/calculator_registry.h"
@@ -39,64 +41,55 @@ void DumpPostStreamPacket(Packet* post_stream_packet, const Packet& packet) {
*post_stream_packet = packet;
}
}
} // namespace
// Creates a callback which takes a packet and stores it either in a
// vector of packets or stores only the packet at PostStream timestamp.
// The kind of callback is controlled by an option. The callback is
// a std::function and is directly usable by CallbackCalculator.
// Since the options for the packet generator include a serialized pointer
// value, the resulting callback is only valid on the original machine
// while that pointer is still alive.
class CallbackPacketCalculator : public CalculatorBase {
public:
static absl::Status GetContract(CalculatorContract* cc) {
const auto& options = cc->Options<CallbackPacketCalculatorOptions>();
switch (options.type()) {
case CallbackPacketCalculatorOptions::VECTOR_PACKET:
case CallbackPacketCalculatorOptions::POST_STREAM_PACKET:
cc->OutputSidePackets()
.Index(0)
.Set<std::function<void(const Packet&)>>();
break;
default:
return mediapipe::InvalidArgumentErrorBuilder(MEDIAPIPE_LOC)
<< "Invalid type of callback to produce.";
}
return absl::OkStatus();
}
absl::Status Open(CalculatorContext* cc) override {
const auto& options = cc->Options<CallbackPacketCalculatorOptions>();
void* ptr;
if (sscanf(options.pointer().c_str(), "%p", &ptr) != 1) {
absl::Status CallbackPacketCalculator::GetContract(CalculatorContract* cc) {
const auto& options = cc->Options<CallbackPacketCalculatorOptions>();
switch (options.type()) {
case CallbackPacketCalculatorOptions::VECTOR_PACKET:
case CallbackPacketCalculatorOptions::POST_STREAM_PACKET:
cc->OutputSidePackets()
.Index(0)
.Set<std::function<void(const Packet&)>>();
break;
default:
return mediapipe::InvalidArgumentErrorBuilder(MEDIAPIPE_LOC)
<< "Stored pointer value in options is invalid.";
}
switch (options.type()) {
case CallbackPacketCalculatorOptions::VECTOR_PACKET:
cc->OutputSidePackets().Index(0).Set(
MakePacket<std::function<void(const Packet&)>>(std::bind(
&DumpToVector, reinterpret_cast<std::vector<Packet>*>(ptr),
std::placeholders::_1)));
break;
case CallbackPacketCalculatorOptions::POST_STREAM_PACKET:
cc->OutputSidePackets().Index(0).Set(
MakePacket<std::function<void(const Packet&)>>(
std::bind(&DumpPostStreamPacket, reinterpret_cast<Packet*>(ptr),
std::placeholders::_1)));
break;
default:
return mediapipe::InvalidArgumentErrorBuilder(MEDIAPIPE_LOC)
<< "Invalid type to dump into.";
}
return absl::OkStatus();
<< "Invalid type of callback to produce.";
}
return absl::OkStatus();
}
absl::Status Process(CalculatorContext* cc) override {
return absl::OkStatus();
absl::Status CallbackPacketCalculator::Open(CalculatorContext* cc) {
const auto& options = cc->Options<CallbackPacketCalculatorOptions>();
void* ptr;
if (sscanf(options.pointer().c_str(), "%p", &ptr) != 1) {
return mediapipe::InvalidArgumentErrorBuilder(MEDIAPIPE_LOC)
<< "Stored pointer value in options is invalid.";
}
};
switch (options.type()) {
case CallbackPacketCalculatorOptions::VECTOR_PACKET:
cc->OutputSidePackets().Index(0).Set(
MakePacket<std::function<void(const Packet&)>>(std::bind(
&DumpToVector, reinterpret_cast<std::vector<Packet>*>(ptr),
std::placeholders::_1)));
break;
case CallbackPacketCalculatorOptions::POST_STREAM_PACKET:
cc->OutputSidePackets().Index(0).Set(
MakePacket<std::function<void(const Packet&)>>(
std::bind(&DumpPostStreamPacket, reinterpret_cast<Packet*>(ptr),
std::placeholders::_1)));
break;
default:
return mediapipe::InvalidArgumentErrorBuilder(MEDIAPIPE_LOC)
<< "Invalid type to dump into.";
}
return absl::OkStatus();
}
absl::Status CallbackPacketCalculator::Process(CalculatorContext* cc) {
return absl::OkStatus();
}
REGISTER_CALCULATOR(CallbackPacketCalculator);
@@ -0,0 +1,39 @@
// Copyright 2023 The MediaPipe Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#ifndef MEDIAPIPE_CALCULATORS_INTERNAL_CALLBACK_PACKET_CALCULATOR_H_
#define MEDIAPIPE_CALCULATORS_INTERNAL_CALLBACK_PACKET_CALCULATOR_H_
#include "absl/status/status.h"
#include "mediapipe/framework/calculator_base.h"
namespace mediapipe {
// Creates a callback which takes a packet and stores it either in a
// vector of packets or stores only the packet at PostStream timestamp.
// The kind of callback is controlled by an option. The callback is
// a std::function and is directly usable by CallbackCalculator.
// Since the options for the packet generator include a serialized pointer
// value, the resulting callback is only valid on the original machine
// while that pointer is still alive.
class CallbackPacketCalculator : public CalculatorBase {
public:
static absl::Status GetContract(CalculatorContract* cc);
absl::Status Open(CalculatorContext* cc) override;
absl::Status Process(CalculatorContext* cc) override;
};
} // namespace mediapipe
#endif // MEDIAPIPE_CALCULATORS_INTERNAL_CALLBACK_PACKET_CALCULATOR_H_
+26
View File
@@ -87,6 +87,7 @@ cc_library(
"//mediapipe/framework/formats:time_series_header_cc_proto",
"//mediapipe/framework/port:ret_check",
"//mediapipe/util:time_series_util",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/memory",
"@com_google_absl//absl/status",
"@com_google_absl//absl/status:statusor",
@@ -181,6 +182,7 @@ cc_library(
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework/api2:node",
"//mediapipe/framework/formats:tensor",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/status",
],
alwayslink = 1,
@@ -198,6 +200,7 @@ cc_test(
"//mediapipe/framework/formats:tensor",
"//mediapipe/framework/port:gtest_main",
"//mediapipe/framework/port:parse_text_proto",
"@com_google_absl//absl/log:absl_check",
"@org_tensorflow//tensorflow/lite/c:common",
],
)
@@ -445,6 +448,7 @@ cc_library(
"//mediapipe/framework/deps:file_path",
"//mediapipe/gpu:gl_calculator_helper",
"//mediapipe/util/tflite:tflite_gpu_runner",
"@com_google_absl//absl/log:absl_log",
"@com_google_absl//absl/memory",
"@com_google_absl//absl/status",
"@com_google_absl//absl/status:statusor",
@@ -474,6 +478,7 @@ cc_library(
"//mediapipe/gpu:gpu_buffer",
"//mediapipe/objc:mediapipe_framework_ios",
"//mediapipe/util/tflite:config",
"@com_google_absl//absl/log:absl_log",
"@com_google_absl//absl/memory",
"@com_google_absl//absl/strings:str_format",
"@org_tensorflow//tensorflow/lite/delegates/gpu:metal_delegate",
@@ -620,6 +625,7 @@ mediapipe_proto_library(
deps = [
"//mediapipe/framework:calculator_options_proto",
"//mediapipe/framework:calculator_proto",
"//mediapipe/gpu:gpu_origin_proto",
],
)
@@ -649,7 +655,18 @@ cc_library(
"//mediapipe/framework/formats:matrix",
"//mediapipe/framework/formats:tensor",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"//mediapipe/framework/port:statusor",
"//mediapipe/gpu:gpu_buffer_format",
"//mediapipe/gpu:gpu_origin_cc_proto",
"//mediapipe/util:resource_util",
"@com_google_absl//absl/log",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/log:absl_log",
"@com_google_absl//absl/log:check",
"@com_google_absl//absl/status",
"@com_google_absl//absl/status:statusor",
"@com_google_absl//absl/strings:str_format",
] + select({
"//mediapipe/gpu:disable_gpu": [],
"//conditions:default": ["tensor_converter_calculator_gpu_deps"],
@@ -699,9 +716,11 @@ cc_test(
"//mediapipe/framework/formats:tensor",
"//mediapipe/framework/port:gtest_main",
"//mediapipe/framework/port:integral_types",
"//mediapipe/framework/port:opencv_core",
"//mediapipe/framework/port:parse_text_proto",
"//mediapipe/framework/tool:validate_type",
"@com_google_absl//absl/memory",
"@com_google_absl//absl/status",
"@com_google_absl//absl/strings",
],
)
@@ -737,6 +756,8 @@ cc_library(
"//mediapipe/framework/formats:tensor",
"//mediapipe/framework/formats/object_detection:anchor_cc_proto",
"//mediapipe/framework/port:ret_check",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/log:absl_log",
"@com_google_absl//absl/strings:str_format",
"@com_google_absl//absl/types:span",
] + selects.with_or({
@@ -793,6 +814,7 @@ cc_library(
"//mediapipe/framework/formats:landmark_cc_proto",
"//mediapipe/framework/formats:tensor",
"//mediapipe/framework/port:ret_check",
"@com_google_absl//absl/log:absl_check",
],
alwayslink = 1,
)
@@ -985,6 +1007,8 @@ cc_library(
"//mediapipe/framework/port:status",
"//mediapipe/framework/port:statusor",
"//mediapipe/gpu:gpu_origin_cc_proto",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/log:absl_log",
] + select({
"//mediapipe/gpu:disable_gpu": [],
"//conditions:default": [":image_to_tensor_calculator_gpu_deps"],
@@ -1077,6 +1101,7 @@ cc_test(
"//mediapipe/framework/port:parse_text_proto",
"//mediapipe/util:image_test_utils",
"@com_google_absl//absl/flags:flag",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/memory",
"@com_google_absl//absl/strings",
"@com_google_absl//absl/strings:str_format",
@@ -1204,6 +1229,7 @@ cc_library(
"//mediapipe/gpu:gl_calculator_helper",
"//mediapipe/gpu:gl_simple_shaders",
"//mediapipe/gpu:shader_util",
"@com_google_absl//absl/log:absl_log",
"@com_google_absl//absl/strings",
],
}),
@@ -20,6 +20,7 @@
#include <utility>
#include <vector>
#include "absl/log/absl_check.h"
#include "absl/memory/memory.h"
#include "absl/status/status.h"
#include "absl/status/statusor.h"
@@ -348,7 +349,7 @@ absl::Status AudioToTensorCalculator::Process(CalculatorContext* cc) {
return absl::InvalidArgumentError(
"The audio data should be stored in column-major.");
}
CHECK(channels_match || mono_output);
ABSL_CHECK(channels_match || mono_output);
const Matrix& input = channels_match ? input_frame
// Mono mixdown.
: input_frame.colwise().mean();
@@ -457,7 +458,7 @@ absl::Status AudioToTensorCalculator::SetupStreamingResampler(
}
void AudioToTensorCalculator::AppendZerosToSampleBuffer(int num_samples) {
CHECK_GE(num_samples, 0); // Ensured by `UpdateContract`.
ABSL_CHECK_GE(num_samples, 0); // Ensured by `UpdateContract`.
if (num_samples == 0) {
return;
}
@@ -18,6 +18,7 @@
#include <utility>
#include <vector>
#include "absl/log/absl_check.h"
#include "mediapipe/calculators/tensor/feedback_tensors_calculator.pb.h"
#include "mediapipe/framework/calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
@@ -65,7 +66,7 @@ template <typename T>
Tensor MakeTensor(std::initializer_list<int> shape,
std::initializer_list<T> values) {
Tensor tensor(TensorElementType<T>::value, shape);
CHECK_EQ(values.size(), tensor.shape().num_elements())
ABSL_CHECK_EQ(values.size(), tensor.shape().num_elements())
<< "The size of `values` is incompatible with `shape`";
absl::c_copy(values, tensor.GetCpuWriteView().buffer<T>());
return tensor;
@@ -16,6 +16,7 @@
#include <memory>
#include <vector>
#include "absl/log/absl_log.h"
#include "mediapipe/calculators/tensor/image_to_tensor_calculator.pb.h"
#include "mediapipe/calculators/tensor/image_to_tensor_converter.h"
#include "mediapipe/calculators/tensor/image_to_tensor_utils.h"
@@ -284,9 +285,9 @@ class ImageToTensorCalculator : public Node {
cc, GetBorderMode(options_.border_mode()),
GetOutputTensorType(/*uses_gpu=*/false, params_)));
#else
LOG(FATAL) << "Cannot create image to tensor CPU converter since "
"MEDIAPIPE_DISABLE_OPENCV is defined and "
"MEDIAPIPE_ENABLE_HALIDE is not defined.";
ABSL_LOG(FATAL) << "Cannot create image to tensor CPU converter since "
"MEDIAPIPE_DISABLE_OPENCV is defined and "
"MEDIAPIPE_ENABLE_HALIDE is not defined.";
#endif // !MEDIAPIPE_DISABLE_HALIDE
}
}
@@ -18,6 +18,7 @@
#include <vector>
#include "absl/flags/flag.h"
#include "absl/log/absl_check.h"
#include "absl/memory/memory.h"
#include "absl/strings/str_format.h"
#include "absl/strings/substitute.h"
@@ -205,7 +206,7 @@ mediapipe::ImageFormat::Format GetImageFormat(int image_channels) {
} else if (image_channels == 1) {
return ImageFormat::GRAY8;
}
CHECK(false) << "Unsupported input image channles: " << image_channels;
ABSL_CHECK(false) << "Unsupported input image channles: " << image_channels;
}
Packet MakeImageFramePacket(cv::Mat input) {
@@ -22,6 +22,7 @@
#include <memory>
#include <vector>
#include "absl/log/absl_log.h"
#include "absl/strings/str_cat.h"
#include "mediapipe/calculators/tensor/image_to_tensor_converter.h"
#include "mediapipe/calculators/tensor/image_to_tensor_converter_gl_utils.h"
@@ -259,7 +260,7 @@ class GlProcessor : public ImageToTensorConverter {
// error. So in that case, we'll grab the transpose of our original matrix
// and send that instead.
const auto gl_context = mediapipe::GlContext::GetCurrent();
LOG_IF(FATAL, !gl_context) << "GlContext is not bound to the thread.";
ABSL_LOG_IF(FATAL, !gl_context) << "GlContext is not bound to the thread.";
if (gl_context->GetGlVersion() == mediapipe::GlVersion::kGLES2) {
GetTransposedRotatedSubRectToRectTransformMatrix(
sub_rect, texture.width(), texture.height(), flip_horizontaly,
@@ -88,6 +88,20 @@ message InferenceCalculatorOptions {
// serialized model is invalid or missing.
optional string serialized_model_dir = 7;
enum CacheWritingBehavior {
// Do not write any caches.
NO_WRITE = 0;
// Try to write caches, log on failure.
TRY_WRITE = 1;
// Write caches or return an error if write fails.
WRITE_OR_ERROR = 2;
}
// Specifies how GPU caches are written to disk.
optional CacheWritingBehavior cache_writing_behavior = 10
[default = WRITE_OR_ERROR];
// Unique token identifying the model. Used in conjunction with
// "serialized_model_dir". It is the caller's responsibility to ensure
// there is no clash of the tokens.
@@ -12,6 +12,7 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include <cstdint>
#include <cstring>
#include <memory>
#include <string>
@@ -26,6 +27,7 @@
#include "mediapipe/util/tflite/tflite_gpu_runner.h"
#if defined(MEDIAPIPE_ANDROID) || defined(MEDIAPIPE_CHROMIUMOS)
#include "absl/log/absl_log.h"
#include "mediapipe/framework/deps/file_path.h"
#include "mediapipe/util/android/file/base/file.h"
#include "mediapipe/util/android/file/base/filesystem.h"
@@ -68,14 +70,21 @@ class InferenceCalculatorGlAdvancedImpl
const mediapipe::InferenceCalculatorOptions::Delegate::Gpu&
gpu_delegate_options);
absl::Status ReadGpuCaches(tflite::gpu::TFLiteGPURunner* gpu_runner) const;
absl::Status SaveGpuCaches(tflite::gpu::TFLiteGPURunner* gpu_runner) const;
// Writes caches to disk based on |cache_writing_behavior_|.
absl::Status SaveGpuCachesBasedOnBehavior(
tflite::gpu::TFLiteGPURunner* gpu_runner) const;
bool UseSerializedModel() const { return use_serialized_model_; }
private:
// Writes caches to disk, returns error on failure.
absl::Status SaveGpuCaches(tflite::gpu::TFLiteGPURunner* gpu_runner) const;
bool use_kernel_caching_ = false;
std::string cached_kernel_filename_;
bool use_serialized_model_ = false;
std::string serialized_model_path_;
mediapipe::InferenceCalculatorOptions::Delegate::Gpu::CacheWritingBehavior
cache_writing_behavior_;
};
// Helper class that wraps everything related to GPU inference acceleration.
@@ -232,7 +241,8 @@ InferenceCalculatorGlAdvancedImpl::GpuInferenceRunner::InitTFLiteGPURunner(
MP_RETURN_IF_ERROR(
on_disk_cache_helper_.ReadGpuCaches(tflite_gpu_runner_.get()));
MP_RETURN_IF_ERROR(tflite_gpu_runner_->Build());
return on_disk_cache_helper_.SaveGpuCaches(tflite_gpu_runner_.get());
return on_disk_cache_helper_.SaveGpuCachesBasedOnBehavior(
tflite_gpu_runner_.get());
}
#if defined(MEDIAPIPE_ANDROID) || defined(MEDIAPIPE_CHROMIUMOS)
@@ -261,9 +271,36 @@ absl::Status InferenceCalculatorGlAdvancedImpl::OnDiskCacheHelper::Init(
mediapipe::file::JoinPath(gpu_delegate_options.serialized_model_dir(),
gpu_delegate_options.model_token());
}
cache_writing_behavior_ = gpu_delegate_options.has_cache_writing_behavior()
? gpu_delegate_options.cache_writing_behavior()
: mediapipe::InferenceCalculatorOptions::
Delegate::Gpu::WRITE_OR_ERROR;
return absl::OkStatus();
}
absl::Status InferenceCalculatorGlAdvancedImpl::OnDiskCacheHelper::
SaveGpuCachesBasedOnBehavior(
tflite::gpu::TFLiteGPURunner* gpu_runner) const {
switch (cache_writing_behavior_) {
case mediapipe::InferenceCalculatorOptions::Delegate::Gpu::NO_WRITE:
return absl::OkStatus();
case mediapipe::InferenceCalculatorOptions::Delegate::Gpu::TRY_WRITE: {
auto status = SaveGpuCaches(gpu_runner);
if (!status.ok()) {
ABSL_LOG_FIRST_N(WARNING, 1) << "Failed to save gpu caches: " << status;
}
return absl::OkStatus();
}
case mediapipe::InferenceCalculatorOptions::Delegate::Gpu::WRITE_OR_ERROR:
return SaveGpuCaches(gpu_runner);
default:
ABSL_LOG_FIRST_N(ERROR, 1)
<< "Unknown cache writing behavior: "
<< static_cast<uint32_t>(cache_writing_behavior_);
return absl::InvalidArgumentError("Unknown cache writing behavior.");
}
}
absl::Status
InferenceCalculatorGlAdvancedImpl::OnDiskCacheHelper::SaveGpuCaches(
tflite::gpu::TFLiteGPURunner* gpu_runner) const {
@@ -318,6 +355,12 @@ absl::Status InferenceCalculatorGlAdvancedImpl::OnDiskCacheHelper::Init(
return absl::OkStatus();
}
absl::Status InferenceCalculatorGlAdvancedImpl::OnDiskCacheHelper::
SaveGpuCachesBasedOnBehavior(
tflite::gpu::TFLiteGPURunner* gpu_runner) const {
return absl::OkStatus();
}
absl::Status
InferenceCalculatorGlAdvancedImpl::OnDiskCacheHelper::ReadGpuCaches(
tflite::gpu::TFLiteGPURunner* gpu_runner) const {
@@ -21,6 +21,7 @@
#include <string>
#include <vector>
#include "absl/log/absl_log.h"
#include "absl/memory/memory.h"
#include "absl/strings/str_format.h"
#include "mediapipe/calculators/tensor/inference_calculator.h"
@@ -74,7 +75,7 @@ tflite::gpu::BHWC BhwcFromTensorShape(const Tensor::Shape& shape) {
break;
default:
// Handles 0 and >4.
LOG(FATAL)
ABSL_LOG(FATAL)
<< "Dimensions size must be in range [1,4] for GPU inference, but "
<< shape.dims.size() << " is provided";
}
@@ -16,7 +16,7 @@
#include <string>
#include <vector>
#include "absl/log/check.h"
#include "absl/log/absl_check.h"
#include "absl/strings/str_cat.h"
#include "absl/strings/str_replace.h"
#include "absl/strings/string_view.h"
@@ -12,9 +12,15 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include <cstdint>
#include <string>
#include <vector>
#include "absl/log/absl_check.h"
#include "absl/log/absl_log.h"
#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/str_format.h"
#include "mediapipe/calculators/tensor/tensor_converter_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/formats/image_frame.h"
@@ -22,7 +28,8 @@
#include "mediapipe/framework/formats/tensor.h"
#include "mediapipe/framework/port.h"
#include "mediapipe/framework/port/ret_check.h"
#include "mediapipe/util/resource_util.h"
#include "mediapipe/gpu/gpu_buffer_format.h"
#include "mediapipe/gpu/gpu_origin.pb.h"
#if !MEDIAPIPE_DISABLE_GPU
#include "mediapipe/gpu/gpu_buffer.h"
@@ -43,12 +50,50 @@
#endif // !MEDIAPIPE_DISABLE_GPU
namespace {
constexpr int kWorkgroupSize = 8; // Block size for GPU shader.
// Commonly used to compute the number of blocks to launch in a kernel.
int NumGroups(const int size, const int group_size) { // NOLINT
return (size + group_size - 1) / group_size;
}
absl::StatusOr<bool> ShouldFlipVertically(
const mediapipe::TensorConverterCalculatorOptions& options, bool use_gpu) {
if (options.has_flip_vertically() && options.has_gpu_origin()) {
return absl::FailedPreconditionError(absl::StrFormat(
"Cannot specify both flip_vertically and gpu_origin options"));
}
if (!options.has_gpu_origin()) {
// Fall back to flip_vertically.
return options.flip_vertically();
}
// Warn if gpu_origin is specified with a CPU input image.
// Those are always TOP_LEFT, so no flipping is necessary.
if (!use_gpu) {
ABSL_LOG(WARNING)
<< "Ignoring gpu_origin option since IMAGE_GPU input is not specified";
return false;
}
switch (options.gpu_origin()) {
case mediapipe::GpuOrigin::TOP_LEFT:
return false;
case mediapipe::GpuOrigin::DEFAULT:
case mediapipe::GpuOrigin::CONVENTIONAL:
// TOP_LEFT on Metal, BOTTOM_LEFT on OpenGL.
#ifdef __APPLE__
return false;
#else
return true;
#endif
default:
return absl::InvalidArgumentError(
absl::StrFormat("Unhandled GPU origin %i", options.gpu_origin()));
}
}
typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>
RowMajorMatrixXf;
typedef Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::ColMajor>
@@ -58,6 +103,7 @@ constexpr char kImageFrameTag[] = "IMAGE";
constexpr char kGpuBufferTag[] = "IMAGE_GPU";
constexpr char kTensorsTag[] = "TENSORS";
constexpr char kMatrixTag[] = "MATRIX";
} // namespace
namespace mediapipe {
@@ -109,7 +155,7 @@ class TensorConverterCalculator : public CalculatorBase {
private:
absl::Status InitGpu(CalculatorContext* cc);
absl::Status LoadOptions(CalculatorContext* cc);
absl::Status LoadOptions(CalculatorContext* cc, bool use_gpu);
template <class T>
absl::Status NormalizeImage(const ImageFrame& image_frame,
bool flip_vertically, float* tensor_ptr);
@@ -145,7 +191,8 @@ absl::Status TensorConverterCalculator::GetContract(CalculatorContract* cc) {
RET_CHECK(static_cast<int>(cc->Inputs().HasTag(kImageFrameTag)) +
static_cast<int>(cc->Inputs().HasTag(kGpuBufferTag)) +
static_cast<int>(cc->Inputs().HasTag(kMatrixTag)) ==
1);
1)
<< "Only one input tag of {IMAGE, IMAGE_GPU, MATRIX} may be specified";
if (cc->Inputs().HasTag(kImageFrameTag)) {
cc->Inputs().Tag(kImageFrameTag).Set<ImageFrame>();
@@ -173,8 +220,6 @@ absl::Status TensorConverterCalculator::GetContract(CalculatorContract* cc) {
absl::Status TensorConverterCalculator::Open(CalculatorContext* cc) {
cc->SetOffset(TimestampDiff(0));
MP_RETURN_IF_ERROR(LoadOptions(cc));
#if !MEDIAPIPE_DISABLE_GPU
if (cc->Inputs().HasTag(kGpuBufferTag)) {
use_gpu_ = true;
@@ -187,6 +232,8 @@ absl::Status TensorConverterCalculator::Open(CalculatorContext* cc) {
}
#endif // !MEDIAPIPE_DISABLE_GPU
MP_RETURN_IF_ERROR(LoadOptions(cc, use_gpu_));
return absl::OkStatus();
}
@@ -378,23 +425,34 @@ absl::Status TensorConverterCalculator::InitGpu(CalculatorContext* cc) {
// Get input image sizes.
const auto& input =
cc->Inputs().Tag(kGpuBufferTag).Get<mediapipe::GpuBuffer>();
mediapipe::ImageFormat::Format format =
mediapipe::ImageFormatForGpuBufferFormat(input.format());
mediapipe::GpuBufferFormat format = input.format();
const bool include_alpha = (max_num_channels_ == 4);
const bool single_channel = (max_num_channels_ == 1);
if (!(format == mediapipe::ImageFormat::GRAY8 ||
format == mediapipe::ImageFormat::SRGB ||
format == mediapipe::ImageFormat::SRGBA))
RET_CHECK_FAIL() << "Unsupported GPU input format.";
if (include_alpha && (format != mediapipe::ImageFormat::SRGBA))
RET_CHECK_FAIL() << "Num input channels is less than desired output.";
RET_CHECK(format == mediapipe::GpuBufferFormat::kBGRA32 ||
format == mediapipe::GpuBufferFormat::kRGB24 ||
format == mediapipe::GpuBufferFormat::kRGBA32 ||
format == mediapipe::GpuBufferFormat::kRGBAFloat128 ||
format == mediapipe::GpuBufferFormat::kRGBAHalf64 ||
format == mediapipe::GpuBufferFormat::kGrayFloat32 ||
format == mediapipe::GpuBufferFormat::kGrayHalf16 ||
format == mediapipe::GpuBufferFormat::kOneComponent8)
<< "Unsupported GPU input format: " << static_cast<uint32_t>(format);
if (include_alpha) {
RET_CHECK(format == mediapipe::GpuBufferFormat::kBGRA32 ||
format == mediapipe::GpuBufferFormat::kRGBA32 ||
format == mediapipe::GpuBufferFormat::kRGBAFloat128 ||
format == mediapipe::GpuBufferFormat::kRGBAHalf64)
<< "Num input channels is less than desired output, input format: "
<< static_cast<uint32_t>(format);
}
#if MEDIAPIPE_METAL_ENABLED
id<MTLDevice> device = gpu_helper_.mtlDevice;
// Shader to convert GL Texture to Metal Buffer,
// with normalization to either: [0,1] or [-1,1].
const std::string shader_source = absl::Substitute(
R"(
R"glsl(
#include <metal_stdlib>
using namespace metal;
@@ -413,7 +471,7 @@ absl::Status TensorConverterCalculator::InitGpu(CalculatorContext* cc) {
$3 // g & b channels
$4 // alpha channel
}
)",
)glsl",
/*$0=*/
output_range_.has_value()
? absl::Substitute("pixel = pixel * half($0) + half($1);",
@@ -423,8 +481,8 @@ absl::Status TensorConverterCalculator::InitGpu(CalculatorContext* cc) {
/*$1=*/max_num_channels_,
/*$2=*/flip_vertically_ ? "(in_tex.get_height() - 1 - gid.y)" : "gid.y",
/*$3=*/
single_channel ? "" : R"(out_buf[linear_index + 1] = pixel.y;
out_buf[linear_index + 2] = pixel.z;)",
single_channel ? "" : R"glsl(out_buf[linear_index + 1] = pixel.y;
out_buf[linear_index + 2] = pixel.z;)glsl",
/*$4=*/include_alpha ? "out_buf[linear_index + 3] = pixel.w;" : "");
NSString* library_source =
@@ -442,17 +500,17 @@ absl::Status TensorConverterCalculator::InitGpu(CalculatorContext* cc) {
RET_CHECK(to_buffer_program_ != nil) << "Couldn't create pipeline state " <<
[[error localizedDescription] UTF8String];
#elif MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_30
MP_RETURN_IF_ERROR(gpu_helper_.RunInGlContext([this, &include_alpha,
MP_RETURN_IF_ERROR(
gpu_helper_.RunInGlContext([this, &include_alpha,
#if MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
&input,
&input,
#endif // MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
&single_channel]()
-> absl::Status {
&single_channel]() -> absl::Status {
#if MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
// Shader to convert GL Texture to Shader Storage Buffer Object (SSBO),
// with normalization to either: [0,1] or [-1,1].
const std::string shader_source = absl::Substitute(
R"( #version 310 es
// Shader to convert GL Texture to Shader Storage Buffer Object (SSBO),
// with normalization to either: [0,1] or [-1,1].
const std::string shader_source = absl::Substitute(
R"glsl( #version 310 es
layout(local_size_x = $0, local_size_y = $0) in;
layout(binding = 0) uniform sampler2D input_texture;
layout(std430, binding = 1) buffer Output {float elements[];} output_data;
@@ -466,38 +524,40 @@ absl::Status TensorConverterCalculator::InitGpu(CalculatorContext* cc) {
output_data.elements[linear_index + 0] = pixel.x; // r channel
$5 // g & b channels
$6 // alpha channel
})",
/*$0=*/kWorkgroupSize, /*$1=*/input.width(), /*$2=*/input.height(),
/*$3=*/
output_range_.has_value()
? absl::Substitute("pixel = pixel * float($0) + float($1);",
(output_range_->second - output_range_->first),
output_range_->first)
: "",
/*$4=*/flip_vertically_ ? "(width_height.y - 1 - gid.y)" : "gid.y",
/*$5=*/
single_channel ? ""
: R"(output_data.elements[linear_index + 1] = pixel.y;
output_data.elements[linear_index + 2] = pixel.z;)",
/*$6=*/
include_alpha ? "output_data.elements[linear_index + 3] = pixel.w;"
: "",
/*$7=*/max_num_channels_);
GLuint shader = glCreateShader(GL_COMPUTE_SHADER);
const GLchar* sources[] = {shader_source.c_str()};
glShaderSource(shader, 1, sources, NULL);
glCompileShader(shader);
GLint compiled = GL_FALSE;
glGetShaderiv(shader, GL_COMPILE_STATUS, &compiled);
RET_CHECK(compiled == GL_TRUE);
to_buffer_program_ = glCreateProgram();
glAttachShader(to_buffer_program_, shader);
glDeleteShader(shader);
glLinkProgram(to_buffer_program_);
})glsl",
/*$0=*/kWorkgroupSize, /*$1=*/input.width(), /*$2=*/input.height(),
/*$3=*/
output_range_.has_value()
? absl::Substitute(
"pixel = pixel * float($0) + float($1);",
(output_range_->second - output_range_->first),
output_range_->first)
: "",
/*$4=*/flip_vertically_ ? "(width_height.y - 1 - gid.y)" : "gid.y",
/*$5=*/
single_channel
? ""
: R"glsl(output_data.elements[linear_index + 1] = pixel.y;
output_data.elements[linear_index + 2] = pixel.z;)glsl",
/*$6=*/
include_alpha ? "output_data.elements[linear_index + 3] = pixel.w;"
: "",
/*$7=*/max_num_channels_);
GLuint shader = glCreateShader(GL_COMPUTE_SHADER);
const GLchar* sources[] = {shader_source.c_str()};
glShaderSource(shader, 1, sources, NULL);
glCompileShader(shader);
GLint compiled = GL_FALSE;
glGetShaderiv(shader, GL_COMPILE_STATUS, &compiled);
RET_CHECK(compiled == GL_TRUE);
to_buffer_program_ = glCreateProgram();
glAttachShader(to_buffer_program_, shader);
glDeleteShader(shader);
glLinkProgram(to_buffer_program_);
#else
// OpenGL ES 3.0 fragment shader Texture2d -> Texture2d conversion.
const std::string shader_source = absl::Substitute(
R"(
// OpenGL ES 3.0 fragment shader Texture2d -> Texture2d conversion.
const std::string shader_source = absl::Substitute(
R"glsl(
#if __VERSION__ < 130
#define in varying
#endif // __VERSION__ < 130
@@ -523,49 +583,51 @@ absl::Status TensorConverterCalculator::InitGpu(CalculatorContext* cc) {
fragColor.r = pixel.r; // r channel
$3 // g & b channels
$4 // alpha channel
})",
/*$0=*/single_channel ? "vec1" : "vec4",
/*$1=*/
flip_vertically_
? "vec2(sample_coordinate.x, 1.0 - sample_coordinate.y);"
: "sample_coordinate;",
/*$2=*/output_range_.has_value()
? absl::Substitute("pixel = pixel * float($0) + float($1);",
(output_range_->second - output_range_->first),
output_range_->first)
: "",
/*$3=*/single_channel ? "" : R"(fragColor.g = pixel.g;
fragColor.b = pixel.b;)",
/*$4=*/
include_alpha ? "fragColor.a = pixel.a;"
: (single_channel ? "" : "fragColor.a = 1.0;"));
})glsl",
/*$0=*/single_channel ? "vec1" : "vec4",
/*$1=*/
flip_vertically_
? "vec2(sample_coordinate.x, 1.0 - sample_coordinate.y);"
: "sample_coordinate;",
/*$2=*/output_range_.has_value()
? absl::Substitute(
"pixel = pixel * float($0) + float($1);",
(output_range_->second - output_range_->first),
output_range_->first)
: "",
/*$3=*/single_channel ? "" : R"glsl(fragColor.g = pixel.g;
fragColor.b = pixel.b;)glsl",
/*$4=*/
include_alpha ? "fragColor.a = pixel.a;"
: (single_channel ? "" : "fragColor.a = 1.0;"));
const GLint attr_location[NUM_ATTRIBUTES] = {
ATTRIB_VERTEX,
ATTRIB_TEXTURE_POSITION,
};
const GLchar* attr_name[NUM_ATTRIBUTES] = {
"position",
"texture_coordinate",
};
// shader program and params
mediapipe::GlhCreateProgram(
mediapipe::kBasicVertexShader, shader_source.c_str(), NUM_ATTRIBUTES,
&attr_name[0], attr_location, &to_tex2d_program_);
RET_CHECK(to_tex2d_program_) << "Problem initializing the program.";
glUseProgram(to_tex2d_program_);
glUniform1i(glGetUniformLocation(to_tex2d_program_, "frame"), 1);
glGenFramebuffers(1, &framebuffer_);
const GLint attr_location[NUM_ATTRIBUTES] = {
ATTRIB_VERTEX,
ATTRIB_TEXTURE_POSITION,
};
const GLchar* attr_name[NUM_ATTRIBUTES] = {
"position",
"texture_coordinate",
};
// shader program and params
mediapipe::GlhCreateProgram(
mediapipe::kBasicVertexShader, shader_source.c_str(),
NUM_ATTRIBUTES, &attr_name[0], attr_location, &to_tex2d_program_);
RET_CHECK(to_tex2d_program_) << "Problem initializing the program.";
glUseProgram(to_tex2d_program_);
glUniform1i(glGetUniformLocation(to_tex2d_program_, "frame"), 1);
glGenFramebuffers(1, &framebuffer_);
#endif // MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_31
return absl::OkStatus();
}));
return absl::OkStatus();
}));
#endif // MEDIAPIPE_OPENGL_ES_VERSION >= MEDIAPIPE_OPENGL_ES_30
#endif // !MEDIAPIPE_DISABLE_GPU
return absl::OkStatus();
}
absl::Status TensorConverterCalculator::LoadOptions(CalculatorContext* cc) {
absl::Status TensorConverterCalculator::LoadOptions(CalculatorContext* cc,
bool use_gpu) {
// Get calculator options specified in the graph.
const auto& options =
cc->Options<::mediapipe::TensorConverterCalculatorOptions>();
@@ -582,7 +644,7 @@ absl::Status TensorConverterCalculator::LoadOptions(CalculatorContext* cc) {
if (options.has_output_tensor_float_range()) {
output_range_.emplace(options.output_tensor_float_range().min(),
options.output_tensor_float_range().max());
CHECK_GT(output_range_->second, output_range_->first);
ABSL_CHECK_GT(output_range_->second, output_range_->first);
}
// Custom div and sub values.
@@ -593,16 +655,16 @@ absl::Status TensorConverterCalculator::LoadOptions(CalculatorContext* cc) {
}
// Get y-flip mode.
flip_vertically_ = options.flip_vertically();
ASSIGN_OR_RETURN(flip_vertically_, ShouldFlipVertically(options, use_gpu));
// Get row_major_matrix mode.
row_major_matrix_ = options.row_major_matrix();
// Get desired way to handle input channels.
max_num_channels_ = options.max_num_channels();
CHECK_GE(max_num_channels_, 1);
CHECK_LE(max_num_channels_, 4);
CHECK_NE(max_num_channels_, 2);
ABSL_CHECK_GE(max_num_channels_, 1);
ABSL_CHECK_LE(max_num_channels_, 4);
ABSL_CHECK_NE(max_num_channels_, 2);
return absl::OkStatus();
}
@@ -3,6 +3,7 @@ syntax = "proto2";
package mediapipe;
import "mediapipe/framework/calculator.proto";
import "mediapipe/gpu/gpu_origin.proto";
// Full Example:
//
@@ -43,8 +44,16 @@ message TensorConverterCalculatorOptions {
// with a coordinate system where the origin is at the bottom-left corner
// (e.g., in OpenGL) whereas the ML model expects an image with a top-left
// origin.
// Prefer gpu_origin over this field when using GPU input images.
optional bool flip_vertically = 2 [default = false];
// Determines when the input GPU image should be flipped vertically.
// See GpuOrigin.Mode for more information.
// Affects only IMAGE_GPU inputs.
// If unset, falls back to flip_vertically for backwards compatibility.
// Cannot set both gpu_origin and flip_vertically.
optional GpuOrigin.Mode gpu_origin = 10;
// Controls how many channels of the input image get passed through to the
// tensor. Valid values are 1,3,4 only. Ignored for iOS GPU.
optional int32 max_num_channels = 3 [default = 3];
@@ -12,10 +12,15 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include <cmath>
#include <cstdint>
#include <memory>
#include <random>
#include <utility>
#include <vector>
#include "absl/memory/memory.h"
#include "absl/status/status.h"
#include "absl/strings/substitute.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/calculator_runner.h"
@@ -24,8 +29,10 @@
#include "mediapipe/framework/formats/image_frame_opencv.h"
#include "mediapipe/framework/formats/matrix.h"
#include "mediapipe/framework/formats/tensor.h"
#include "mediapipe/framework/port/gmock.h"
#include "mediapipe/framework/port/gtest.h"
#include "mediapipe/framework/port/integral_types.h"
#include "mediapipe/framework/port/opencv_core_inc.h"
#include "mediapipe/framework/port/parse_text_proto.h"
#include "mediapipe/framework/port/status_matchers.h" // NOLINT
#include "mediapipe/framework/tool/validate_type.h"
@@ -40,7 +47,7 @@ constexpr char kTransposeOptionsString[] =
} // namespace
using RandomEngine = std::mt19937_64;
using testing::Eq;
using ::testing::HasSubstr;
const uint32_t kSeed = 1234;
const int kNumSizes = 8;
const int sizes[kNumSizes][2] = {{1, 1}, {12, 1}, {1, 9}, {2, 2},
@@ -53,7 +60,7 @@ class TensorConverterCalculatorTest : public ::testing::Test {
bool row_major_matrix = false) {
RandomEngine random(kSeed);
std::uniform_real_distribution<> uniform_dist(0, 1.0);
auto matrix = ::absl::make_unique<Matrix>();
auto matrix = std::make_unique<Matrix>();
matrix->resize(num_rows, num_columns);
if (row_major_matrix) {
for (int y = 0; y < num_rows; ++y) {
@@ -101,7 +108,7 @@ TEST_F(TensorConverterCalculatorTest, RandomMatrixColMajor) {
tool::AddVectorSink("tensor", &graph_config, &output_packets);
// Run the graph.
graph_ = absl::make_unique<CalculatorGraph>();
graph_ = std::make_unique<CalculatorGraph>();
MP_ASSERT_OK(graph_->Initialize(graph_config));
MP_ASSERT_OK(graph_->StartRun({}));
@@ -110,12 +117,12 @@ TEST_F(TensorConverterCalculatorTest, RandomMatrixColMajor) {
// Wait until the calculator done processing.
MP_ASSERT_OK(graph_->WaitUntilIdle());
EXPECT_EQ(1, output_packets.size());
ASSERT_EQ(output_packets.size(), 1);
// Get and process results.
const std::vector<Tensor>& tensor_vec =
output_packets[0].Get<std::vector<Tensor>>();
EXPECT_EQ(1, tensor_vec.size());
ASSERT_EQ(tensor_vec.size(), 1);
const Tensor* tensor = &tensor_vec[0];
EXPECT_EQ(Tensor::ElementType::kFloat32, tensor->element_type());
@@ -127,7 +134,7 @@ TEST_F(TensorConverterCalculatorTest, RandomMatrixColMajor) {
auto tensor_buffer = view.buffer<float>();
for (int i = 0; i < num_rows * num_columns; ++i) {
const float expected = uniform_dist(random);
EXPECT_EQ(expected, tensor_buffer[i]) << "at i = " << i;
EXPECT_FLOAT_EQ(tensor_buffer[i], expected) << "at i = " << i;
}
// Fully close graph at end, otherwise calculator+tensors are destroyed
@@ -163,7 +170,7 @@ TEST_F(TensorConverterCalculatorTest, RandomMatrixRowMajor) {
tool::AddVectorSink("tensor", &graph_config, &output_packets);
// Run the graph.
graph_ = absl::make_unique<CalculatorGraph>();
graph_ = std::make_unique<CalculatorGraph>();
MP_ASSERT_OK(graph_->Initialize(graph_config));
MP_ASSERT_OK(graph_->StartRun({}));
@@ -172,12 +179,12 @@ TEST_F(TensorConverterCalculatorTest, RandomMatrixRowMajor) {
// Wait until the calculator done processing.
MP_ASSERT_OK(graph_->WaitUntilIdle());
EXPECT_EQ(1, output_packets.size());
ASSERT_EQ(output_packets.size(), 1);
// Get and process results.
const std::vector<Tensor>& tensor_vec =
output_packets[0].Get<std::vector<Tensor>>();
EXPECT_EQ(1, tensor_vec.size());
ASSERT_EQ(tensor_vec.size(), 1);
const Tensor* tensor = &tensor_vec[0];
EXPECT_EQ(Tensor::ElementType::kFloat32, tensor->element_type());
@@ -189,7 +196,7 @@ TEST_F(TensorConverterCalculatorTest, RandomMatrixRowMajor) {
auto tensor_buffer = view.buffer<float>();
for (int i = 0; i < num_rows * num_columns; ++i) {
const float expected = uniform_dist(random);
EXPECT_EQ(expected, tensor_buffer[i]) << "at i = " << i;
EXPECT_EQ(tensor_buffer[i], expected) << "at i = " << i;
}
// Fully close graph at end, otherwise calculator+tensors are destroyed
@@ -227,7 +234,7 @@ TEST_F(TensorConverterCalculatorTest, CustomDivAndSub) {
// Run the graph.
MP_ASSERT_OK(graph.Initialize(graph_config));
MP_ASSERT_OK(graph.StartRun({}));
auto input_image = absl::make_unique<ImageFrame>(ImageFormat::GRAY8, 1, 1);
auto input_image = std::make_unique<ImageFrame>(ImageFormat::GRAY8, 1, 1);
cv::Mat mat = mediapipe::formats::MatView(input_image.get());
mat.at<uint8_t>(0, 0) = 200;
MP_ASSERT_OK(graph.AddPacketToInputStream(
@@ -239,12 +246,12 @@ TEST_F(TensorConverterCalculatorTest, CustomDivAndSub) {
// Get and process results.
const std::vector<Tensor>& tensor_vec =
output_packets[0].Get<std::vector<Tensor>>();
EXPECT_EQ(1, tensor_vec.size());
ASSERT_EQ(tensor_vec.size(), 1);
const Tensor* tensor = &tensor_vec[0];
EXPECT_EQ(Tensor::ElementType::kFloat32, tensor->element_type());
auto view = tensor->GetCpuReadView();
EXPECT_FLOAT_EQ(67.0f, *view.buffer<float>());
EXPECT_FLOAT_EQ(*view.buffer<float>(), 67.0f);
// Fully close graph at end, otherwise calculator+tensors are destroyed
// after calling WaitUntilDone().
@@ -259,32 +266,29 @@ TEST_F(TensorConverterCalculatorTest, SetOutputRange) {
for (std::pair<float, float> range : range_values) {
CalculatorGraph graph;
CalculatorGraphConfig graph_config =
mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(
absl::Substitute(R"(
input_stream: "input_image"
node {
calculator: "TensorConverterCalculator"
input_stream: "IMAGE:input_image"
output_stream: "TENSORS:tensor"
options {
[mediapipe.TensorConverterCalculatorOptions.ext] {
output_tensor_float_range {
min: $0
max: $1
mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(absl::Substitute(
R"pb(
input_stream: "input_image"
node {
calculator: "TensorConverterCalculator"
input_stream: "IMAGE:input_image"
output_stream: "TENSORS:tensor"
options {
[mediapipe.TensorConverterCalculatorOptions.ext] {
output_tensor_float_range { min: $0 max: $1 }
}
}
}
}
}
}
)",
/*$0=*/range.first,
/*$1=*/range.second));
)pb",
/*$0=*/range.first,
/*$1=*/range.second));
std::vector<Packet> output_packets;
tool::AddVectorSink("tensor", &graph_config, &output_packets);
// Run the graph.
MP_ASSERT_OK(graph.Initialize(graph_config));
MP_ASSERT_OK(graph.StartRun({}));
auto input_image = absl::make_unique<ImageFrame>(ImageFormat::GRAY8, 1, 1);
auto input_image = std::make_unique<ImageFrame>(ImageFormat::GRAY8, 1, 1);
cv::Mat mat = mediapipe::formats::MatView(input_image.get());
mat.at<uint8_t>(0, 0) = 200;
MP_ASSERT_OK(graph.AddPacketToInputStream(
@@ -292,26 +296,23 @@ TEST_F(TensorConverterCalculatorTest, SetOutputRange) {
// Wait until the calculator finishes processing.
MP_ASSERT_OK(graph.WaitUntilIdle());
EXPECT_THAT(output_packets.size(), Eq(1));
ASSERT_EQ(output_packets.size(), 1);
// Get and process results.
const std::vector<Tensor>& tensor_vec =
output_packets[0].Get<std::vector<Tensor>>();
EXPECT_THAT(tensor_vec.size(), Eq(1));
ASSERT_EQ(tensor_vec.size(), 1);
const Tensor* tensor = &tensor_vec[0];
// Calculate the expected normalized value:
float normalized_value =
float expected_value =
range.first + (200 * (range.second - range.first)) / 255.0;
EXPECT_THAT(tensor->element_type(), Eq(Tensor::ElementType::kFloat32));
EXPECT_EQ(tensor->element_type(), Tensor::ElementType::kFloat32);
auto view = tensor->GetCpuReadView();
float dataf = *view.buffer<float>();
EXPECT_THAT(
normalized_value,
testing::FloatNear(dataf, 2.0f * std::abs(dataf) *
std::numeric_limits<float>::epsilon()));
float actual_value = *view.buffer<float>();
EXPECT_FLOAT_EQ(actual_value, expected_value);
// Fully close graph at end, otherwise calculator+tensors are destroyed
// after calling WaitUntilDone().
@@ -320,4 +321,153 @@ TEST_F(TensorConverterCalculatorTest, SetOutputRange) {
}
}
TEST_F(TensorConverterCalculatorTest, FlipVertically) {
CalculatorGraph graph;
CalculatorGraphConfig graph_config =
mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(R"pb(
input_stream: "input_image"
node {
calculator: "TensorConverterCalculator"
input_stream: "IMAGE:input_image"
output_stream: "TENSORS:tensor"
options {
[mediapipe.TensorConverterCalculatorOptions.ext] {
flip_vertically: true
output_tensor_float_range { min: 0 max: 255 }
}
}
}
)pb");
std::vector<Packet> output_packets;
tool::AddVectorSink("tensor", &graph_config, &output_packets);
// Run the graph.
MP_ASSERT_OK(graph.Initialize(graph_config));
MP_ASSERT_OK(graph.StartRun({}));
auto input_image = std::make_unique<ImageFrame>(ImageFormat::GRAY8, 1, 2);
cv::Mat mat = mediapipe::formats::MatView(input_image.get());
constexpr uint8_t kY0Value = 100;
constexpr uint8_t kY1Value = 200;
mat.at<uint8_t>(0, 0) = kY0Value;
mat.at<uint8_t>(1, 0) = kY1Value; // Note: y, x!
MP_ASSERT_OK(graph.AddPacketToInputStream(
"input_image", Adopt(input_image.release()).At(Timestamp(0))));
// Wait until the calculator finishes processing.
MP_ASSERT_OK(graph.WaitUntilIdle());
ASSERT_EQ(output_packets.size(), 1);
// Get and process results.
const std::vector<Tensor>& tensor_vec =
output_packets[0].Get<std::vector<Tensor>>();
ASSERT_EQ(tensor_vec.size(), 1);
const Tensor* tensor = &tensor_vec[0];
EXPECT_EQ(tensor->element_type(), Tensor::ElementType::kFloat32);
const float* dataf = tensor->GetCpuReadView().buffer<float>();
EXPECT_EQ(static_cast<int>(roundf(dataf[0])), kY1Value); // Y0, Y1 flipped!
EXPECT_EQ(static_cast<int>(roundf(dataf[1])), kY0Value);
// Fully close graph at end, otherwise calculator+tensors are destroyed
// after calling WaitUntilDone().
MP_ASSERT_OK(graph.CloseInputStream("input_image"));
MP_ASSERT_OK(graph.WaitUntilDone());
}
TEST_F(TensorConverterCalculatorTest,
CannotSpecifyBothFlipVerticallyAndGpuOrigin) {
CalculatorGraph graph;
CalculatorGraphConfig graph_config =
mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(R"pb(
input_stream: "input_image"
node {
calculator: "TensorConverterCalculator"
input_stream: "IMAGE:input_image"
output_stream: "TENSORS:tensor"
options {
[mediapipe.TensorConverterCalculatorOptions.ext] {
flip_vertically: true
gpu_origin: TOP_LEFT
output_tensor_float_range { min: 0 max: 255 }
}
}
}
)pb");
std::vector<Packet> output_packets;
tool::AddVectorSink("tensor", &graph_config, &output_packets);
// Run the graph.
MP_ASSERT_OK(graph.Initialize(graph_config));
MP_ASSERT_OK(graph.StartRun({}));
auto input_image = std::make_unique<ImageFrame>(ImageFormat::GRAY8, 1, 1);
MP_ASSERT_OK(graph.AddPacketToInputStream(
"input_image", Adopt(input_image.release()).At(Timestamp(0))));
// Processing should fail as we specified both flip_vertically and gpu_origin.
absl::Status status = graph.WaitUntilIdle();
EXPECT_FALSE(status.ok());
EXPECT_THAT(status.message(), HasSubstr("flip_vertically and gpu_origin"));
EXPECT_EQ(output_packets.size(), 0);
// Fully close graph at end, otherwise calculator+tensors are destroyed
// after calling WaitUntilDone().
MP_ASSERT_OK(graph.CloseInputStream("input_image"));
EXPECT_FALSE(graph.WaitUntilDone().ok());
}
TEST_F(TensorConverterCalculatorTest, GpuOriginIsIgnoredWithCpuImage) {
CalculatorGraph graph;
CalculatorGraphConfig graph_config =
mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(R"pb(
input_stream: "input_image"
node {
calculator: "TensorConverterCalculator"
input_stream: "IMAGE:input_image"
output_stream: "TENSORS:tensor"
options {
[mediapipe.TensorConverterCalculatorOptions.ext] {
gpu_origin: CONVENTIONAL
output_tensor_float_range { min: 0 max: 255 }
}
}
}
)pb");
std::vector<Packet> output_packets;
tool::AddVectorSink("tensor", &graph_config, &output_packets);
// Run the graph.
MP_ASSERT_OK(graph.Initialize(graph_config));
MP_ASSERT_OK(graph.StartRun({}));
auto input_image = std::make_unique<ImageFrame>(ImageFormat::GRAY8, 1, 2);
cv::Mat mat = mediapipe::formats::MatView(input_image.get());
constexpr uint8_t kY0Value = 100;
constexpr uint8_t kY1Value = 200;
mat.at<uint8_t>(0, 0) = kY0Value;
mat.at<uint8_t>(1, 0) = kY1Value; // Note: y, x!
MP_ASSERT_OK(graph.AddPacketToInputStream(
"input_image", Adopt(input_image.release()).At(Timestamp(0))));
// Wait until the calculator finishes processing.
MP_ASSERT_OK(graph.WaitUntilIdle());
ASSERT_EQ(output_packets.size(), 1);
// Get and process results.
const std::vector<Tensor>& tensor_vec =
output_packets[0].Get<std::vector<Tensor>>();
ASSERT_EQ(tensor_vec.size(), 1);
const Tensor* tensor = &tensor_vec[0];
EXPECT_EQ(tensor->element_type(), Tensor::ElementType::kFloat32);
const float* dataf = tensor->GetCpuReadView().buffer<float>();
EXPECT_EQ(static_cast<int>(roundf(dataf[0])), kY0Value); // Not flipped!
EXPECT_EQ(static_cast<int>(roundf(dataf[1])), kY1Value);
// Fully close graph at end, otherwise calculator+tensors are destroyed
// after calling WaitUntilDone().
MP_ASSERT_OK(graph.CloseInputStream("input_image"));
MP_ASSERT_OK(graph.WaitUntilDone());
}
} // namespace mediapipe
@@ -15,6 +15,7 @@
#include <unordered_map>
#include <vector>
#include "absl/log/absl_log.h"
#include "absl/strings/str_format.h"
#include "absl/types/span.h"
#include "mediapipe/calculators/tensor/tensors_to_detections_calculator.pb.h"
@@ -83,7 +84,7 @@ void ConvertRawValuesToAnchors(const float* raw_anchors, int num_boxes,
void ConvertAnchorsToRawValues(const std::vector<Anchor>& anchors,
int num_boxes, float* raw_anchors) {
CHECK_EQ(anchors.size(), num_boxes);
ABSL_CHECK_EQ(anchors.size(), num_boxes);
int box = 0;
for (const auto& anchor : anchors) {
raw_anchors[box * kNumCoordsPerBox + 0] = anchor.y_center();
@@ -329,7 +330,7 @@ absl::Status TensorsToDetectionsCalculator::Process(CalculatorContext* cc) {
} else if (status.code() == absl::StatusCode::kFailedPrecondition) {
// For initialization error because of hardware limitation, fallback to
// CPU processing.
LOG(WARNING) << status.message();
ABSL_LOG(WARNING) << status.message();
} else {
// For other error, let the error propagates.
return status;
@@ -668,7 +669,7 @@ absl::Status TensorsToDetectionsCalculator::ProcessGPU(
output_detections));
#else
LOG(ERROR) << "GPU input on non-Android not supported yet.";
ABSL_LOG(ERROR) << "GPU input on non-Android not supported yet.";
#endif // !defined(MEDIAPIPE_DISABLE_GL_COMPUTE)
return absl::OkStatus();
}
@@ -703,18 +704,18 @@ absl::Status TensorsToDetectionsCalculator::LoadOptions(CalculatorContext* cc) {
num_boxes_ = options_.num_boxes();
num_coords_ = options_.num_coords();
box_output_format_ = GetBoxFormat(options_);
CHECK_NE(options_.max_results(), 0)
ABSL_CHECK_NE(options_.max_results(), 0)
<< "The maximum number of the top-scored detection results must be "
"non-zero.";
max_results_ = options_.max_results();
// Currently only support 2D when num_values_per_keypoint equals to 2.
CHECK_EQ(options_.num_values_per_keypoint(), 2);
ABSL_CHECK_EQ(options_.num_values_per_keypoint(), 2);
// Check if the output size is equal to the requested boxes and keypoints.
CHECK_EQ(options_.num_keypoints() * options_.num_values_per_keypoint() +
kNumCoordsPerBox,
num_coords_);
ABSL_CHECK_EQ(options_.num_keypoints() * options_.num_values_per_keypoint() +
kNumCoordsPerBox,
num_coords_);
if (kSideInIgnoreClasses(cc).IsConnected()) {
RET_CHECK(!kSideInIgnoreClasses(cc).IsEmpty());
@@ -1154,11 +1155,12 @@ void main() {
}
// TODO support better filtering.
if (class_index_set_.is_allowlist) {
CHECK_EQ(class_index_set_.values.size(),
IsClassIndexAllowed(0) ? num_classes_ : num_classes_ - 1)
ABSL_CHECK_EQ(class_index_set_.values.size(),
IsClassIndexAllowed(0) ? num_classes_ : num_classes_ - 1)
<< "Only all classes >= class 0 or >= class 1";
} else {
CHECK_EQ(class_index_set_.values.size(), IsClassIndexAllowed(0) ? 0 : 1)
ABSL_CHECK_EQ(class_index_set_.values.size(),
IsClassIndexAllowed(0) ? 0 : 1)
<< "Only ignore class 0 is allowed";
}
@@ -1379,11 +1381,12 @@ kernel void scoreKernel(
// TODO support better filtering.
if (class_index_set_.is_allowlist) {
CHECK_EQ(class_index_set_.values.size(),
IsClassIndexAllowed(0) ? num_classes_ : num_classes_ - 1)
ABSL_CHECK_EQ(class_index_set_.values.size(),
IsClassIndexAllowed(0) ? num_classes_ : num_classes_ - 1)
<< "Only all classes >= class 0 or >= class 1";
} else {
CHECK_EQ(class_index_set_.values.size(), IsClassIndexAllowed(0) ? 0 : 1)
ABSL_CHECK_EQ(class_index_set_.values.size(),
IsClassIndexAllowed(0) ? 0 : 1)
<< "Only ignore class 0 is allowed";
}
@@ -142,7 +142,7 @@ absl::Status TensorsToLandmarksCalculator::Process(CalculatorContext* cc) {
RET_CHECK(input_tensors[0].element_type() == Tensor::ElementType::kFloat32);
int num_values = input_tensors[0].shape().num_elements();
const int num_dimensions = num_values / num_landmarks_;
CHECK_GT(num_dimensions, 0);
ABSL_CHECK_GT(num_dimensions, 0);
auto view = input_tensors[0].GetCpuReadView();
auto raw_landmarks = view.buffer<float>();
+30 -8
View File
@@ -13,6 +13,7 @@
# limitations under the License.
#
# Placeholder: load py_proto_library
load("//mediapipe/framework/port:build_config.bzl", "mediapipe_cc_proto_library", "mediapipe_proto_library")
licenses(["notice"])
@@ -314,6 +315,7 @@ cc_library(
"//mediapipe/framework/formats:time_series_header_cc_proto",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_check",
] + select({
"//conditions:default": [
"@org_tensorflow//tensorflow/core:framework",
@@ -366,18 +368,18 @@ cc_library(
name = "pack_media_sequence_calculator",
srcs = ["pack_media_sequence_calculator.cc"],
deps = [
":pack_media_sequence_calculator_cc_proto",
"//mediapipe/calculators/image:opencv_image_encoder_calculator_cc_proto",
"//mediapipe/calculators/tensorflow:pack_media_sequence_calculator_cc_proto",
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework/formats:detection_cc_proto",
"//mediapipe/framework/formats:location",
"//mediapipe/framework/formats:location_opencv",
"//mediapipe/framework/port:opencv_imgcodecs",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"//mediapipe/util/sequence:media_sequence",
"//mediapipe/util/sequence:media_sequence_util",
"@com_google_absl//absl/container:flat_hash_map",
"@com_google_absl//absl/status",
"@com_google_absl//absl/strings",
"@org_tensorflow//tensorflow/core:protos_all_cc",
],
@@ -429,7 +431,7 @@ cc_library(
"//mediapipe/framework/port:status",
"//mediapipe/framework/tool:status_util",
"@com_google_absl//absl/base:core_headers",
"@com_google_absl//absl/log:check",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/memory",
"@com_google_absl//absl/strings",
"@com_google_absl//absl/synchronization",
@@ -488,10 +490,10 @@ cc_library(
"//mediapipe/calculators/tensorflow:tensorflow_session_from_frozen_graph_calculator_cc_proto",
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework/deps:clock",
"//mediapipe/framework/port:logging",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"//mediapipe/framework/tool:status_util",
"@com_google_absl//absl/log:absl_log",
"@org_tensorflow//tensorflow/core:protos_all_cc",
] + select({
"//conditions:default": [
@@ -519,10 +521,10 @@ cc_library(
":tensorflow_session_from_frozen_graph_generator_cc_proto",
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework/deps:clock",
"//mediapipe/framework/port:logging",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"//mediapipe/framework/tool:status_util",
"@com_google_absl//absl/log:absl_log",
"@org_tensorflow//tensorflow/core:protos_all_cc",
] + select({
"//conditions:default": [
@@ -555,6 +557,7 @@ cc_library(
"//mediapipe/framework/deps:file_path",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_log",
"@com_google_absl//absl/strings",
"@org_tensorflow//tensorflow/cc/saved_model:constants",
"@org_tensorflow//tensorflow/cc/saved_model:loader_lite",
@@ -632,6 +635,7 @@ cc_library(
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"//mediapipe/framework/tool:status_util",
"@com_google_absl//absl/log:absl_log",
"@com_google_absl//absl/status",
"@com_google_absl//absl/strings",
"@org_tensorflow//tensorflow/cc/saved_model:constants",
@@ -653,6 +657,7 @@ cc_library(
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_log",
"@org_tensorflow//tensorflow/core:framework",
],
alwayslink = 1,
@@ -667,6 +672,7 @@ cc_library(
"//mediapipe/framework/formats:image_frame",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_check",
"@org_tensorflow//tensorflow/core:framework",
],
alwayslink = 1,
@@ -682,6 +688,7 @@ cc_library(
"//mediapipe/framework/formats:time_series_header_cc_proto",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_check",
] + select({
"//conditions:default": [
"@org_tensorflow//tensorflow/core:framework",
@@ -716,6 +723,7 @@ cc_library(
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"@org_tensorflow//tensorflow/core/platform:bfloat16",
] + select({
"//conditions:default": [
"@org_tensorflow//tensorflow/core:framework",
@@ -778,6 +786,7 @@ cc_library(
"//mediapipe/framework/port:status",
"//mediapipe/util:audio_decoder_cc_proto",
"//mediapipe/util/sequence:media_sequence",
"@com_google_absl//absl/log:absl_log",
"@com_google_absl//absl/strings",
"@org_tensorflow//tensorflow/core:protos_all_cc",
],
@@ -792,6 +801,8 @@ cc_library(
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/log:absl_log",
"@org_tensorflow//tensorflow/core:framework",
],
alwayslink = 1,
@@ -805,6 +816,7 @@ cc_library(
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_log",
"@org_tensorflow//tensorflow/core:framework",
],
alwayslink = 1,
@@ -818,6 +830,7 @@ cc_library(
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_log",
"@org_tensorflow//tensorflow/core:framework",
],
alwayslink = 1,
@@ -831,6 +844,8 @@ cc_library(
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework:packet",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/log:absl_log",
"@org_tensorflow//tensorflow/core:protos_all_cc",
],
alwayslink = 1,
@@ -925,21 +940,24 @@ cc_test(
srcs = ["pack_media_sequence_calculator_test.cc"],
deps = [
":pack_media_sequence_calculator",
":pack_media_sequence_calculator_cc_proto",
"//mediapipe/calculators/image:opencv_image_encoder_calculator_cc_proto",
"//mediapipe/calculators/tensorflow:pack_media_sequence_calculator_cc_proto",
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework:calculator_runner",
"//mediapipe/framework:packet",
"//mediapipe/framework:timestamp",
"//mediapipe/framework/formats:detection_cc_proto",
"//mediapipe/framework/formats:image_frame",
"//mediapipe/framework/formats:location",
"//mediapipe/framework/formats:location_opencv",
"//mediapipe/framework/port:gtest_main",
"//mediapipe/framework/port:opencv_imgcodecs",
"//mediapipe/util/sequence:media_sequence",
"@com_google_absl//absl/container:flat_hash_map",
"//mediapipe/util/sequence:media_sequence_util",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/memory",
"@com_google_absl//absl/status",
"@com_google_absl//absl/strings",
"@com_google_googletest//:gtest_main",
"@org_tensorflow//tensorflow/core:protos_all_cc",
],
)
@@ -1122,6 +1140,7 @@ cc_test(
"//mediapipe/util:packet_test_util",
"@org_tensorflow//tensorflow/core:framework",
"@org_tensorflow//tensorflow/core:protos_all_cc",
"@org_tensorflow//tensorflow/core/platform:bfloat16",
],
)
@@ -1167,6 +1186,7 @@ cc_test(
"//mediapipe/framework/port:rectangle",
"//mediapipe/util:audio_decoder_cc_proto",
"//mediapipe/util/sequence:media_sequence",
"@com_google_absl//absl/log:absl_log",
"@com_google_absl//absl/memory",
"@com_google_absl//absl/strings",
"@org_tensorflow//tensorflow/core:protos_all_cc",
@@ -1248,6 +1268,8 @@ cc_test(
"//mediapipe/framework/tool:sink",
"//mediapipe/framework/tool:validate_type",
"@com_google_absl//absl/flags:flag",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/log:absl_log",
] + select({
"//conditions:default": [
"@org_tensorflow//tensorflow/core:direct_session",
@@ -12,6 +12,7 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "absl/log/absl_check.h"
#include "mediapipe/calculators/tensorflow/matrix_to_tensor_calculator_options.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/formats/matrix.h"
@@ -28,7 +29,7 @@ namespace mediapipe {
namespace {
absl::Status FillTimeSeriesHeaderIfValid(const Packet& header_packet,
TimeSeriesHeader* header) {
CHECK(header);
ABSL_CHECK(header);
if (header_packet.IsEmpty()) {
return absl::UnknownError("No header found.");
}
@@ -12,21 +12,23 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include <cstdint>
#include <optional>
#include <string>
#include <vector>
#include "absl/container/flat_hash_map.h"
#include "absl/status/status.h"
#include "absl/strings/match.h"
#include "absl/strings/strip.h"
#include "mediapipe/calculators/image/opencv_image_encoder_calculator.pb.h"
#include "mediapipe/calculators/tensorflow/pack_media_sequence_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/formats/detection.pb.h"
#include "mediapipe/framework/formats/location.h"
#include "mediapipe/framework/formats/location_opencv.h"
#include "mediapipe/framework/port/canonical_errors.h"
#include "mediapipe/framework/port/opencv_imgcodecs_inc.h"
#include "mediapipe/framework/port/ret_check.h"
#include "mediapipe/framework/port/status.h"
#include "mediapipe/util/sequence/media_sequence.h"
#include "mediapipe/util/sequence/media_sequence_util.h"
#include "tensorflow/core/example/example.pb.h"
@@ -36,7 +38,11 @@ namespace mediapipe {
const char kSequenceExampleTag[] = "SEQUENCE_EXAMPLE";
const char kImageTag[] = "IMAGE";
const char kImageLabelPrefixTag[] = "IMAGE_LABEL_";
const char kClipLabelPrefixTag[] = "CLIP_LABEL_";
const char kFloatContextFeaturePrefixTag[] = "FLOAT_CONTEXT_FEATURE_";
const char kIntsContextFeaturePrefixTag[] = "INTS_CONTEXT_FEATURE_";
const char kBytesContextFeaturePrefixTag[] = "BYTES_CONTEXT_FEATURE_";
const char kFloatFeaturePrefixTag[] = "FLOAT_FEATURE_";
const char kIntFeaturePrefixTag[] = "INT_FEATURE_";
const char kBytesFeaturePrefixTag[] = "BYTES_FEATURE_";
@@ -44,6 +50,7 @@ const char kForwardFlowEncodedTag[] = "FORWARD_FLOW_ENCODED";
const char kBBoxTag[] = "BBOX";
const char kKeypointsTag[] = "KEYPOINTS";
const char kSegmentationMaskTag[] = "CLASS_SEGMENTATION";
const char kClipMediaIdTag[] = "CLIP_MEDIA_ID";
namespace tf = ::tensorflow;
namespace mpms = mediapipe::mediasequence;
@@ -55,16 +62,23 @@ namespace mpms = mediapipe::mediasequence;
// context features can be supplied verbatim in the calculator's options. The
// SequenceExample will conform to the description in media_sequence.h.
//
// The supported input stream tags are "IMAGE", which stores the encoded
// images from the OpenCVImageEncoderCalculator, "FORWARD_FLOW_ENCODED", which
// stores the encoded optical flow from the same calculator, "BBOX" which stores
// bounding boxes from vector<Detections>, and streams with the
// "FLOAT_FEATURE_${NAME}" pattern, which stores the values from vector<float>'s
// associated with the name ${NAME}. "KEYPOINTS" stores a map of 2D keypoints
// from flat_hash_map<string, vector<pair<float, float>>>. "IMAGE_${NAME}",
// "BBOX_${NAME}", and "KEYPOINTS_${NAME}" will also store prefixed versions of
// each stream, which allows for multiple image streams to be included. However,
// the default names are suppored by more tools.
// The supported input stream tags are:
// * "IMAGE", which stores the encoded images from the
// OpenCVImageEncoderCalculator,
// * "IMAGE_LABEL", which stores whole image labels from Detection,
// * "FORWARD_FLOW_ENCODED", which stores the encoded optical flow from the same
// calculator,
// * "BBOX" which stores bounding boxes from vector<Detections>,
// * streams with the "FLOAT_FEATURE_${NAME}" pattern, which stores the values
// from vector<float>'s associated with the name ${NAME},
// * "KEYPOINTS" stores a map of 2D keypoints from flat_hash_map<string,
// vector<pair<float, float>>>,
// * "CLIP_MEDIA_ID", which stores the clip's media ID as a string.
// * "CLIP_LABEL_${NAME}" which stores sparse feature labels, ID and scores in
// mediapipe::Detection.
// "IMAGE_${NAME}", "BBOX_${NAME}", and "KEYPOINTS_${NAME}" will also store
// prefixed versions of each stream, which allows for multiple image streams to
// be included. However, the default names are suppored by more tools.
//
// Example config:
// node {
@@ -100,6 +114,9 @@ class PackMediaSequenceCalculator : public CalculatorBase {
static absl::Status GetContract(CalculatorContract* cc) {
RET_CHECK(cc->InputSidePackets().HasTag(kSequenceExampleTag));
cc->InputSidePackets().Tag(kSequenceExampleTag).Set<tf::SequenceExample>();
if (cc->InputSidePackets().HasTag(kClipMediaIdTag)) {
cc->InputSidePackets().Tag(kClipMediaIdTag).Set<std::string>();
}
if (cc->Inputs().HasTag(kForwardFlowEncodedTag)) {
cc->Inputs()
@@ -112,6 +129,10 @@ class PackMediaSequenceCalculator : public CalculatorBase {
for (const auto& tag : cc->Inputs().GetTags()) {
if (absl::StartsWith(tag, kImageTag)) {
if (absl::StartsWith(tag, kImageLabelPrefixTag)) {
cc->Inputs().Tag(tag).Set<Detection>();
continue;
}
std::string key = "";
if (tag != kImageTag) {
int tag_length = sizeof(kImageTag) / sizeof(*kImageTag) - 1;
@@ -150,9 +171,18 @@ class PackMediaSequenceCalculator : public CalculatorBase {
}
cc->Inputs().Tag(tag).Set<std::vector<Detection>>();
}
if (absl::StartsWith(tag, kClipLabelPrefixTag)) {
cc->Inputs().Tag(tag).Set<Detection>();
}
if (absl::StartsWith(tag, kFloatContextFeaturePrefixTag)) {
cc->Inputs().Tag(tag).Set<std::vector<float>>();
}
if (absl::StartsWith(tag, kIntsContextFeaturePrefixTag)) {
cc->Inputs().Tag(tag).Set<std::vector<int64_t>>();
}
if (absl::StartsWith(tag, kBytesContextFeaturePrefixTag)) {
cc->Inputs().Tag(tag).Set<std::vector<std::string>>();
}
if (absl::StartsWith(tag, kFloatFeaturePrefixTag)) {
cc->Inputs().Tag(tag).Set<std::vector<float>>();
}
@@ -184,6 +214,11 @@ class PackMediaSequenceCalculator : public CalculatorBase {
cc->InputSidePackets()
.Tag(kSequenceExampleTag)
.Get<tf::SequenceExample>());
if (cc->InputSidePackets().HasTag(kClipMediaIdTag) &&
!cc->InputSidePackets().Tag(kClipMediaIdTag).IsEmpty()) {
clip_media_id_ =
cc->InputSidePackets().Tag(kClipMediaIdTag).Get<std::string>();
}
const auto& context_features =
cc->Options<PackMediaSequenceCalculatorOptions>().context_feature_map();
@@ -197,8 +232,19 @@ class PackMediaSequenceCalculator : public CalculatorBase {
replace_keypoints_ = false;
if (cc->Options<PackMediaSequenceCalculatorOptions>()
.replace_data_instead_of_append()) {
// Clear the existing values under the same key.
for (const auto& tag : cc->Inputs().GetTags()) {
if (absl::StartsWith(tag, kImageTag)) {
if (absl::StartsWith(tag, kImageLabelPrefixTag)) {
std::string key =
std::string(absl::StripPrefix(tag, kImageLabelPrefixTag));
mpms::ClearImageLabelString(key, sequence_.get());
mpms::ClearImageLabelConfidence(key, sequence_.get());
if (!key.empty() || mpms::HasImageEncoded(*sequence_)) {
mpms::ClearImageTimestamp(key, sequence_.get());
}
continue;
}
std::string key = "";
if (tag != kImageTag) {
int tag_length = sizeof(kImageTag) / sizeof(*kImageTag) - 1;
@@ -227,12 +273,41 @@ class PackMediaSequenceCalculator : public CalculatorBase {
mpms::ClearBBoxNumRegions(key, sequence_.get());
mpms::ClearBBoxLabelString(key, sequence_.get());
mpms::ClearBBoxLabelIndex(key, sequence_.get());
mpms::ClearBBoxLabelConfidence(key, sequence_.get());
mpms::ClearBBoxClassString(key, sequence_.get());
mpms::ClearBBoxClassIndex(key, sequence_.get());
mpms::ClearBBoxTrackString(key, sequence_.get());
mpms::ClearBBoxTrackIndex(key, sequence_.get());
mpms::ClearUnmodifiedBBoxTimestamp(key, sequence_.get());
}
if (absl::StartsWith(tag, kClipLabelPrefixTag)) {
const std::string& key = tag.substr(
sizeof(kClipLabelPrefixTag) / sizeof(*kClipLabelPrefixTag) - 1);
mpms::ClearClipLabelIndex(key, sequence_.get());
mpms::ClearClipLabelString(key, sequence_.get());
mpms::ClearClipLabelConfidence(key, sequence_.get());
}
if (absl::StartsWith(tag, kFloatContextFeaturePrefixTag)) {
const std::string& key =
tag.substr(sizeof(kFloatContextFeaturePrefixTag) /
sizeof(*kFloatContextFeaturePrefixTag) -
1);
mpms::ClearContextFeatureFloats(key, sequence_.get());
}
if (absl::StartsWith(tag, kIntsContextFeaturePrefixTag)) {
const std::string& key =
tag.substr(sizeof(kIntsContextFeaturePrefixTag) /
sizeof(*kIntsContextFeaturePrefixTag) -
1);
mpms::ClearContextFeatureInts(key, sequence_.get());
}
if (absl::StartsWith(tag, kBytesContextFeaturePrefixTag)) {
const std::string& key =
tag.substr(sizeof(kBytesContextFeaturePrefixTag) /
sizeof(*kBytesContextFeaturePrefixTag) -
1);
mpms::ClearContextFeatureBytes(key, sequence_.get());
}
if (absl::StartsWith(tag, kFloatFeaturePrefixTag)) {
std::string key = tag.substr(sizeof(kFloatFeaturePrefixTag) /
sizeof(*kFloatFeaturePrefixTag) -
@@ -343,6 +418,34 @@ class PackMediaSequenceCalculator : public CalculatorBase {
if (absl::StartsWith(tag, kImageTag) &&
!cc->Inputs().Tag(tag).IsEmpty()) {
std::string key = "";
if (absl::StartsWith(tag, kImageLabelPrefixTag)) {
std::string key =
std::string(absl::StripPrefix(tag, kImageLabelPrefixTag));
const auto& detection = cc->Inputs().Tag(tag).Get<Detection>();
if (detection.label().empty()) continue;
RET_CHECK(detection.label_size() == detection.score_size())
<< "Wrong image label data format: " << detection.label_size()
<< " vs " << detection.score_size();
if (!detection.label_id().empty()) {
RET_CHECK(detection.label_id_size() == detection.label_size())
<< "Wrong image label ID format: " << detection.label_id_size()
<< " vs " << detection.label_size();
}
std::vector<std::string> labels(detection.label().begin(),
detection.label().end());
std::vector<float> confidences(detection.score().begin(),
detection.score().end());
std::vector<int32_t> ids(detection.label_id().begin(),
detection.label_id().end());
if (!key.empty() || mpms::HasImageEncoded(*sequence_)) {
mpms::AddImageTimestamp(key, cc->InputTimestamp().Value(),
sequence_.get());
}
mpms::AddImageLabelString(key, labels, sequence_.get());
mpms::AddImageLabelConfidence(key, confidences, sequence_.get());
if (!ids.empty()) mpms::AddImageLabelIndex(key, ids, sequence_.get());
continue;
}
if (tag != kImageTag) {
int tag_length = sizeof(kImageTag) / sizeof(*kImageTag) - 1;
if (tag[tag_length] == '_') {
@@ -393,6 +496,7 @@ class PackMediaSequenceCalculator : public CalculatorBase {
mpms::ClearBBoxNumRegions(prefix, sequence_.get());
mpms::ClearBBoxLabelString(prefix, sequence_.get());
mpms::ClearBBoxLabelIndex(prefix, sequence_.get());
mpms::ClearBBoxLabelConfidence(prefix, sequence_.get());
mpms::ClearBBoxClassString(prefix, sequence_.get());
mpms::ClearBBoxClassIndex(prefix, sequence_.get());
mpms::ClearBBoxTrackString(prefix, sequence_.get());
@@ -405,6 +509,33 @@ class PackMediaSequenceCalculator : public CalculatorBase {
}
replace_keypoints_ = false;
}
if (absl::StartsWith(tag, kClipLabelPrefixTag) &&
!cc->Inputs().Tag(tag).IsEmpty()) {
const std::string& key = tag.substr(
sizeof(kClipLabelPrefixTag) / sizeof(*kClipLabelPrefixTag) - 1);
const Detection& detection = cc->Inputs().Tag(tag).Get<Detection>();
if (detection.label().size() != detection.score().size()) {
return absl::InvalidArgumentError(
"Different size of detection.label and detection.score");
}
// Allow empty label_ids, but if label_ids is not empty, it should have
// the same size as the label and score fields.
if (!detection.label_id().empty()) {
if (detection.label_id().size() != detection.label().size()) {
return absl::InvalidArgumentError(
"Different size of detection.label_id and detection.label");
}
}
for (int i = 0; i < detection.label().size(); ++i) {
if (!detection.label_id().empty()) {
mpms::AddClipLabelIndex(key, detection.label_id(i),
sequence_.get());
}
mpms::AddClipLabelString(key, detection.label(i), sequence_.get());
mpms::AddClipLabelConfidence(key, detection.score(i),
sequence_.get());
}
}
if (absl::StartsWith(tag, kFloatContextFeaturePrefixTag) &&
!cc->Inputs().Tag(tag).IsEmpty()) {
std::string key =
@@ -412,9 +543,36 @@ class PackMediaSequenceCalculator : public CalculatorBase {
sizeof(*kFloatContextFeaturePrefixTag) -
1);
RET_CHECK_EQ(cc->InputTimestamp(), Timestamp::PostStream());
mpms::SetContextFeatureFloats(
key, cc->Inputs().Tag(tag).Get<std::vector<float>>(),
sequence_.get());
for (const auto& value :
cc->Inputs().Tag(tag).Get<std::vector<float>>()) {
mpms::AddContextFeatureFloats(key, value, sequence_.get());
}
}
if (absl::StartsWith(tag, kIntsContextFeaturePrefixTag) &&
!cc->Inputs().Tag(tag).IsEmpty()) {
const std::string& key =
tag.substr(sizeof(kIntsContextFeaturePrefixTag) /
sizeof(*kIntsContextFeaturePrefixTag) -
1);
// To ensure only one packet is provided for this tag.
RET_CHECK_EQ(cc->InputTimestamp(), Timestamp::PostStream());
for (const auto& value :
cc->Inputs().Tag(tag).Get<std::vector<int64_t>>()) {
mpms::AddContextFeatureInts(key, value, sequence_.get());
}
}
if (absl::StartsWith(tag, kBytesContextFeaturePrefixTag) &&
!cc->Inputs().Tag(tag).IsEmpty()) {
const std::string& key =
tag.substr(sizeof(kBytesContextFeaturePrefixTag) /
sizeof(*kBytesContextFeaturePrefixTag) -
1);
// To ensure only one packet is provided for this tag.
RET_CHECK_EQ(cc->InputTimestamp(), Timestamp::PostStream());
for (const auto& value :
cc->Inputs().Tag(tag).Get<std::vector<std::string>>()) {
mpms::AddContextFeatureBytes(key, value, sequence_.get());
}
}
if (absl::StartsWith(tag, kFloatFeaturePrefixTag) &&
!cc->Inputs().Tag(tag).IsEmpty()) {
@@ -460,6 +618,7 @@ class PackMediaSequenceCalculator : public CalculatorBase {
}
std::vector<Location> predicted_locations;
std::vector<std::string> predicted_class_strings;
std::vector<float> predicted_class_confidences;
std::vector<int> predicted_label_ids;
for (auto& detection :
cc->Inputs().Tag(tag).Get<std::vector<Detection>>()) {
@@ -488,6 +647,9 @@ class PackMediaSequenceCalculator : public CalculatorBase {
if (detection.label_id_size() > 0) {
predicted_label_ids.push_back(detection.label_id(0));
}
if (detection.score_size() > 0) {
predicted_class_confidences.push_back(detection.score(0));
}
}
}
if (!predicted_locations.empty()) {
@@ -501,6 +663,10 @@ class PackMediaSequenceCalculator : public CalculatorBase {
if (!predicted_label_ids.empty()) {
mpms::AddBBoxLabelIndex(key, predicted_label_ids, sequence_.get());
}
if (!predicted_class_confidences.empty()) {
mpms::AddBBoxLabelConfidence(key, predicted_class_confidences,
sequence_.get());
}
}
}
}
@@ -548,10 +714,14 @@ class PackMediaSequenceCalculator : public CalculatorBase {
}
}
}
if (clip_media_id_.has_value()) {
mpms::SetClipMediaId(*clip_media_id_, sequence_.get());
}
return absl::OkStatus();
}
std::unique_ptr<tf::SequenceExample> sequence_;
std::optional<std::string> clip_media_id_ = std::nullopt;
std::map<std::string, bool> features_present_;
bool replace_keypoints_;
};
@@ -12,27 +12,32 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include <algorithm>
#include <cstdint>
#include <memory>
#include <string>
#include <vector>
#include "absl/container/flat_hash_map.h"
#include "absl/log/absl_check.h"
#include "absl/memory/memory.h"
#include "absl/strings/numbers.h"
#include "absl/status/status.h"
#include "absl/strings/str_cat.h"
#include "mediapipe/calculators/image/opencv_image_encoder_calculator.pb.h"
#include "mediapipe/calculators/tensorflow/pack_media_sequence_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/calculator_runner.h"
#include "mediapipe/framework/formats/detection.pb.h"
#include "mediapipe/framework/formats/image_frame.h"
#include "mediapipe/framework/formats/location.h"
#include "mediapipe/framework/formats/location_opencv.h"
#include "mediapipe/framework/port/gmock.h"
#include "mediapipe/framework/port/gtest.h"
#include "mediapipe/framework/packet.h"
#include "mediapipe/framework/port/opencv_imgcodecs_inc.h"
#include "mediapipe/framework/port/status_matchers.h"
#include "mediapipe/framework/timestamp.h"
#include "mediapipe/util/sequence/media_sequence.h"
#include "mediapipe/util/sequence/media_sequence_util.h"
#include "tensorflow/core/example/example.pb.h"
#include "tensorflow/core/example/feature.pb.h"
#include "testing/base/public/gmock.h"
#include "testing/base/public/gunit.h"
namespace mediapipe {
namespace {
@@ -54,13 +59,22 @@ constexpr char kBytesFeatureTestTag[] = "BYTES_FEATURE_TEST";
constexpr char kForwardFlowEncodedTag[] = "FORWARD_FLOW_ENCODED";
constexpr char kFloatContextFeatureOtherTag[] = "FLOAT_CONTEXT_FEATURE_OTHER";
constexpr char kFloatContextFeatureTestTag[] = "FLOAT_CONTEXT_FEATURE_TEST";
constexpr char kIntsContextFeatureTestTag[] = "INTS_CONTEXT_FEATURE_TEST";
constexpr char kIntsContextFeatureOtherTag[] = "INTS_CONTEXT_FEATURE_OTHER";
constexpr char kBytesContextFeatureTestTag[] = "BYTES_CONTEXT_FEATURE_TEST";
constexpr char kBytesContextFeatureOtherTag[] = "BYTES_CONTEXT_FEATURE_OTHER";
constexpr char kFloatFeatureOtherTag[] = "FLOAT_FEATURE_OTHER";
constexpr char kFloatFeatureTestTag[] = "FLOAT_FEATURE_TEST";
constexpr char kIntFeatureOtherTag[] = "INT_FEATURE_OTHER";
constexpr char kIntFeatureTestTag[] = "INT_FEATURE_TEST";
constexpr char kImageLabelTestTag[] = "IMAGE_LABEL_TEST";
constexpr char kImageLabelOtherTag[] = "IMAGE_LABEL_OTHER";
constexpr char kImagePrefixTag[] = "IMAGE_PREFIX";
constexpr char kSequenceExampleTag[] = "SEQUENCE_EXAMPLE";
constexpr char kImageTag[] = "IMAGE";
constexpr char kClipMediaIdTag[] = "CLIP_MEDIA_ID";
constexpr char kClipLabelTestTag[] = "CLIP_LABEL_TEST";
constexpr char kClipLabelOtherTag[] = "CLIP_LABEL_OTHER";
class PackMediaSequenceCalculatorTest : public ::testing::Test {
protected:
@@ -68,10 +82,14 @@ class PackMediaSequenceCalculatorTest : public ::testing::Test {
const tf::Features& features,
const bool output_only_if_all_present,
const bool replace_instead_of_append,
const bool output_as_zero_timestamp = false) {
const bool output_as_zero_timestamp = false,
const std::vector<std::string>& input_side_packets = {
"SEQUENCE_EXAMPLE:input_sequence"}) {
CalculatorGraphConfig::Node config;
config.set_calculator("PackMediaSequenceCalculator");
config.add_input_side_packet("SEQUENCE_EXAMPLE:input_sequence");
for (const std::string& side_packet : input_side_packets) {
config.add_input_side_packet(side_packet);
}
config.add_output_stream("SEQUENCE_EXAMPLE:output_sequence");
for (const std::string& stream : input_streams) {
config.add_input_stream(stream);
@@ -313,6 +331,76 @@ TEST_F(PackMediaSequenceCalculatorTest, PacksTwoBytesLists) {
}
}
TEST_F(PackMediaSequenceCalculatorTest, PacksTwoImageLabels) {
SetUpCalculator(
{"IMAGE_LABEL_TEST:test_labels", "IMAGE_LABEL_OTHER:test_labels2"}, {},
false, true);
auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
int num_timesteps = 2;
for (int i = 0; i < num_timesteps; ++i) {
Detection detection1;
detection1.add_label(absl::StrCat("foo", 2 << i));
detection1.add_label_id(i);
detection1.add_score(0.1 * i);
detection1.add_label(absl::StrCat("foo", 2 << i));
detection1.add_label_id(i);
detection1.add_score(0.1 * i);
auto label_ptr1 = ::absl::make_unique<Detection>(detection1);
runner_->MutableInputs()
->Tag(kImageLabelTestTag)
.packets.push_back(Adopt(label_ptr1.release()).At(Timestamp(i)));
Detection detection2;
detection2.add_label(absl::StrCat("bar", 2 << i));
detection2.add_score(0.2 * i);
detection2.add_label(absl::StrCat("bar", 2 << i));
detection2.add_score(0.2 * i);
auto label_ptr2 = ::absl::make_unique<Detection>(detection2);
runner_->MutableInputs()
->Tag(kImageLabelOtherTag)
.packets.push_back(Adopt(label_ptr2.release()).At(Timestamp(i)));
}
runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
Adopt(input_sequence.release());
MP_ASSERT_OK(runner_->Run());
const std::vector<Packet>& output_packets =
runner_->Outputs().Tag(kSequenceExampleTag).packets;
ASSERT_EQ(1, output_packets.size());
const tf::SequenceExample& output_sequence =
output_packets[0].Get<tf::SequenceExample>();
ASSERT_EQ(num_timesteps,
mpms::GetImageTimestampSize("TEST", output_sequence));
ASSERT_EQ(num_timesteps,
mpms::GetImageLabelStringSize("TEST", output_sequence));
ASSERT_EQ(num_timesteps,
mpms::GetImageLabelConfidenceSize("TEST", output_sequence));
ASSERT_EQ(num_timesteps,
mpms::GetImageTimestampSize("OTHER", output_sequence));
ASSERT_EQ(num_timesteps,
mpms::GetImageLabelStringSize("OTHER", output_sequence));
ASSERT_EQ(num_timesteps,
mpms::GetImageLabelConfidenceSize("OTHER", output_sequence));
for (int i = 0; i < num_timesteps; ++i) {
ASSERT_EQ(i, mpms::GetImageTimestampAt("TEST", output_sequence, i));
ASSERT_THAT(mpms::GetImageLabelStringAt("TEST", output_sequence, i),
::testing::ElementsAreArray(
std::vector<std::string>(2, absl::StrCat("foo", 2 << i))));
ASSERT_THAT(mpms::GetImageLabelIndexAt("TEST", output_sequence, i),
::testing::ElementsAreArray(std::vector<int32_t>(2, i)));
ASSERT_THAT(mpms::GetImageLabelConfidenceAt("TEST", output_sequence, i),
::testing::ElementsAreArray(std::vector<float>(2, 0.1 * i)));
ASSERT_EQ(i, mpms::GetImageTimestampAt("OTHER", output_sequence, i));
ASSERT_THAT(mpms::GetImageLabelStringAt("OTHER", output_sequence, i),
::testing::ElementsAreArray(
std::vector<std::string>(2, absl::StrCat("bar", 2 << i))));
ASSERT_THAT(mpms::GetImageLabelConfidenceAt("OTHER", output_sequence, i),
::testing::ElementsAreArray(std::vector<float>(2, 0.2 * i)));
}
}
TEST_F(PackMediaSequenceCalculatorTest, OutputAsZeroTimestamp) {
SetUpCalculator({"FLOAT_FEATURE_TEST:test"}, {}, false, true, true);
auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
@@ -368,6 +456,315 @@ TEST_F(PackMediaSequenceCalculatorTest, PacksTwoContextFloatLists) {
testing::ElementsAre(4, 4));
}
TEST_F(PackMediaSequenceCalculatorTest, ReplaceTwoContextFloatLists) {
SetUpCalculator(
/*input_streams=*/{"FLOAT_CONTEXT_FEATURE_TEST:test",
"FLOAT_CONTEXT_FEATURE_OTHER:test2"},
/*features=*/{},
/*output_only_if_all_present=*/false, /*replace_instead_of_append=*/true);
auto input_sequence = std::make_unique<tf::SequenceExample>();
mpms::SetContextFeatureFloats("TEST", {2, 3}, input_sequence.get());
mpms::SetContextFeatureFloats("OTHER", {2, 4}, input_sequence.get());
const std::vector<float> vf_1 = {5, 6};
runner_->MutableInputs()
->Tag(kFloatContextFeatureTestTag)
.packets.push_back(
MakePacket<std::vector<float>>(vf_1).At(Timestamp::PostStream()));
const std::vector<float> vf_2 = {7, 8};
runner_->MutableInputs()
->Tag(kFloatContextFeatureOtherTag)
.packets.push_back(
MakePacket<std::vector<float>>(vf_2).At(Timestamp::PostStream()));
runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
Adopt(input_sequence.release());
MP_ASSERT_OK(runner_->Run());
const std::vector<Packet>& output_packets =
runner_->Outputs().Tag(kSequenceExampleTag).packets;
ASSERT_EQ(1, output_packets.size());
const tf::SequenceExample& output_sequence =
output_packets[0].Get<tf::SequenceExample>();
ASSERT_THAT(mpms::GetContextFeatureFloats("TEST", output_sequence),
testing::ElementsAre(5, 6));
ASSERT_THAT(mpms::GetContextFeatureFloats("OTHER", output_sequence),
testing::ElementsAre(7, 8));
}
TEST_F(PackMediaSequenceCalculatorTest, AppendTwoContextFloatLists) {
SetUpCalculator(
/*input_streams=*/{"FLOAT_CONTEXT_FEATURE_TEST:test",
"FLOAT_CONTEXT_FEATURE_OTHER:test2"},
/*features=*/{},
/*output_only_if_all_present=*/false,
/*replace_instead_of_append=*/false);
auto input_sequence = std::make_unique<tf::SequenceExample>();
mpms::SetContextFeatureFloats("TEST", {2, 3}, input_sequence.get());
mpms::SetContextFeatureFloats("OTHER", {2, 4}, input_sequence.get());
const std::vector<float> vf_1 = {5, 6};
runner_->MutableInputs()
->Tag(kFloatContextFeatureTestTag)
.packets.push_back(
MakePacket<std::vector<float>>(vf_1).At(Timestamp::PostStream()));
const std::vector<float> vf_2 = {7, 8};
runner_->MutableInputs()
->Tag(kFloatContextFeatureOtherTag)
.packets.push_back(
MakePacket<std::vector<float>>(vf_2).At(Timestamp::PostStream()));
runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
Adopt(input_sequence.release());
MP_ASSERT_OK(runner_->Run());
const std::vector<Packet>& output_packets =
runner_->Outputs().Tag(kSequenceExampleTag).packets;
ASSERT_EQ(1, output_packets.size());
const tf::SequenceExample& output_sequence =
output_packets[0].Get<tf::SequenceExample>();
EXPECT_THAT(mpms::GetContextFeatureFloats("TEST", output_sequence),
testing::ElementsAre(2, 3, 5, 6));
EXPECT_THAT(mpms::GetContextFeatureFloats("OTHER", output_sequence),
testing::ElementsAre(2, 4, 7, 8));
}
TEST_F(PackMediaSequenceCalculatorTest, PackTwoContextIntLists) {
SetUpCalculator(
/*input_streams=*/{"INTS_CONTEXT_FEATURE_TEST:test",
"INTS_CONTEXT_FEATURE_OTHER:test2"},
/*features=*/{},
/*output_only_if_all_present=*/false, /*replace_instead_of_append=*/true);
auto input_sequence = absl::make_unique<tf::SequenceExample>();
const std::vector<int64_t> vi_1 = {2, 3};
runner_->MutableInputs()
->Tag(kIntsContextFeatureTestTag)
.packets.push_back(
MakePacket<std::vector<int64_t>>(vi_1).At(Timestamp::PostStream()));
const std::vector<int64_t> vi_2 = {2, 4};
runner_->MutableInputs()
->Tag(kIntsContextFeatureOtherTag)
.packets.push_back(
MakePacket<std::vector<int64_t>>(vi_2).At(Timestamp::PostStream()));
runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
Adopt(input_sequence.release());
MP_ASSERT_OK(runner_->Run());
const std::vector<Packet>& output_packets =
runner_->Outputs().Tag(kSequenceExampleTag).packets;
ASSERT_EQ(1, output_packets.size());
const tf::SequenceExample& output_sequence =
output_packets[0].Get<tf::SequenceExample>();
ASSERT_THAT(mpms::GetContextFeatureInts("TEST", output_sequence),
testing::ElementsAre(2, 3));
ASSERT_THAT(mpms::GetContextFeatureInts("OTHER", output_sequence),
testing::ElementsAre(2, 4));
}
TEST_F(PackMediaSequenceCalculatorTest, ReplaceTwoContextIntLists) {
SetUpCalculator(
/*input_streams=*/{"INTS_CONTEXT_FEATURE_TEST:test",
"INTS_CONTEXT_FEATURE_OTHER:test2"},
/*features=*/{},
/*output_only_if_all_present=*/false, /*replace_instead_of_append=*/true);
auto input_sequence = absl::make_unique<tf::SequenceExample>();
mpms::SetContextFeatureInts("TEST", {2, 3}, input_sequence.get());
mpms::SetContextFeatureInts("OTHER", {2, 4}, input_sequence.get());
const std::vector<int64_t> vi_1 = {5, 6};
runner_->MutableInputs()
->Tag(kIntsContextFeatureTestTag)
.packets.push_back(
MakePacket<std::vector<int64_t>>(vi_1).At(Timestamp::PostStream()));
const std::vector<int64_t> vi_2 = {7, 8};
runner_->MutableInputs()
->Tag(kIntsContextFeatureOtherTag)
.packets.push_back(
MakePacket<std::vector<int64_t>>(vi_2).At(Timestamp::PostStream()));
runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
Adopt(input_sequence.release());
MP_ASSERT_OK(runner_->Run());
const std::vector<Packet>& output_packets =
runner_->Outputs().Tag(kSequenceExampleTag).packets;
ASSERT_EQ(1, output_packets.size());
const tf::SequenceExample& output_sequence =
output_packets[0].Get<tf::SequenceExample>();
ASSERT_THAT(mpms::GetContextFeatureInts("TEST", output_sequence),
testing::ElementsAre(5, 6));
ASSERT_THAT(mpms::GetContextFeatureInts("OTHER", output_sequence),
testing::ElementsAre(7, 8));
}
TEST_F(PackMediaSequenceCalculatorTest, AppendTwoContextIntLists) {
SetUpCalculator(
/*input_streams=*/{"INTS_CONTEXT_FEATURE_TEST:test",
"INTS_CONTEXT_FEATURE_OTHER:test2"},
/*features=*/{},
/*output_only_if_all_present=*/false,
/*replace_instead_of_append=*/false);
auto input_sequence = absl::make_unique<tf::SequenceExample>();
mpms::SetContextFeatureInts("TEST", {2, 3}, input_sequence.get());
mpms::SetContextFeatureInts("OTHER", {2, 4}, input_sequence.get());
const std::vector<int64_t> vi_1 = {5, 6};
runner_->MutableInputs()
->Tag(kIntsContextFeatureTestTag)
.packets.push_back(
MakePacket<std::vector<int64_t>>(vi_1).At(Timestamp::PostStream()));
const std::vector<int64_t> vi_2 = {7, 8};
runner_->MutableInputs()
->Tag(kIntsContextFeatureOtherTag)
.packets.push_back(
MakePacket<std::vector<int64_t>>(vi_2).At(Timestamp::PostStream()));
runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
Adopt(input_sequence.release());
MP_ASSERT_OK(runner_->Run());
const std::vector<Packet>& output_packets =
runner_->Outputs().Tag(kSequenceExampleTag).packets;
ASSERT_EQ(1, output_packets.size());
const tf::SequenceExample& output_sequence =
output_packets[0].Get<tf::SequenceExample>();
ASSERT_THAT(mpms::GetContextFeatureInts("TEST", output_sequence),
testing::ElementsAre(2, 3, 5, 6));
ASSERT_THAT(mpms::GetContextFeatureInts("OTHER", output_sequence),
testing::ElementsAre(2, 4, 7, 8));
}
TEST_F(PackMediaSequenceCalculatorTest, PackTwoContextByteLists) {
SetUpCalculator(
/*input_streams=*/{"BYTES_CONTEXT_FEATURE_TEST:test",
"BYTES_CONTEXT_FEATURE_OTHER:test2"},
/*features=*/{},
/*output_only_if_all_present=*/false, /*replace_instead_of_append=*/true);
auto input_sequence = absl::make_unique<tf::SequenceExample>();
const std::vector<std::string> vb_1 = {"value_1", "value_2"};
runner_->MutableInputs()
->Tag(kBytesContextFeatureTestTag)
.packets.push_back(MakePacket<std::vector<std::string>>(vb_1).At(
Timestamp::PostStream()));
const std::vector<std::string> vb_2 = {"value_3", "value_4"};
runner_->MutableInputs()
->Tag(kBytesContextFeatureOtherTag)
.packets.push_back(MakePacket<std::vector<std::string>>(vb_2).At(
Timestamp::PostStream()));
runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
Adopt(input_sequence.release());
MP_ASSERT_OK(runner_->Run());
const std::vector<Packet>& output_packets =
runner_->Outputs().Tag(kSequenceExampleTag).packets;
ASSERT_EQ(1, output_packets.size());
const tf::SequenceExample& output_sequence =
output_packets[0].Get<tf::SequenceExample>();
ASSERT_THAT(mpms::GetContextFeatureBytes("TEST", output_sequence),
testing::ElementsAre("value_1", "value_2"));
ASSERT_THAT(mpms::GetContextFeatureBytes("OTHER", output_sequence),
testing::ElementsAre("value_3", "value_4"));
}
TEST_F(PackMediaSequenceCalculatorTest, ReplaceTwoContextByteLists) {
SetUpCalculator(
/*input_streams=*/{"BYTES_CONTEXT_FEATURE_TEST:test",
"BYTES_CONTEXT_FEATURE_OTHER:test2"},
/*features=*/{},
/*output_only_if_all_present=*/false, /*replace_instead_of_append=*/true);
auto input_sequence = absl::make_unique<tf::SequenceExample>();
mpms::SetContextFeatureBytes("TEST", {"existing_value_1", "existing_value_2"},
input_sequence.get());
mpms::SetContextFeatureBytes(
"OTHER", {"existing_value_3", "existing_value_4"}, input_sequence.get());
const std::vector<std::string> vb_1 = {"value_1", "value_2"};
runner_->MutableInputs()
->Tag(kBytesContextFeatureTestTag)
.packets.push_back(MakePacket<std::vector<std::string>>(vb_1).At(
Timestamp::PostStream()));
const std::vector<std::string> vb_2 = {"value_3", "value_4"};
runner_->MutableInputs()
->Tag(kBytesContextFeatureOtherTag)
.packets.push_back(MakePacket<std::vector<std::string>>(vb_2).At(
Timestamp::PostStream()));
runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
Adopt(input_sequence.release());
MP_ASSERT_OK(runner_->Run());
const std::vector<Packet>& output_packets =
runner_->Outputs().Tag(kSequenceExampleTag).packets;
ASSERT_EQ(1, output_packets.size());
const tf::SequenceExample& output_sequence =
output_packets[0].Get<tf::SequenceExample>();
ASSERT_THAT(mpms::GetContextFeatureBytes("TEST", output_sequence),
testing::ElementsAre("value_1", "value_2"));
ASSERT_THAT(mpms::GetContextFeatureBytes("OTHER", output_sequence),
testing::ElementsAre("value_3", "value_4"));
}
TEST_F(PackMediaSequenceCalculatorTest, AppendTwoContextByteLists) {
SetUpCalculator(
/*input_streams=*/{"BYTES_CONTEXT_FEATURE_TEST:test",
"BYTES_CONTEXT_FEATURE_OTHER:test2"},
/*features=*/{},
/*output_only_if_all_present=*/false,
/*replace_instead_of_append=*/false);
auto input_sequence = absl::make_unique<tf::SequenceExample>();
mpms::SetContextFeatureBytes("TEST", {"existing_value_1", "existing_value_2"},
input_sequence.get());
mpms::SetContextFeatureBytes(
"OTHER", {"existing_value_3", "existing_value_4"}, input_sequence.get());
const std::vector<std::string> vb_1 = {"value_1", "value_2"};
runner_->MutableInputs()
->Tag(kBytesContextFeatureTestTag)
.packets.push_back(MakePacket<std::vector<std::string>>(vb_1).At(
Timestamp::PostStream()));
const std::vector<std::string> vb_2 = {"value_3", "value_4"};
runner_->MutableInputs()
->Tag(kBytesContextFeatureOtherTag)
.packets.push_back(MakePacket<std::vector<std::string>>(vb_2).At(
Timestamp::PostStream()));
runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
Adopt(input_sequence.release());
MP_ASSERT_OK(runner_->Run());
const std::vector<Packet>& output_packets =
runner_->Outputs().Tag(kSequenceExampleTag).packets;
ASSERT_EQ(1, output_packets.size());
const tf::SequenceExample& output_sequence =
output_packets[0].Get<tf::SequenceExample>();
ASSERT_THAT(mpms::GetContextFeatureBytes("TEST", output_sequence),
testing::ElementsAre("existing_value_1", "existing_value_2",
"value_1", "value_2"));
ASSERT_THAT(mpms::GetContextFeatureBytes("OTHER", output_sequence),
testing::ElementsAre("existing_value_3", "existing_value_4",
"value_3", "value_4"));
}
TEST_F(PackMediaSequenceCalculatorTest, PacksAdditionalContext) {
tf::Features context;
(*context.mutable_feature())["TEST"].mutable_bytes_list()->add_value("YES");
@@ -529,6 +926,10 @@ TEST_F(PackMediaSequenceCalculatorTest, PacksTwoBBoxDetections) {
auto class_indices = mpms::GetPredictedBBoxLabelIndexAt(output_sequence, i);
ASSERT_EQ(0, class_indices[0]);
ASSERT_EQ(1, class_indices[1]);
auto class_scores =
mpms::GetPredictedBBoxLabelConfidenceAt(output_sequence, i);
ASSERT_FLOAT_EQ(0.5, class_scores[0]);
ASSERT_FLOAT_EQ(0.75, class_scores[1]);
}
}
@@ -671,6 +1072,10 @@ TEST_F(PackMediaSequenceCalculatorTest, PacksBBoxWithImages) {
auto class_indices = mpms::GetPredictedBBoxLabelIndexAt(output_sequence, i);
ASSERT_EQ(0, class_indices[0]);
ASSERT_EQ(1, class_indices[1]);
auto class_scores =
mpms::GetPredictedBBoxLabelConfidenceAt(output_sequence, i);
ASSERT_FLOAT_EQ(0.5, class_scores[0]);
ASSERT_FLOAT_EQ(0.75, class_scores[1]);
}
}
@@ -761,6 +1166,365 @@ TEST_F(PackMediaSequenceCalculatorTest, PacksTwoMaskDetections) {
testing::ElementsAreArray(::std::vector<std::string>({"mask"})));
}
TEST_F(PackMediaSequenceCalculatorTest, PackTwoClipLabels) {
SetUpCalculator(
/*input_streams=*/{"CLIP_LABEL_TEST:test", "CLIP_LABEL_OTHER:test2"},
/*features=*/{}, /*output_only_if_all_present=*/false,
/*replace_instead_of_append=*/true);
auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
Detection detection_1;
detection_1.add_label("label_1");
detection_1.add_label("label_2");
detection_1.add_label_id(1);
detection_1.add_label_id(2);
detection_1.add_score(0.1);
detection_1.add_score(0.2);
runner_->MutableInputs()
->Tag(kClipLabelTestTag)
.packets.push_back(MakePacket<Detection>(detection_1).At(Timestamp(1)));
// No label ID for detection_2.
Detection detection_2;
detection_2.add_label("label_3");
detection_2.add_label("label_4");
detection_2.add_score(0.3);
detection_2.add_score(0.4);
runner_->MutableInputs()
->Tag(kClipLabelOtherTag)
.packets.push_back(MakePacket<Detection>(detection_2).At(Timestamp(2)));
runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
Adopt(input_sequence.release());
MP_ASSERT_OK(runner_->Run());
const std::vector<Packet>& output_packets =
runner_->Outputs().Tag(kSequenceExampleTag).packets;
ASSERT_EQ(1, output_packets.size());
const tf::SequenceExample& output_sequence =
output_packets[0].Get<tf::SequenceExample>();
ASSERT_THAT(mpms::GetClipLabelString("TEST", output_sequence),
testing::ElementsAre("label_1", "label_2"));
ASSERT_THAT(mpms::GetClipLabelIndex("TEST", output_sequence),
testing::ElementsAre(1, 2));
ASSERT_THAT(mpms::GetClipLabelConfidence("TEST", output_sequence),
testing::ElementsAre(0.1, 0.2));
ASSERT_THAT(mpms::GetClipLabelString("OTHER", output_sequence),
testing::ElementsAre("label_3", "label_4"));
ASSERT_FALSE(mpms::HasClipLabelIndex("OTHER", output_sequence));
ASSERT_THAT(mpms::GetClipLabelConfidence("OTHER", output_sequence),
testing::ElementsAre(0.3, 0.4));
}
TEST_F(PackMediaSequenceCalculatorTest,
PackTwoClipLabels_DifferentLabelScoreSize) {
SetUpCalculator(
/*input_streams=*/{"CLIP_LABEL_TEST:test", "CLIP_LABEL_OTHER:test2"},
/*features=*/{}, /*output_only_if_all_present=*/false,
/*replace_instead_of_append=*/true);
auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
// 2 labels and 1 score in detection_1.
Detection detection_1;
detection_1.add_label("label_1");
detection_1.add_label("label_2");
detection_1.add_score(0.1);
runner_->MutableInputs()
->Tag(kClipLabelTestTag)
.packets.push_back(MakePacket<Detection>(detection_1).At(Timestamp(1)));
Detection detection_2;
detection_2.add_label("label_3");
detection_2.add_label("label_4");
detection_2.add_score(0.3);
detection_2.add_score(0.4);
runner_->MutableInputs()
->Tag(kClipLabelOtherTag)
.packets.push_back(MakePacket<Detection>(detection_2).At(Timestamp(2)));
runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
Adopt(input_sequence.release());
ASSERT_THAT(
runner_->Run(),
testing::status::StatusIs(
absl::StatusCode::kInvalidArgument,
testing::HasSubstr(
"Different size of detection.label and detection.score")));
}
TEST_F(PackMediaSequenceCalculatorTest,
PackTwoClipLabels_DifferentLabelIdSize) {
SetUpCalculator(
/*input_streams=*/{"CLIP_LABEL_TEST:test", "CLIP_LABEL_OTHER:test2"},
/*features=*/{}, /*output_only_if_all_present=*/false,
/*replace_instead_of_append=*/true);
auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
// 2 labels and 1 label_id in detection_1.
Detection detection_1;
detection_1.add_label("label_1");
detection_1.add_label("label_2");
detection_1.add_label_id(1);
detection_1.add_score(0.1);
detection_1.add_score(0.2);
runner_->MutableInputs()
->Tag(kClipLabelTestTag)
.packets.push_back(MakePacket<Detection>(detection_1).At(Timestamp(1)));
Detection detection_2;
detection_2.add_label("label_3");
detection_2.add_label("label_4");
detection_2.add_score(0.3);
detection_2.add_score(0.4);
runner_->MutableInputs()
->Tag(kClipLabelOtherTag)
.packets.push_back(MakePacket<Detection>(detection_2).At(Timestamp(2)));
runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
Adopt(input_sequence.release());
ASSERT_THAT(
runner_->Run(),
testing::status::StatusIs(
absl::StatusCode::kInvalidArgument,
testing::HasSubstr(
"Different size of detection.label_id and detection.label")));
}
TEST_F(PackMediaSequenceCalculatorTest, ReplaceTwoClipLabels) {
// Replace existing clip/label/string and clip/label/confidence values for
// the prefixes.
SetUpCalculator(
/*input_streams=*/{"CLIP_LABEL_TEST:test", "CLIP_LABEL_OTHER:test2"},
/*features=*/{}, /*output_only_if_all_present=*/false,
/*replace_instead_of_append=*/true);
auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
mpms::SetClipLabelString("TEST", {"old_label_1", "old_label_2"},
input_sequence.get());
mpms::SetClipLabelConfidence("TEST", {0.1, 0.2}, input_sequence.get());
mpms::SetClipLabelString("OTHER", {"old_label_3", "old_label_4"},
input_sequence.get());
mpms::SetClipLabelConfidence("OTHER", {0.3, 0.4}, input_sequence.get());
Detection detection_1;
detection_1.add_label("label_1");
detection_1.add_label("label_2");
detection_1.add_label_id(1);
detection_1.add_label_id(2);
detection_1.add_score(0.9);
detection_1.add_score(0.8);
runner_->MutableInputs()
->Tag(kClipLabelTestTag)
.packets.push_back(MakePacket<Detection>(detection_1).At(Timestamp(1)));
Detection detection_2;
detection_2.add_label("label_3");
detection_2.add_label("label_4");
detection_2.add_label_id(3);
detection_2.add_label_id(4);
detection_2.add_score(0.7);
detection_2.add_score(0.6);
runner_->MutableInputs()
->Tag(kClipLabelOtherTag)
.packets.push_back(MakePacket<Detection>(detection_2).At(Timestamp(2)));
runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
Adopt(input_sequence.release());
MP_ASSERT_OK(runner_->Run());
const std::vector<Packet>& output_packets =
runner_->Outputs().Tag(kSequenceExampleTag).packets;
ASSERT_EQ(1, output_packets.size());
const tf::SequenceExample& output_sequence =
output_packets[0].Get<tf::SequenceExample>();
ASSERT_THAT(mpms::GetClipLabelString("TEST", output_sequence),
testing::ElementsAre("label_1", "label_2"));
ASSERT_THAT(mpms::GetClipLabelIndex("TEST", output_sequence),
testing::ElementsAre(1, 2));
ASSERT_THAT(mpms::GetClipLabelConfidence("TEST", output_sequence),
testing::ElementsAre(0.9, 0.8));
ASSERT_THAT(mpms::GetClipLabelString("OTHER", output_sequence),
testing::ElementsAre("label_3", "label_4"));
ASSERT_THAT(mpms::GetClipLabelIndex("OTHER", output_sequence),
testing::ElementsAre(3, 4));
ASSERT_THAT(mpms::GetClipLabelConfidence("OTHER", output_sequence),
testing::ElementsAre(0.7, 0.6));
}
TEST_F(PackMediaSequenceCalculatorTest, AppendTwoClipLabels) {
// Append to the existing clip/label/string and clip/label/confidence values
// for the prefixes.
SetUpCalculator(
/*input_streams=*/{"CLIP_LABEL_TEST:test", "CLIP_LABEL_OTHER:test2"},
/*features=*/{}, /*output_only_if_all_present=*/false,
/*replace_instead_of_append=*/false);
auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
mpms::SetClipLabelString("TEST", {"old_label_1", "old_label_2"},
input_sequence.get());
mpms::SetClipLabelIndex("TEST", {1, 2}, input_sequence.get());
mpms::SetClipLabelConfidence("TEST", {0.1, 0.2}, input_sequence.get());
mpms::SetClipLabelString("OTHER", {"old_label_3", "old_label_4"},
input_sequence.get());
mpms::SetClipLabelIndex("OTHER", {3, 4}, input_sequence.get());
mpms::SetClipLabelConfidence("OTHER", {0.3, 0.4}, input_sequence.get());
Detection detection_1;
detection_1.add_label("label_1");
detection_1.add_label("label_2");
detection_1.add_label_id(9);
detection_1.add_label_id(8);
detection_1.add_score(0.9);
detection_1.add_score(0.8);
runner_->MutableInputs()
->Tag(kClipLabelTestTag)
.packets.push_back(MakePacket<Detection>(detection_1).At(Timestamp(1)));
Detection detection_2;
detection_2.add_label("label_3");
detection_2.add_label("label_4");
detection_2.add_label_id(7);
detection_2.add_label_id(6);
detection_2.add_score(0.7);
detection_2.add_score(0.6);
runner_->MutableInputs()
->Tag(kClipLabelOtherTag)
.packets.push_back(MakePacket<Detection>(detection_2).At(Timestamp(2)));
runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
Adopt(input_sequence.release());
MP_ASSERT_OK(runner_->Run());
const std::vector<Packet>& output_packets =
runner_->Outputs().Tag(kSequenceExampleTag).packets;
ASSERT_EQ(1, output_packets.size());
const tf::SequenceExample& output_sequence =
output_packets[0].Get<tf::SequenceExample>();
ASSERT_THAT(
mpms::GetClipLabelString("TEST", output_sequence),
testing::ElementsAre("old_label_1", "old_label_2", "label_1", "label_2"));
ASSERT_THAT(mpms::GetClipLabelIndex("TEST", output_sequence),
testing::ElementsAre(1, 2, 9, 8));
ASSERT_THAT(mpms::GetClipLabelConfidence("TEST", output_sequence),
testing::ElementsAre(0.1, 0.2, 0.9, 0.8));
ASSERT_THAT(
mpms::GetClipLabelString("OTHER", output_sequence),
testing::ElementsAre("old_label_3", "old_label_4", "label_3", "label_4"));
ASSERT_THAT(mpms::GetClipLabelIndex("OTHER", output_sequence),
testing::ElementsAre(3, 4, 7, 6));
ASSERT_THAT(mpms::GetClipLabelConfidence("OTHER", output_sequence),
testing::ElementsAre(0.3, 0.4, 0.7, 0.6));
}
TEST_F(PackMediaSequenceCalculatorTest,
DifferentClipLabelScoreAndConfidenceSize) {
SetUpCalculator(
/*input_streams=*/{"CLIP_LABEL_TEST:test", "CLIP_LABEL_OTHER:test2"},
/*features=*/{}, /*output_only_if_all_present=*/false,
/*replace_instead_of_append=*/true);
auto input_sequence = ::absl::make_unique<tf::SequenceExample>();
Detection detection_1;
// 2 labels and 1 score.
detection_1.add_label("label_1");
detection_1.add_label("label_2");
detection_1.add_score(0.1);
runner_->MutableInputs()
->Tag(kClipLabelTestTag)
.packets.push_back(MakePacket<Detection>(detection_1).At(Timestamp(1)));
Detection detection_2;
detection_2.add_label("label_3");
detection_2.add_label("label_4");
detection_2.add_score(0.3);
detection_2.add_score(0.4);
runner_->MutableInputs()
->Tag(kClipLabelOtherTag)
.packets.push_back(MakePacket<Detection>(detection_2).At(Timestamp(2)));
runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
Adopt(input_sequence.release());
ASSERT_THAT(runner_->Run(),
testing::status::StatusIs(absl::StatusCode::kInvalidArgument));
}
TEST_F(PackMediaSequenceCalculatorTest, AddClipMediaId) {
SetUpCalculator(
/*input_streams=*/{"FLOAT_FEATURE_TEST:test",
"FLOAT_FEATURE_OTHER:test2"},
/*features=*/{},
/*output_only_if_all_present=*/false,
/*replace_instead_of_append=*/true,
/*output_as_zero_timestamp=*/false, /*input_side_packets=*/
{"SEQUENCE_EXAMPLE:input_sequence", "CLIP_MEDIA_ID:video_id"});
auto input_sequence = absl::make_unique<tf::SequenceExample>();
const std::string test_video_id = "test_video_id";
int num_timesteps = 2;
for (int i = 0; i < num_timesteps; ++i) {
auto vf_ptr = ::absl::make_unique<std::vector<float>>(2, 2 << i);
runner_->MutableInputs()
->Tag(kFloatFeatureTestTag)
.packets.push_back(Adopt(vf_ptr.release()).At(Timestamp(i)));
vf_ptr = ::absl::make_unique<std::vector<float>>(2, 2 << i);
runner_->MutableInputs()
->Tag(kFloatFeatureOtherTag)
.packets.push_back(Adopt(vf_ptr.release()).At(Timestamp(i)));
}
runner_->MutableSidePackets()->Tag(kClipMediaIdTag) =
MakePacket<std::string>(test_video_id);
runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
Adopt(input_sequence.release());
MP_ASSERT_OK(runner_->Run());
const std::vector<Packet>& output_packets =
runner_->Outputs().Tag(kSequenceExampleTag).packets;
ASSERT_EQ(1, output_packets.size());
const tf::SequenceExample& output_sequence =
output_packets[0].Get<tf::SequenceExample>();
ASSERT_EQ(test_video_id, mpms::GetClipMediaId(output_sequence));
}
TEST_F(PackMediaSequenceCalculatorTest, ReplaceClipMediaId) {
SetUpCalculator(
/*input_streams=*/{"FLOAT_FEATURE_TEST:test",
"FLOAT_FEATURE_OTHER:test2"},
/*features=*/{},
/*output_only_if_all_present=*/false,
/*replace_instead_of_append=*/true,
/*output_as_zero_timestamp=*/false, /*input_side_packets=*/
{"SEQUENCE_EXAMPLE:input_sequence", "CLIP_MEDIA_ID:video_id"});
auto input_sequence = absl::make_unique<tf::SequenceExample>();
const std::string existing_video_id = "existing_video_id";
mpms::SetClipMediaId(existing_video_id, input_sequence.get());
const std::string test_video_id = "test_video_id";
int num_timesteps = 2;
for (int i = 0; i < num_timesteps; ++i) {
auto vf_ptr = ::absl::make_unique<std::vector<float>>(2, 2 << i);
runner_->MutableInputs()
->Tag(kFloatFeatureTestTag)
.packets.push_back(Adopt(vf_ptr.release()).At(Timestamp(i)));
vf_ptr = ::absl::make_unique<std::vector<float>>(2, 2 << i);
runner_->MutableInputs()
->Tag(kFloatFeatureOtherTag)
.packets.push_back(Adopt(vf_ptr.release()).At(Timestamp(i)));
}
runner_->MutableSidePackets()->Tag(kClipMediaIdTag) =
MakePacket<std::string>(test_video_id).At(Timestamp(0));
runner_->MutableSidePackets()->Tag(kSequenceExampleTag) =
Adopt(input_sequence.release());
MP_ASSERT_OK(runner_->Run());
const std::vector<Packet>& output_packets =
runner_->Outputs().Tag(kSequenceExampleTag).packets;
ASSERT_EQ(1, output_packets.size());
const tf::SequenceExample& output_sequence =
output_packets[0].Get<tf::SequenceExample>();
ASSERT_EQ(test_video_id, mpms::GetClipMediaId(output_sequence));
}
TEST_F(PackMediaSequenceCalculatorTest, MissingStreamOK) {
SetUpCalculator(
{"FORWARD_FLOW_ENCODED:flow", "FLOAT_FEATURE_I3D_FLOW:feature"}, {},
@@ -1065,6 +1829,7 @@ TEST_F(PackMediaSequenceCalculatorTest, TestOverwritingAndReconciling) {
mpms::AddBBoxNumRegions(-1, input_sequence.get());
mpms::AddBBoxLabelString({"anything"}, input_sequence.get());
mpms::AddBBoxLabelIndex({-1}, input_sequence.get());
mpms::AddBBoxLabelConfidence({-1}, input_sequence.get());
mpms::AddBBoxClassString({"anything"}, input_sequence.get());
mpms::AddBBoxClassIndex({-1}, input_sequence.get());
mpms::AddBBoxTrackString({"anything"}, input_sequence.get());
@@ -12,6 +12,7 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "absl/log/absl_log.h"
#include "mediapipe/calculators/tensorflow/tensor_squeeze_dimensions_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/port/ret_check.h"
@@ -99,10 +100,11 @@ class TensorSqueezeDimensionsCalculator : public CalculatorBase {
}
}
if (remove_dims_.empty()) {
LOG(ERROR) << "TensorSqueezeDimensionsCalculator is squeezing input with "
"no single-dimensions. Calculator will be a no-op.";
LOG(ERROR) << "Input to TensorSqueezeDimensionsCalculator has shape "
<< tensor_shape.DebugString();
ABSL_LOG(ERROR)
<< "TensorSqueezeDimensionsCalculator is squeezing input with "
"no single-dimensions. Calculator will be a no-op.";
ABSL_LOG(ERROR) << "Input to TensorSqueezeDimensionsCalculator has shape "
<< tensor_shape.DebugString();
}
}
};
@@ -14,6 +14,7 @@
#include <iostream>
#include "absl/log/absl_check.h"
#include "mediapipe/calculators/tensorflow/tensor_to_image_frame_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/formats/image_frame.h"
@@ -99,7 +100,7 @@ absl::Status TensorToImageFrameCalculator::Process(CalculatorContext* cc) {
const tf::Tensor& input_tensor = cc->Inputs().Tag(kTensor).Get<tf::Tensor>();
int32_t depth = 1;
if (input_tensor.dims() != 2) { // Depth is 1 for 2D tensors.
CHECK(3 == input_tensor.dims())
ABSL_CHECK(3 == input_tensor.dims())
<< "Only 2 or 3-D Tensors can be converted to frames. Instead got: "
<< input_tensor.dims();
depth = input_tensor.dim_size(2);
@@ -15,6 +15,7 @@
// Calculator converts from one-dimensional Tensor of DT_FLOAT to Matrix
// OR from (batched) two-dimensional Tensor of DT_FLOAT to Matrix.
#include "absl/log/absl_check.h"
#include "mediapipe/calculators/tensorflow/tensor_to_matrix_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/formats/matrix.h"
@@ -36,7 +37,7 @@ constexpr char kReference[] = "REFERENCE";
absl::Status FillTimeSeriesHeaderIfValid(const Packet& header_packet,
TimeSeriesHeader* header) {
CHECK(header);
ABSL_CHECK(header);
if (header_packet.IsEmpty()) {
return absl::UnknownError("No header found.");
}
@@ -191,7 +192,7 @@ absl::Status TensorToMatrixCalculator::Process(CalculatorContext* cc) {
<< "Tensor stream packet does not contain a Tensor.";
const tf::Tensor& input_tensor = cc->Inputs().Tag(kTensor).Get<tf::Tensor>();
CHECK(1 == input_tensor.dims() || 2 == input_tensor.dims())
ABSL_CHECK(1 == input_tensor.dims() || 2 == input_tensor.dims())
<< "Only 1-D or 2-D Tensors can be converted to matrices.";
const int32_t length = input_tensor.dim_size(input_tensor.dims() - 1);
const int32_t width =
@@ -15,12 +15,16 @@
// Calculator converts from one-dimensional Tensor of DT_FLOAT to vector<float>
// OR from (batched) two-dimensional Tensor of DT_FLOAT to vector<vector<float>.
#include <memory>
#include <vector>
#include "mediapipe/calculators/tensorflow/tensor_to_vector_float_calculator_options.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/port/ret_check.h"
#include "mediapipe/framework/port/status.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/platform/bfloat16.h"
namespace mediapipe {
@@ -76,21 +80,31 @@ absl::Status TensorToVectorFloatCalculator::Open(CalculatorContext* cc) {
absl::Status TensorToVectorFloatCalculator::Process(CalculatorContext* cc) {
const tf::Tensor& input_tensor =
cc->Inputs().Index(0).Value().Get<tf::Tensor>();
RET_CHECK(tf::DT_FLOAT == input_tensor.dtype())
<< "expected DT_FLOAT input but got "
RET_CHECK(tf::DT_FLOAT == input_tensor.dtype() ||
tf::DT_BFLOAT16 == input_tensor.dtype())
<< "expected DT_FLOAT or DT_BFLOAT_16 input but got "
<< tensorflow::DataTypeString(input_tensor.dtype());
if (options_.tensor_is_2d()) {
RET_CHECK(2 == input_tensor.dims())
<< "Expected 2-dimensional Tensor, but the tensor shape is: "
<< input_tensor.shape().DebugString();
auto output = absl::make_unique<std::vector<std::vector<float>>>(
auto output = std::make_unique<std::vector<std::vector<float>>>(
input_tensor.dim_size(0), std::vector<float>(input_tensor.dim_size(1)));
for (int i = 0; i < input_tensor.dim_size(0); ++i) {
auto& instance_output = output->at(i);
const auto& slice = input_tensor.Slice(i, i + 1).unaligned_flat<float>();
for (int j = 0; j < input_tensor.dim_size(1); ++j) {
instance_output.at(j) = slice(j);
if (tf::DT_BFLOAT16 == input_tensor.dtype()) {
const auto& slice =
input_tensor.Slice(i, i + 1).unaligned_flat<tf::bfloat16>();
for (int j = 0; j < input_tensor.dim_size(1); ++j) {
instance_output.at(j) = static_cast<float>(slice(j));
}
} else {
const auto& slice =
input_tensor.Slice(i, i + 1).unaligned_flat<float>();
for (int j = 0; j < input_tensor.dim_size(1); ++j) {
instance_output.at(j) = slice(j);
}
}
}
cc->Outputs().Index(0).Add(output.release(), cc->InputTimestamp());
@@ -101,10 +115,17 @@ absl::Status TensorToVectorFloatCalculator::Process(CalculatorContext* cc) {
<< "tensor shape is: " << input_tensor.shape().DebugString();
}
auto output =
absl::make_unique<std::vector<float>>(input_tensor.NumElements());
const auto& tensor_values = input_tensor.unaligned_flat<float>();
for (int i = 0; i < input_tensor.NumElements(); ++i) {
output->at(i) = tensor_values(i);
std::make_unique<std::vector<float>>(input_tensor.NumElements());
if (tf::DT_BFLOAT16 == input_tensor.dtype()) {
const auto& tensor_values = input_tensor.unaligned_flat<tf::bfloat16>();
for (int i = 0; i < input_tensor.NumElements(); ++i) {
output->at(i) = static_cast<float>(tensor_values(i));
}
} else {
const auto& tensor_values = input_tensor.unaligned_flat<float>();
for (int i = 0; i < input_tensor.NumElements(); ++i) {
output->at(i) = tensor_values(i);
}
}
cc->Outputs().Index(0).Add(output.release(), cc->InputTimestamp());
}
@@ -12,6 +12,8 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include <memory>
#include "mediapipe/calculators/tensorflow/tensor_to_vector_float_calculator_options.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/calculator_runner.h"
@@ -19,6 +21,7 @@
#include "mediapipe/util/packet_test_util.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/bfloat16.h"
namespace mediapipe {
@@ -72,6 +75,62 @@ TEST_F(TensorToVectorFloatCalculatorTest, ConvertsToVectorFloat) {
}
}
TEST_F(TensorToVectorFloatCalculatorTest, CheckBFloat16Type) {
SetUpRunner(false, false);
const tf::TensorShape tensor_shape(std::vector<tf::int64>{5});
auto tensor = std::make_unique<tf::Tensor>(tf::DT_BFLOAT16, tensor_shape);
auto tensor_vec = tensor->vec<tf::bfloat16>();
for (int i = 0; i < 5; ++i) {
tensor_vec(i) = static_cast<tf::bfloat16>(1 << i);
}
const int64_t time = 1234;
runner_->MutableInputs()->Index(0).packets.push_back(
Adopt(tensor.release()).At(Timestamp(time)));
EXPECT_TRUE(runner_->Run().ok());
const std::vector<Packet>& output_packets =
runner_->Outputs().Index(0).packets;
EXPECT_EQ(1, output_packets.size());
EXPECT_EQ(time, output_packets[0].Timestamp().Value());
const std::vector<float>& output_vector =
output_packets[0].Get<std::vector<float>>();
EXPECT_EQ(5, output_vector.size());
for (int i = 0; i < 5; ++i) {
const float expected = static_cast<float>(1 << i);
EXPECT_EQ(expected, output_vector[i]);
}
}
TEST_F(TensorToVectorFloatCalculatorTest, CheckBFloat16TypeAllDim) {
SetUpRunner(false, true);
const tf::TensorShape tensor_shape(std::vector<tf::int64>{2, 2, 2});
auto tensor = std::make_unique<tf::Tensor>(tf::DT_BFLOAT16, tensor_shape);
auto slice = tensor->flat<tf::bfloat16>();
for (int i = 0; i < 2 * 2 * 2; ++i) {
// 2^i can be represented exactly in floating point numbers if 'i' is small.
slice(i) = static_cast<tf::bfloat16>(1 << i);
}
const int64_t time = 1234;
runner_->MutableInputs()->Index(0).packets.push_back(
Adopt(tensor.release()).At(Timestamp(time)));
EXPECT_TRUE(runner_->Run().ok());
const std::vector<Packet>& output_packets =
runner_->Outputs().Index(0).packets;
EXPECT_EQ(1, output_packets.size());
EXPECT_EQ(time, output_packets[0].Timestamp().Value());
const std::vector<float>& output_vector =
output_packets[0].Get<std::vector<float>>();
EXPECT_EQ(2 * 2 * 2, output_vector.size());
for (int i = 0; i < 2 * 2 * 2; ++i) {
const float expected = static_cast<float>(1 << i);
EXPECT_EQ(expected, output_vector[i]);
}
}
TEST_F(TensorToVectorFloatCalculatorTest, ConvertsBatchedToVectorVectorFloat) {
SetUpRunner(true, false);
const tf::TensorShape tensor_shape(std::vector<tf::int64>{1, 5});
@@ -20,6 +20,7 @@
#include <vector>
#include "absl/base/thread_annotations.h"
#include "absl/log/absl_check.h"
#include "absl/memory/memory.h"
#include "absl/strings/str_split.h"
#include "absl/synchronization/mutex.h"
@@ -515,7 +516,7 @@ class TensorFlowInferenceCalculator : public CalculatorBase {
tf::Tensor concated;
const tf::Status concat_status =
tf::tensor::Concat(keyed_tensors.second, &concated);
CHECK(concat_status.ok()) << concat_status.ToString();
ABSL_CHECK(concat_status.ok()) << concat_status.ToString();
input_tensors.emplace_back(tag_to_tensor_map_[keyed_tensors.first],
concated);
}
@@ -597,7 +598,7 @@ class TensorFlowInferenceCalculator : public CalculatorBase {
std::vector<tf::Tensor> split_tensors;
const tf::Status split_status =
tf::tensor::Split(outputs[i], split_vector, &split_tensors);
CHECK(split_status.ok()) << split_status.ToString();
ABSL_CHECK(split_status.ok()) << split_status.ToString();
// Loop over timestamps so that we don't copy the padding.
for (int j = 0; j < inference_state->batch_timestamps_.size(); ++j) {
tf::Tensor output_tensor(split_tensors[j]);
@@ -17,6 +17,8 @@
#include <vector>
#include "absl/flags/flag.h"
#include "absl/log/absl_check.h"
#include "absl/log/absl_log.h"
#include "mediapipe/calculators/tensorflow/tensorflow_inference_calculator.pb.h"
#include "mediapipe/calculators/tensorflow/tensorflow_session_from_frozen_graph_generator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
@@ -118,7 +120,7 @@ class TensorflowInferenceCalculatorTest : public ::testing::Test {
// Create tensor from Vector and add as a Packet to the provided tag as input.
void AddVectorToInputsAsPacket(const std::vector<Packet>& packets,
const std::string& tag) {
CHECK(!packets.empty())
ABSL_CHECK(!packets.empty())
<< "Please specify at least some data in the packet";
auto packets_ptr = absl::make_unique<std::vector<Packet>>(packets);
runner_->MutableInputs()->Tag(tag).packets.push_back(
@@ -586,12 +588,12 @@ TEST_F(TensorflowInferenceCalculatorTest, TestRecurrentStates) {
runner_->Outputs().Tag(kMultipliedTag).packets;
ASSERT_EQ(2, output_packets_mult.size());
const tf::Tensor& tensor_mult = output_packets_mult[0].Get<tf::Tensor>();
LOG(INFO) << "timestamp: " << 0;
ABSL_LOG(INFO) << "timestamp: " << 0;
auto expected_tensor = tf::test::AsTensor<int32_t>({3, 8, 15});
tf::test::ExpectTensorEqual<int32_t>(tensor_mult, expected_tensor);
const tf::Tensor& tensor_mult1 = output_packets_mult[1].Get<tf::Tensor>();
auto expected_tensor1 = tf::test::AsTensor<int32_t>({9, 32, 75});
LOG(INFO) << "timestamp: " << 1;
ABSL_LOG(INFO) << "timestamp: " << 1;
tf::test::ExpectTensorEqual<int32_t>(tensor_mult1, expected_tensor1);
EXPECT_EQ(2, runner_
@@ -627,12 +629,12 @@ TEST_F(TensorflowInferenceCalculatorTest, TestRecurrentStateOverride) {
runner_->Outputs().Tag(kMultipliedTag).packets;
ASSERT_EQ(2, output_packets_mult.size());
const tf::Tensor& tensor_mult = output_packets_mult[0].Get<tf::Tensor>();
LOG(INFO) << "timestamp: " << 0;
ABSL_LOG(INFO) << "timestamp: " << 0;
auto expected_tensor = tf::test::AsTensor<int32_t>({3, 4, 5});
tf::test::ExpectTensorEqual<int32_t>(tensor_mult, expected_tensor);
const tf::Tensor& tensor_mult1 = output_packets_mult[1].Get<tf::Tensor>();
auto expected_tensor1 = tf::test::AsTensor<int32_t>({3, 4, 5});
LOG(INFO) << "timestamp: " << 1;
ABSL_LOG(INFO) << "timestamp: " << 1;
tf::test::ExpectTensorEqual<int32_t>(tensor_mult1, expected_tensor1);
EXPECT_EQ(2, runner_
@@ -23,12 +23,12 @@
#include <string>
#include "absl/log/absl_log.h"
#include "mediapipe/calculators/tensorflow/tensorflow_session.h"
#include "mediapipe/calculators/tensorflow/tensorflow_session_from_frozen_graph_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/deps/clock.h"
#include "mediapipe/framework/deps/monotonic_clock.h"
#include "mediapipe/framework/port/logging.h"
#include "mediapipe/framework/port/ret_check.h"
#include "mediapipe/framework/port/status.h"
#include "mediapipe/framework/tool/status_util.h"
@@ -156,8 +156,8 @@ class TensorFlowSessionFromFrozenGraphCalculator : public CalculatorBase {
cc->OutputSidePackets().Tag(kSessionTag).Set(Adopt(session.release()));
const uint64_t end_time = absl::ToUnixMicros(clock->TimeNow());
LOG(INFO) << "Loaded frozen model in: " << end_time - start_time
<< " microseconds.";
ABSL_LOG(INFO) << "Loaded frozen model in: " << end_time - start_time
<< " microseconds.";
return absl::OkStatus();
}
@@ -24,13 +24,13 @@
#include <string>
#include "absl/log/absl_log.h"
#include "mediapipe/calculators/tensorflow/tensorflow_session.h"
#include "mediapipe/calculators/tensorflow/tensorflow_session_from_frozen_graph_generator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/deps/clock.h"
#include "mediapipe/framework/deps/monotonic_clock.h"
#include "mediapipe/framework/port/file_helpers.h"
#include "mediapipe/framework/port/logging.h"
#include "mediapipe/framework/port/ret_check.h"
#include "mediapipe/framework/port/status.h"
#include "mediapipe/framework/tool/status_util.h"
@@ -155,8 +155,8 @@ class TensorFlowSessionFromFrozenGraphGenerator : public PacketGenerator {
output_side_packets->Tag(kSessionTag) = Adopt(session.release());
const uint64_t end_time = absl::ToUnixMicros(clock->TimeNow());
LOG(INFO) << "Loaded frozen model in: " << end_time - start_time
<< " microseconds.";
ABSL_LOG(INFO) << "Loaded frozen model in: " << end_time - start_time
<< " microseconds.";
return absl::OkStatus();
}
};
@@ -17,6 +17,7 @@
#if !defined(__ANDROID__)
#include "mediapipe/framework/port/file_helpers.h"
#endif
#include "absl/log/absl_log.h"
#include "absl/strings/str_replace.h"
#include "mediapipe/calculators/tensorflow/tensorflow_session.h"
#include "mediapipe/calculators/tensorflow/tensorflow_session_from_saved_model_calculator.pb.h"
@@ -69,7 +70,7 @@ const std::string MaybeConvertSignatureToTag(
[](unsigned char c) { return std::toupper(c); });
output = absl::StrReplaceAll(
output, {{"/", "_"}, {"-", "_"}, {".", "_"}, {":", "_"}});
LOG(INFO) << "Renamed TAG from: " << name << " to " << output;
ABSL_LOG(INFO) << "Renamed TAG from: " << name << " to " << output;
return output;
} else {
return name;
@@ -19,6 +19,7 @@
#if !defined(__ANDROID__)
#include "mediapipe/framework/port/file_helpers.h"
#endif
#include "absl/log/absl_log.h"
#include "absl/strings/str_replace.h"
#include "mediapipe/calculators/tensorflow/tensorflow_session.h"
#include "mediapipe/calculators/tensorflow/tensorflow_session_from_saved_model_generator.pb.h"
@@ -75,7 +76,7 @@ const std::string MaybeConvertSignatureToTag(
[](unsigned char c) { return std::toupper(c); });
output = absl::StrReplaceAll(
output, {{"/", "_"}, {"-", "_"}, {".", "_"}, {":", "_"}});
LOG(INFO) << "Renamed TAG from: " << name << " to " << output;
ABSL_LOG(INFO) << "Renamed TAG from: " << name << " to " << output;
return output;
} else {
return name;
@@ -13,6 +13,7 @@
// limitations under the License.
#include "absl/container/flat_hash_map.h"
#include "absl/log/absl_log.h"
#include "absl/strings/match.h"
#include "mediapipe/calculators/core/packet_resampler_calculator.pb.h"
#include "mediapipe/calculators/tensorflow/unpack_media_sequence_calculator.pb.h"
@@ -201,8 +202,8 @@ class UnpackMediaSequenceCalculator : public CalculatorBase {
first_timestamp_seen_ = Timestamp::OneOverPostStream().Value();
for (const auto& map_kv : sequence_->feature_lists().feature_list()) {
if (absl::StrContains(map_kv.first, "/timestamp")) {
LOG(INFO) << "Found feature timestamps: " << map_kv.first
<< " with size: " << map_kv.second.feature_size();
ABSL_LOG(INFO) << "Found feature timestamps: " << map_kv.first
<< " with size: " << map_kv.second.feature_size();
int64_t recent_timestamp = Timestamp::PreStream().Value();
for (int i = 0; i < map_kv.second.feature_size(); ++i) {
int64_t next_timestamp =
@@ -309,8 +310,8 @@ class UnpackMediaSequenceCalculator : public CalculatorBase {
audio_decoder_options->set_end_time(
end_time + options.extra_padding_from_media_decoder());
}
LOG(INFO) << "Created AudioDecoderOptions:\n"
<< audio_decoder_options->DebugString();
ABSL_LOG(INFO) << "Created AudioDecoderOptions:\n"
<< audio_decoder_options->DebugString();
cc->OutputSidePackets()
.Tag(kAudioDecoderOptions)
.Set(Adopt(audio_decoder_options.release()));
@@ -331,8 +332,8 @@ class UnpackMediaSequenceCalculator : public CalculatorBase {
->set_end_time(Timestamp::FromSeconds(end_time).Value());
}
LOG(INFO) << "Created PacketResamplerOptions:\n"
<< resampler_options->DebugString();
ABSL_LOG(INFO) << "Created PacketResamplerOptions:\n"
<< resampler_options->DebugString();
cc->OutputSidePackets()
.Tag(kPacketResamplerOptions)
.Set(Adopt(resampler_options.release()));
@@ -351,7 +352,8 @@ class UnpackMediaSequenceCalculator : public CalculatorBase {
absl::Status Process(CalculatorContext* cc) override {
if (timestamps_.empty()) {
// This occurs when we only have metadata to unpack.
LOG(INFO) << "only unpacking metadata because there are no timestamps.";
ABSL_LOG(INFO)
<< "only unpacking metadata because there are no timestamps.";
return tool::StatusStop();
}
// In Process(), we loop through timestamps on a reference stream and emit
@@ -12,6 +12,7 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "absl/log/absl_log.h"
#include "absl/memory/memory.h"
#include "absl/strings/numbers.h"
#include "mediapipe/calculators/core/packet_resampler_calculator.pb.h"
@@ -81,7 +82,7 @@ class UnpackMediaSequenceCalculatorTest : public ::testing::Test {
if (options != nullptr) {
*config.mutable_options() = *options;
}
LOG(INFO) << config.DebugString();
ABSL_LOG(INFO) << config.DebugString();
runner_ = absl::make_unique<CalculatorRunner>(config);
}
@@ -14,6 +14,8 @@
#include <iterator>
#include "absl/log/absl_check.h"
#include "absl/log/absl_log.h"
#include "mediapipe/calculators/tensorflow/lapped_tensor_buffer_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/packet.h"
@@ -46,7 +48,7 @@ std::string GetQuantizedFeature(
.Get(index)
.bytes_list()
.value();
CHECK_EQ(1, bytes_list.size());
ABSL_CHECK_EQ(1, bytes_list.size());
return bytes_list.Get(0);
}
} // namespace
@@ -149,8 +151,9 @@ class UnpackYt8mSequenceExampleCalculator : public CalculatorBase {
.Set(MakePacket<int>(segment_size));
}
}
LOG(INFO) << "Reading the sequence example that contains yt8m id: "
<< yt8m_id << ". Feature list length: " << feature_list_length_;
ABSL_LOG(INFO) << "Reading the sequence example that contains yt8m id: "
<< yt8m_id
<< ". Feature list length: " << feature_list_length_;
return absl::OkStatus();
}
@@ -14,6 +14,7 @@
//
// Converts vector<float> (or vector<vector<float>>) to 1D (or 2D) tf::Tensor.
#include "absl/log/absl_log.h"
#include "mediapipe/calculators/tensorflow/vector_float_to_tensor_calculator_options.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/port/ret_check.h"
@@ -68,7 +69,7 @@ absl::Status VectorFloatToTensorCalculator::GetContract(
// Output vector<float>.
);
} else {
LOG(FATAL) << "input size not supported";
ABSL_LOG(FATAL) << "input size not supported";
}
RET_CHECK_EQ(cc->Outputs().NumEntries(), 1)
<< "Only one output stream is supported.";
@@ -125,7 +126,7 @@ absl::Status VectorFloatToTensorCalculator::Process(CalculatorContext* cc) {
}
cc->Outputs().Index(0).Add(output.release(), cc->InputTimestamp());
} else {
LOG(FATAL) << "input size not supported";
ABSL_LOG(FATAL) << "input size not supported";
}
return absl::OkStatus();
}
@@ -15,6 +15,8 @@
// Converts a single int or vector<int> or vector<vector<int>> to 1D (or 2D)
// tf::Tensor.
#include "absl/log/absl_check.h"
#include "absl/log/absl_log.h"
#include "mediapipe/calculators/tensorflow/vector_int_to_tensor_calculator_options.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/port/ret_check.h"
@@ -86,7 +88,7 @@ absl::Status VectorIntToTensorCalculator::GetContract(CalculatorContract* cc) {
cc->Inputs().Tag(kVectorInt).Set<std::vector<int>>();
}
} else {
LOG(FATAL) << "input size not supported";
ABSL_LOG(FATAL) << "input size not supported";
}
RET_CHECK_EQ(cc->Outputs().NumEntries(), 1)
<< "Only one output stream is supported.";
@@ -113,11 +115,11 @@ absl::Status VectorIntToTensorCalculator::Process(CalculatorContext* cc) {
.Get<std::vector<std::vector<int>>>();
const int32_t rows = input.size();
CHECK_GE(rows, 1);
ABSL_CHECK_GE(rows, 1);
const int32_t cols = input[0].size();
CHECK_GE(cols, 1);
ABSL_CHECK_GE(cols, 1);
for (int i = 1; i < rows; ++i) {
CHECK_EQ(input[i].size(), cols);
ABSL_CHECK_EQ(input[i].size(), cols);
}
if (options_.transpose()) {
tensor_shape = tf::TensorShape({cols, rows});
@@ -140,7 +142,7 @@ absl::Status VectorIntToTensorCalculator::Process(CalculatorContext* cc) {
AssignMatrixValue<int>(c, r, input[r][c], output.get());
break;
default:
LOG(FATAL) << "tensor data type is not supported.";
ABSL_LOG(FATAL) << "tensor data type is not supported.";
}
}
}
@@ -158,7 +160,7 @@ absl::Status VectorIntToTensorCalculator::Process(CalculatorContext* cc) {
AssignMatrixValue<int>(r, c, input[r][c], output.get());
break;
default:
LOG(FATAL) << "tensor data type is not supported.";
ABSL_LOG(FATAL) << "tensor data type is not supported.";
}
}
}
@@ -171,7 +173,7 @@ absl::Status VectorIntToTensorCalculator::Process(CalculatorContext* cc) {
} else {
input = cc->Inputs().Tag(kVectorInt).Value().Get<std::vector<int>>();
}
CHECK_GE(input.size(), 1);
ABSL_CHECK_GE(input.size(), 1);
const int32_t length = input.size();
tensor_shape = tf::TensorShape({length});
auto output = ::absl::make_unique<tf::Tensor>(options_.tensor_data_type(),
@@ -188,12 +190,12 @@ absl::Status VectorIntToTensorCalculator::Process(CalculatorContext* cc) {
output->tensor<int, 1>()(i) = input.at(i);
break;
default:
LOG(FATAL) << "tensor data type is not supported.";
ABSL_LOG(FATAL) << "tensor data type is not supported.";
}
}
cc->Outputs().Tag(kTensorOut).Add(output.release(), cc->InputTimestamp());
} else {
LOG(FATAL) << "input size not supported";
ABSL_LOG(FATAL) << "input size not supported";
}
return absl::OkStatus();
}
@@ -15,6 +15,7 @@
// Converts vector<std::string> (or vector<vector<std::string>>) to 1D (or 2D)
// tf::Tensor.
#include "absl/log/absl_log.h"
#include "mediapipe/calculators/tensorflow/vector_string_to_tensor_calculator_options.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/port/ret_check.h"
@@ -69,7 +70,7 @@ absl::Status VectorStringToTensorCalculator::GetContract(
// Input vector<std::string>.
);
} else {
LOG(FATAL) << "input size not supported";
ABSL_LOG(FATAL) << "input size not supported";
}
RET_CHECK_EQ(cc->Outputs().NumEntries(), 1)
<< "Only one output stream is supported.";
@@ -129,7 +130,7 @@ absl::Status VectorStringToTensorCalculator::Process(CalculatorContext* cc) {
}
cc->Outputs().Index(0).Add(output.release(), cc->InputTimestamp());
} else {
LOG(FATAL) << "input size not supported";
ABSL_LOG(FATAL) << "input size not supported";
}
return absl::OkStatus();
}
+10
View File
@@ -103,6 +103,8 @@ cc_library(
"//mediapipe/framework/formats/object_detection:anchor_cc_proto",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/log:absl_log",
],
alwayslink = 1,
)
@@ -196,10 +198,13 @@ cc_library(
deps = [
":tflite_inference_calculator_cc_proto",
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework/port:logging",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/stream_handler:fixed_size_input_stream_handler",
"//mediapipe/util/tflite:config",
"//mediapipe/util/tflite:tflite_model_loader",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/log:absl_log",
"@com_google_absl//absl/memory",
"@org_tensorflow//tensorflow/lite:framework",
"@org_tensorflow//tensorflow/lite/delegates/xnnpack:xnnpack_delegate",
@@ -275,6 +280,7 @@ cc_library(
"//mediapipe/framework/stream_handler:fixed_size_input_stream_handler",
"//mediapipe/util:resource_util",
"//mediapipe/util/tflite:config",
"@com_google_absl//absl/log:absl_check",
"@org_tensorflow//tensorflow/lite:framework",
"@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
] + selects.with_or({
@@ -392,6 +398,8 @@ cc_library(
"//mediapipe/framework/formats/object_detection:anchor_cc_proto",
"//mediapipe/framework/port:ret_check",
"//mediapipe/util/tflite:config",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/log:absl_log",
"@com_google_absl//absl/strings:str_format",
"@com_google_absl//absl/types:span",
"@org_tensorflow//tensorflow/lite:framework",
@@ -428,6 +436,7 @@ cc_library(
"//mediapipe/framework/port:ret_check",
"//mediapipe/util:resource_util",
"@com_google_absl//absl/container:node_hash_map",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/strings:str_format",
"@com_google_absl//absl/types:span",
"@org_tensorflow//tensorflow/lite:framework",
@@ -456,6 +465,7 @@ cc_library(
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework/formats:landmark_cc_proto",
"//mediapipe/framework/port:ret_check",
"@com_google_absl//absl/log:absl_check",
"@org_tensorflow//tensorflow/lite:framework",
],
alwayslink = 1,
@@ -16,6 +16,8 @@
#include <utility>
#include <vector>
#include "absl/log/absl_check.h"
#include "absl/log/absl_log.h"
#include "mediapipe/calculators/tflite/ssd_anchors_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/formats/object_detection/anchor.pb.h"
@@ -272,13 +274,13 @@ absl::Status SsdAnchorsCalculator::GenerateAnchors(
if (options.feature_map_height_size()) {
if (options.strides_size()) {
LOG(ERROR) << "Found feature map shapes. Strides will be ignored.";
ABSL_LOG(ERROR) << "Found feature map shapes. Strides will be ignored.";
}
CHECK_EQ(options.feature_map_height_size(), kNumLayers);
CHECK_EQ(options.feature_map_height_size(),
options.feature_map_width_size());
ABSL_CHECK_EQ(options.feature_map_height_size(), kNumLayers);
ABSL_CHECK_EQ(options.feature_map_height_size(),
options.feature_map_width_size());
} else {
CHECK_EQ(options.strides_size(), kNumLayers);
ABSL_CHECK_EQ(options.strides_size(), kNumLayers);
}
if (options.multiscale_anchor_generation()) {
@@ -15,6 +15,7 @@
#include <string>
#include <vector>
#include "absl/log/absl_check.h"
#include "mediapipe/calculators/tflite/tflite_converter_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/formats/image_frame.h"
@@ -643,7 +644,7 @@ absl::Status TfLiteConverterCalculator::LoadOptions(CalculatorContext* cc) {
if (options.has_output_tensor_float_range()) {
output_range_.emplace(options.output_tensor_float_range().min(),
options.output_tensor_float_range().max());
CHECK_GT(output_range_->second, output_range_->first);
ABSL_CHECK_GT(output_range_->second, output_range_->first);
}
// Custom div and sub values.
@@ -661,9 +662,9 @@ absl::Status TfLiteConverterCalculator::LoadOptions(CalculatorContext* cc) {
// Get desired way to handle input channels.
max_num_channels_ = options.max_num_channels();
CHECK_GE(max_num_channels_, 1);
CHECK_LE(max_num_channels_, 4);
CHECK_NE(max_num_channels_, 2);
ABSL_CHECK_GE(max_num_channels_, 1);
ABSL_CHECK_LE(max_num_channels_, 4);
ABSL_CHECK_NE(max_num_channels_, 2);
#if defined(MEDIAPIPE_IOS)
if (cc->Inputs().HasTag(kGpuBufferTag))
// Currently on iOS, tflite gpu input tensor must be 4 channels,
@@ -17,9 +17,12 @@
#include <string>
#include <vector>
#include "absl/log/absl_check.h"
#include "absl/log/absl_log.h"
#include "absl/memory/memory.h"
#include "mediapipe/calculators/tflite/tflite_inference_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/port/logging.h"
#include "mediapipe/framework/port/ret_check.h"
#include "mediapipe/util/tflite/config.h"
@@ -109,8 +112,8 @@ std::unique_ptr<tflite::Interpreter> BuildEdgeTpuInterpreter(
edgetpu::EdgeTpuContext* edgetpu_context) {
resolver->AddCustom(edgetpu::kCustomOp, edgetpu::RegisterCustomOp());
std::unique_ptr<tflite::Interpreter> interpreter;
CHECK_EQ(tflite::InterpreterBuilder(model, *resolver)(&interpreter),
kTfLiteOk);
ABSL_CHECK_EQ(tflite::InterpreterBuilder(model, *resolver)(&interpreter),
kTfLiteOk);
interpreter->SetExternalContext(kTfLiteEdgeTpuContext, edgetpu_context);
return interpreter;
}
@@ -406,11 +409,12 @@ absl::Status TfLiteInferenceCalculator::Open(CalculatorContext* cc) {
}
if (use_advanced_gpu_api_ && !gpu_input_) {
LOG(WARNING) << "Cannot use advanced GPU APIs, input must be GPU buffers."
"Falling back to the default TFLite API.";
ABSL_LOG(WARNING)
<< "Cannot use advanced GPU APIs, input must be GPU buffers."
"Falling back to the default TFLite API.";
use_advanced_gpu_api_ = false;
}
CHECK(!use_advanced_gpu_api_ || gpu_inference_);
ABSL_CHECK(!use_advanced_gpu_api_ || gpu_inference_);
MP_RETURN_IF_ERROR(LoadModel(cc));
@@ -802,9 +806,10 @@ absl::Status TfLiteInferenceCalculator::InitTFLiteGPURunner(
const int tensor_idx = interpreter_->inputs()[i];
interpreter_->SetTensorParametersReadWrite(tensor_idx, kTfLiteFloat32, "",
shape, quant);
CHECK(interpreter_->ResizeInputTensor(tensor_idx, shape) == kTfLiteOk);
ABSL_CHECK(interpreter_->ResizeInputTensor(tensor_idx, shape) ==
kTfLiteOk);
}
CHECK(interpreter_->AllocateTensors() == kTfLiteOk);
ABSL_CHECK(interpreter_->AllocateTensors() == kTfLiteOk);
}
// Create and bind OpenGL buffers for outputs.
@@ -1053,7 +1058,7 @@ absl::Status TfLiteInferenceCalculator::LoadDelegate(CalculatorContext* cc) {
gpu_data_in_[i]->shape.w * gpu_data_in_[i]->shape.c;
// Input to model can be RGBA only.
if (tensor->dims->data[3] != 4) {
LOG(WARNING) << "Please ensure input GPU tensor is 4 channels.";
ABSL_LOG(WARNING) << "Please ensure input GPU tensor is 4 channels.";
}
const std::string shader_source =
absl::Substitute(R"(#include <metal_stdlib>
@@ -17,6 +17,7 @@
#include <vector>
#include "absl/container/node_hash_map.h"
#include "absl/log/absl_check.h"
#include "absl/strings/str_format.h"
#include "absl/types/span.h"
#include "mediapipe/calculators/tflite/tflite_tensors_to_classification_calculator.pb.h"
@@ -172,7 +173,7 @@ absl::Status TfLiteTensorsToClassificationCalculator::Process(
// Note that partial_sort will raise error when top_k_ >
// classification_list->classification_size().
CHECK_GE(classification_list->classification_size(), top_k_);
ABSL_CHECK_GE(classification_list->classification_size(), top_k_);
auto raw_classification_list = classification_list->mutable_classification();
if (top_k_ > 0 && classification_list->classification_size() >= top_k_) {
std::partial_sort(raw_classification_list->begin(),
@@ -15,6 +15,8 @@
#include <unordered_map>
#include <vector>
#include "absl/log/absl_check.h"
#include "absl/log/absl_log.h"
#include "absl/strings/str_format.h"
#include "absl/types/span.h"
#include "mediapipe/calculators/tflite/tflite_tensors_to_detections_calculator.pb.h"
@@ -93,7 +95,7 @@ void ConvertRawValuesToAnchors(const float* raw_anchors, int num_boxes,
void ConvertAnchorsToRawValues(const std::vector<Anchor>& anchors,
int num_boxes, float* raw_anchors) {
CHECK_EQ(anchors.size(), num_boxes);
ABSL_CHECK_EQ(anchors.size(), num_boxes);
int box = 0;
for (const auto& anchor : anchors) {
raw_anchors[box * kNumCoordsPerBox + 0] = anchor.y_center();
@@ -288,14 +290,14 @@ absl::Status TfLiteTensorsToDetectionsCalculator::ProcessCPU(
const TfLiteTensor* raw_score_tensor = &input_tensors[1];
// TODO: Add flexible input tensor size handling.
CHECK_EQ(raw_box_tensor->dims->size, 3);
CHECK_EQ(raw_box_tensor->dims->data[0], 1);
CHECK_EQ(raw_box_tensor->dims->data[1], num_boxes_);
CHECK_EQ(raw_box_tensor->dims->data[2], num_coords_);
CHECK_EQ(raw_score_tensor->dims->size, 3);
CHECK_EQ(raw_score_tensor->dims->data[0], 1);
CHECK_EQ(raw_score_tensor->dims->data[1], num_boxes_);
CHECK_EQ(raw_score_tensor->dims->data[2], num_classes_);
ABSL_CHECK_EQ(raw_box_tensor->dims->size, 3);
ABSL_CHECK_EQ(raw_box_tensor->dims->data[0], 1);
ABSL_CHECK_EQ(raw_box_tensor->dims->data[1], num_boxes_);
ABSL_CHECK_EQ(raw_box_tensor->dims->data[2], num_coords_);
ABSL_CHECK_EQ(raw_score_tensor->dims->size, 3);
ABSL_CHECK_EQ(raw_score_tensor->dims->data[0], 1);
ABSL_CHECK_EQ(raw_score_tensor->dims->data[1], num_boxes_);
ABSL_CHECK_EQ(raw_score_tensor->dims->data[2], num_classes_);
const float* raw_boxes = raw_box_tensor->data.f;
const float* raw_scores = raw_score_tensor->data.f;
@@ -303,13 +305,13 @@ absl::Status TfLiteTensorsToDetectionsCalculator::ProcessCPU(
if (!anchors_init_) {
if (input_tensors.size() == kNumInputTensorsWithAnchors) {
const TfLiteTensor* anchor_tensor = &input_tensors[2];
CHECK_EQ(anchor_tensor->dims->size, 2);
CHECK_EQ(anchor_tensor->dims->data[0], num_boxes_);
CHECK_EQ(anchor_tensor->dims->data[1], kNumCoordsPerBox);
ABSL_CHECK_EQ(anchor_tensor->dims->size, 2);
ABSL_CHECK_EQ(anchor_tensor->dims->data[0], num_boxes_);
ABSL_CHECK_EQ(anchor_tensor->dims->data[1], kNumCoordsPerBox);
const float* raw_anchors = anchor_tensor->data.f;
ConvertRawValuesToAnchors(raw_anchors, num_boxes_, &anchors_);
} else if (side_packet_anchors_) {
CHECK(!cc->InputSidePackets().Tag("ANCHORS").IsEmpty());
ABSL_CHECK(!cc->InputSidePackets().Tag("ANCHORS").IsEmpty());
anchors_ =
cc->InputSidePackets().Tag("ANCHORS").Get<std::vector<Anchor>>();
} else {
@@ -409,7 +411,7 @@ absl::Status TfLiteTensorsToDetectionsCalculator::ProcessGPU(
CopyBuffer(input_tensors[1], gpu_data_->raw_scores_buffer));
if (!anchors_init_) {
if (side_packet_anchors_) {
CHECK(!cc->InputSidePackets().Tag("ANCHORS").IsEmpty());
ABSL_CHECK(!cc->InputSidePackets().Tag("ANCHORS").IsEmpty());
const auto& anchors =
cc->InputSidePackets().Tag("ANCHORS").Get<std::vector<Anchor>>();
std::vector<float> raw_anchors(num_boxes_ * kNumCoordsPerBox);
@@ -417,7 +419,7 @@ absl::Status TfLiteTensorsToDetectionsCalculator::ProcessGPU(
MP_RETURN_IF_ERROR(gpu_data_->raw_anchors_buffer.Write<float>(
absl::MakeSpan(raw_anchors)));
} else {
CHECK_EQ(input_tensors.size(), kNumInputTensorsWithAnchors);
ABSL_CHECK_EQ(input_tensors.size(), kNumInputTensorsWithAnchors);
MP_RETURN_IF_ERROR(
CopyBuffer(input_tensors[2], gpu_data_->raw_anchors_buffer));
}
@@ -477,7 +479,7 @@ absl::Status TfLiteTensorsToDetectionsCalculator::ProcessGPU(
commandBuffer:[gpu_helper_ commandBuffer]];
if (!anchors_init_) {
if (side_packet_anchors_) {
CHECK(!cc->InputSidePackets().Tag("ANCHORS").IsEmpty());
ABSL_CHECK(!cc->InputSidePackets().Tag("ANCHORS").IsEmpty());
const auto& anchors =
cc->InputSidePackets().Tag("ANCHORS").Get<std::vector<Anchor>>();
std::vector<float> raw_anchors(num_boxes_ * kNumCoordsPerBox);
@@ -541,7 +543,7 @@ absl::Status TfLiteTensorsToDetectionsCalculator::ProcessGPU(
output_detections));
#else
LOG(ERROR) << "GPU input on non-Android not supported yet.";
ABSL_LOG(ERROR) << "GPU input on non-Android not supported yet.";
#endif // MEDIAPIPE_TFLITE_GL_INFERENCE
return absl::OkStatus();
}
@@ -567,12 +569,12 @@ absl::Status TfLiteTensorsToDetectionsCalculator::LoadOptions(
num_coords_ = options_.num_coords();
// Currently only support 2D when num_values_per_keypoint equals to 2.
CHECK_EQ(options_.num_values_per_keypoint(), 2);
ABSL_CHECK_EQ(options_.num_values_per_keypoint(), 2);
// Check if the output size is equal to the requested boxes and keypoints.
CHECK_EQ(options_.num_keypoints() * options_.num_values_per_keypoint() +
kNumCoordsPerBox,
num_coords_);
ABSL_CHECK_EQ(options_.num_keypoints() * options_.num_values_per_keypoint() +
kNumCoordsPerBox,
num_coords_);
for (int i = 0; i < options_.ignore_classes_size(); ++i) {
ignore_classes_.insert(options_.ignore_classes(i));
@@ -897,10 +899,11 @@ void main() {
int max_wg_size; // typically <= 1024
glGetIntegeri_v(GL_MAX_COMPUTE_WORK_GROUP_SIZE, 1,
&max_wg_size); // y-dim
CHECK_LT(num_classes_, max_wg_size)
ABSL_CHECK_LT(num_classes_, max_wg_size)
<< "# classes must be < " << max_wg_size;
// TODO support better filtering.
CHECK_LE(ignore_classes_.size(), 1) << "Only ignore class 0 is allowed";
ABSL_CHECK_LE(ignore_classes_.size(), 1)
<< "Only ignore class 0 is allowed";
// Shader program
GlShader score_shader;
@@ -1115,7 +1118,7 @@ kernel void scoreKernel(
ignore_classes_.size() ? 1 : 0);
// TODO support better filtering.
CHECK_LE(ignore_classes_.size(), 1) << "Only ignore class 0 is allowed";
ABSL_CHECK_LE(ignore_classes_.size(), 1) << "Only ignore class 0 is allowed";
{
// Shader program
@@ -1147,7 +1150,8 @@ kernel void scoreKernel(
options:MTLResourceStorageModeShared];
// # filter classes supported is hardware dependent.
int max_wg_size = gpu_data_->score_program.maxTotalThreadsPerThreadgroup;
CHECK_LT(num_classes_, max_wg_size) << "# classes must be <" << max_wg_size;
ABSL_CHECK_LT(num_classes_, max_wg_size)
<< "# classes must be <" << max_wg_size;
}
#endif // MEDIAPIPE_TFLITE_GL_INFERENCE
@@ -12,6 +12,7 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "absl/log/absl_check.h"
#include "mediapipe/calculators/tflite/tflite_tensors_to_landmarks_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/formats/landmark.pb.h"
@@ -199,7 +200,7 @@ absl::Status TfLiteTensorsToLandmarksCalculator::Process(
num_values *= raw_tensor->dims->data[i];
}
const int num_dimensions = num_values / num_landmarks_;
CHECK_GT(num_dimensions, 0);
ABSL_CHECK_GT(num_dimensions, 0);
const float* raw_landmarks = raw_tensor->data.f;
+13 -3
View File
@@ -183,9 +183,9 @@ cc_library(
"//mediapipe/framework:calculator_options_cc_proto",
"//mediapipe/framework:timestamp",
"//mediapipe/framework/deps:clock",
"//mediapipe/framework/port:logging",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_log",
"@com_google_absl//absl/strings",
"@com_google_absl//absl/time",
],
@@ -248,11 +248,12 @@ cc_library(
":annotation_overlay_calculator_cc_proto",
"//mediapipe/framework:calculator_framework",
"//mediapipe/framework:calculator_options_cc_proto",
"//mediapipe/framework/formats:image",
"//mediapipe/framework/formats:image_format_cc_proto",
"//mediapipe/framework/formats:image_frame",
"//mediapipe/framework/formats:image_frame_opencv",
"//mediapipe/framework/formats:image_opencv",
"//mediapipe/framework/formats:video_stream_header",
"//mediapipe/framework/port:logging",
"//mediapipe/framework/port:opencv_core",
"//mediapipe/framework/port:opencv_imgproc",
"//mediapipe/framework/port:status",
@@ -260,6 +261,7 @@ cc_library(
"//mediapipe/util:annotation_renderer",
"//mediapipe/util:color_cc_proto",
"//mediapipe/util:render_data_cc_proto",
"@com_google_absl//absl/log:absl_log",
"@com_google_absl//absl/strings",
] + select({
"//mediapipe/gpu:disable_gpu": [],
@@ -267,6 +269,7 @@ cc_library(
"//mediapipe/gpu:gl_calculator_helper",
"//mediapipe/gpu:gl_simple_shaders",
"//mediapipe/gpu:gpu_buffer",
"//mediapipe/gpu:gpu_buffer_format",
"//mediapipe/gpu:shader_util",
],
}),
@@ -374,9 +377,10 @@ cc_library(
"//mediapipe/framework/formats:detection_cc_proto",
"//mediapipe/framework/formats:image_frame",
"//mediapipe/framework/formats:location",
"//mediapipe/framework/port:logging",
"//mediapipe/framework/port:rectangle",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/log:absl_log",
],
alwayslink = 1,
)
@@ -675,6 +679,7 @@ cc_library(
"//mediapipe/framework/port:ret_check",
"//mediapipe/util:color_cc_proto",
"//mediapipe/util:render_data_cc_proto",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/memory",
"@com_google_absl//absl/strings",
],
@@ -731,6 +736,7 @@ cc_library(
"//mediapipe/framework/port:statusor",
"//mediapipe/util:color_cc_proto",
"//mediapipe/util:render_data_cc_proto",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/strings",
],
alwayslink = 1,
@@ -746,6 +752,7 @@ cc_library(
"//mediapipe/framework/port:ret_check",
"//mediapipe/util:color_cc_proto",
"//mediapipe/util:render_data_cc_proto",
"@com_google_absl//absl/log:absl_check",
],
alwayslink = 1,
)
@@ -1149,6 +1156,7 @@ cc_library(
"//mediapipe/framework/port:file_helpers",
"//mediapipe/framework/port:ret_check",
"//mediapipe/framework/port:status",
"@com_google_absl//absl/log:absl_log",
],
alwayslink = 1,
)
@@ -1209,6 +1217,7 @@ cc_library(
"//mediapipe/framework/port:rectangle",
"//mediapipe/framework/port:status",
"//mediapipe/util:rectangle_util",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/memory",
],
alwayslink = 1,
@@ -1480,6 +1489,7 @@ cc_library(
"//mediapipe/framework/formats:landmark_cc_proto",
"//mediapipe/framework/port:core_proto",
"//mediapipe/framework/port:ret_check",
"@com_google_absl//absl/log:absl_check",
"@com_google_absl//absl/memory",
],
alwayslink = 1,
@@ -14,15 +14,17 @@
#include <memory>
#include "absl/log/absl_log.h"
#include "absl/strings/str_cat.h"
#include "mediapipe/calculators/util/annotation_overlay_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
#include "mediapipe/framework/calculator_options.pb.h"
#include "mediapipe/framework/formats/image.h"
#include "mediapipe/framework/formats/image_format.pb.h"
#include "mediapipe/framework/formats/image_frame.h"
#include "mediapipe/framework/formats/image_frame_opencv.h"
#include "mediapipe/framework/formats/image_opencv.h"
#include "mediapipe/framework/formats/video_stream_header.h"
#include "mediapipe/framework/port/logging.h"
#include "mediapipe/framework/port/opencv_core_inc.h"
#include "mediapipe/framework/port/opencv_imgproc_inc.h"
#include "mediapipe/framework/port/status.h"
@@ -35,6 +37,7 @@
#include "mediapipe/gpu/gl_calculator_helper.h"
#include "mediapipe/gpu/gl_simple_shaders.h"
#include "mediapipe/gpu/gpu_buffer.h"
#include "mediapipe/gpu/gpu_buffer_format.h"
#include "mediapipe/gpu/shader_util.h"
#endif // !MEDIAPIPE_DISABLE_GPU
@@ -45,6 +48,7 @@ namespace {
constexpr char kVectorTag[] = "VECTOR";
constexpr char kGpuBufferTag[] = "IMAGE_GPU";
constexpr char kImageFrameTag[] = "IMAGE";
constexpr char kImageTag[] = "UIMAGE"; // Universal Image
enum { ATTRIB_VERTEX, ATTRIB_TEXTURE_POSITION, NUM_ATTRIBUTES };
@@ -57,13 +61,16 @@ size_t RoundUp(size_t n, size_t m) { return ((n + m - 1) / m) * m; } // NOLINT
constexpr uchar kAnnotationBackgroundColor = 2; // Grayscale value.
// Future Image type.
inline bool HasImageTag(mediapipe::CalculatorContext* cc) { return false; }
inline bool HasImageTag(mediapipe::CalculatorContext* cc) {
return cc->Inputs().HasTag(kImageTag);
}
} // namespace
// A calculator for rendering data on images.
//
// Inputs:
// 1. IMAGE or IMAGE_GPU (optional): An ImageFrame (or GpuBuffer),
// or UIMAGE (an Image).
// containing the input image.
// If output is CPU, and input isn't provided, the renderer creates a
// blank canvas with the width, height and color provided in the options.
@@ -76,6 +83,7 @@ inline bool HasImageTag(mediapipe::CalculatorContext* cc) { return false; }
//
// Output:
// 1. IMAGE or IMAGE_GPU: A rendered ImageFrame (or GpuBuffer),
// or UIMAGE (an Image).
// Note: Output types should match their corresponding input stream type.
//
// For CPU input frames, only SRGBA, SRGB and GRAY8 format are supported. The
@@ -135,6 +143,9 @@ class AnnotationOverlayCalculator : public CalculatorBase {
absl::Status CreateRenderTargetCpu(CalculatorContext* cc,
std::unique_ptr<cv::Mat>& image_mat,
ImageFormat::Format* target_format);
absl::Status CreateRenderTargetCpuImage(CalculatorContext* cc,
std::unique_ptr<cv::Mat>& image_mat,
ImageFormat::Format* target_format);
template <typename Type, const char* Tag>
absl::Status CreateRenderTargetGpu(CalculatorContext* cc,
std::unique_ptr<cv::Mat>& image_mat);
@@ -176,14 +187,14 @@ absl::Status AnnotationOverlayCalculator::GetContract(CalculatorContract* cc) {
bool use_gpu = false;
if (cc->Inputs().HasTag(kImageFrameTag) &&
cc->Inputs().HasTag(kGpuBufferTag)) {
return absl::InternalError("Cannot have multiple input images.");
}
if (cc->Inputs().HasTag(kGpuBufferTag) !=
cc->Outputs().HasTag(kGpuBufferTag)) {
return absl::InternalError("GPU output must have GPU input.");
}
RET_CHECK(cc->Inputs().HasTag(kImageFrameTag) +
cc->Inputs().HasTag(kGpuBufferTag) +
cc->Inputs().HasTag(kImageTag) <=
1);
RET_CHECK(cc->Outputs().HasTag(kImageFrameTag) +
cc->Outputs().HasTag(kGpuBufferTag) +
cc->Outputs().HasTag(kImageTag) ==
1);
// Input image to render onto copy of. Should be same type as output.
#if !MEDIAPIPE_DISABLE_GPU
@@ -198,6 +209,14 @@ absl::Status AnnotationOverlayCalculator::GetContract(CalculatorContract* cc) {
RET_CHECK(cc->Outputs().HasTag(kImageFrameTag));
}
if (cc->Inputs().HasTag(kImageTag)) {
cc->Inputs().Tag(kImageTag).Set<mediapipe::Image>();
RET_CHECK(cc->Outputs().HasTag(kImageTag));
#if !MEDIAPIPE_DISABLE_GPU
use_gpu = true; // Prepare GPU resources because images can come in on GPU.
#endif
}
// Data streams to render.
for (CollectionItemId id = cc->Inputs().BeginId(); id < cc->Inputs().EndId();
++id) {
@@ -220,6 +239,9 @@ absl::Status AnnotationOverlayCalculator::GetContract(CalculatorContract* cc) {
if (cc->Outputs().HasTag(kImageFrameTag)) {
cc->Outputs().Tag(kImageFrameTag).Set<ImageFrame>();
}
if (cc->Outputs().HasTag(kImageTag)) {
cc->Outputs().Tag(kImageTag).Set<mediapipe::Image>();
}
if (use_gpu) {
#if !MEDIAPIPE_DISABLE_GPU
@@ -252,9 +274,14 @@ absl::Status AnnotationOverlayCalculator::Open(CalculatorContext* cc) {
renderer_ = absl::make_unique<AnnotationRenderer>();
renderer_->SetFlipTextVertically(options_.flip_text_vertically());
if (use_gpu_) renderer_->SetScaleFactor(options_.gpu_scale_factor());
if (renderer_->GetScaleFactor() < 1.0 && HasImageTag(cc))
ABSL_LOG(WARNING)
<< "Annotation scale factor only supports GPU backed Image.";
// Set the output header based on the input header (if present).
const char* tag = use_gpu_ ? kGpuBufferTag : kImageFrameTag;
const char* tag = HasImageTag(cc) ? kImageTag
: use_gpu_ ? kGpuBufferTag
: kImageFrameTag;
if (image_frame_available_ && !cc->Inputs().Tag(tag).Header().IsEmpty()) {
const auto& input_header =
cc->Inputs().Tag(tag).Header().Get<VideoHeader>();
@@ -280,6 +307,12 @@ absl::Status AnnotationOverlayCalculator::Process(CalculatorContext* cc) {
cc->Inputs().Tag(kImageFrameTag).IsEmpty()) {
return absl::OkStatus();
}
if (cc->Inputs().HasTag(kImageTag) && cc->Inputs().Tag(kImageTag).IsEmpty()) {
return absl::OkStatus();
}
if (HasImageTag(cc)) {
use_gpu_ = cc->Inputs().Tag(kImageTag).Get<mediapipe::Image>().UsesGpu();
}
// Initialize render target, drawn with OpenCV.
std::unique_ptr<cv::Mat> image_mat;
@@ -289,10 +322,17 @@ absl::Status AnnotationOverlayCalculator::Process(CalculatorContext* cc) {
if (!gpu_initialized_) {
MP_RETURN_IF_ERROR(
gpu_helper_.RunInGlContext([this, cc]() -> absl::Status {
if (HasImageTag(cc)) {
return GlSetup<mediapipe::Image, kImageTag>(cc);
}
return GlSetup<mediapipe::GpuBuffer, kGpuBufferTag>(cc);
}));
gpu_initialized_ = true;
}
if (HasImageTag(cc)) {
MP_RETURN_IF_ERROR(
(CreateRenderTargetGpu<mediapipe::Image, kImageTag>(cc, image_mat)));
}
if (cc->Inputs().HasTag(kGpuBufferTag)) {
MP_RETURN_IF_ERROR(
(CreateRenderTargetGpu<mediapipe::GpuBuffer, kGpuBufferTag>(
@@ -300,6 +340,10 @@ absl::Status AnnotationOverlayCalculator::Process(CalculatorContext* cc) {
}
#endif // !MEDIAPIPE_DISABLE_GPU
} else {
if (cc->Outputs().HasTag(kImageTag)) {
MP_RETURN_IF_ERROR(
CreateRenderTargetCpuImage(cc, image_mat, &target_format));
}
if (cc->Outputs().HasTag(kImageFrameTag)) {
MP_RETURN_IF_ERROR(CreateRenderTargetCpu(cc, image_mat, &target_format));
}
@@ -339,6 +383,9 @@ absl::Status AnnotationOverlayCalculator::Process(CalculatorContext* cc) {
uchar* image_mat_ptr = image_mat->data;
MP_RETURN_IF_ERROR(
gpu_helper_.RunInGlContext([this, cc, image_mat_ptr]() -> absl::Status {
if (HasImageTag(cc)) {
return RenderToGpu<mediapipe::Image, kImageTag>(cc, image_mat_ptr);
}
return RenderToGpu<mediapipe::GpuBuffer, kGpuBufferTag>(
cc, image_mat_ptr);
}));
@@ -381,6 +428,10 @@ absl::Status AnnotationOverlayCalculator::RenderToCpu(
ImageFrame::kDefaultAlignmentBoundary);
#endif // !MEDIAPIPE_DISABLE_GPU
if (HasImageTag(cc)) {
auto out = std::make_unique<mediapipe::Image>(std::move(output_frame));
cc->Outputs().Tag(kImageTag).Add(out.release(), cc->InputTimestamp());
}
if (cc->Outputs().HasTag(kImageFrameTag)) {
cc->Outputs()
.Tag(kImageFrameTag)
@@ -399,7 +450,8 @@ absl::Status AnnotationOverlayCalculator::RenderToGpu(CalculatorContext* cc,
auto input_texture = gpu_helper_.CreateSourceTexture(input_frame);
auto output_texture = gpu_helper_.CreateDestinationTexture(
width_, height_, mediapipe::GpuBufferFormat::kBGRA32);
input_texture.width(), input_texture.height(),
mediapipe::GpuBufferFormat::kBGRA32);
// Upload render target to GPU.
{
@@ -428,7 +480,7 @@ absl::Status AnnotationOverlayCalculator::RenderToGpu(CalculatorContext* cc,
}
// Send out blended image as GPU packet.
auto output_frame = output_texture.GetFrame<Type>();
auto output_frame = output_texture.template GetFrame<Type>();
cc->Outputs().Tag(Tag).Add(output_frame.release(), cc->InputTimestamp());
// Cleanup
@@ -487,6 +539,54 @@ absl::Status AnnotationOverlayCalculator::CreateRenderTargetCpu(
return absl::OkStatus();
}
absl::Status AnnotationOverlayCalculator::CreateRenderTargetCpuImage(
CalculatorContext* cc, std::unique_ptr<cv::Mat>& image_mat,
ImageFormat::Format* target_format) {
if (image_frame_available_) {
const auto& input_frame =
cc->Inputs().Tag(kImageTag).Get<mediapipe::Image>();
int target_mat_type;
switch (input_frame.image_format()) {
case ImageFormat::SRGBA:
*target_format = ImageFormat::SRGBA;
target_mat_type = CV_8UC4;
break;
case ImageFormat::SRGB:
*target_format = ImageFormat::SRGB;
target_mat_type = CV_8UC3;
break;
case ImageFormat::GRAY8:
*target_format = ImageFormat::SRGB;
target_mat_type = CV_8UC3;
break;
default:
return absl::UnknownError("Unexpected image frame format.");
break;
}
image_mat = absl::make_unique<cv::Mat>(
input_frame.height(), input_frame.width(), target_mat_type);
auto input_mat = formats::MatView(&input_frame);
if (input_frame.image_format() == ImageFormat::GRAY8) {
cv::Mat rgb_mat;
cv::cvtColor(*input_mat, rgb_mat, cv::COLOR_GRAY2RGB);
rgb_mat.copyTo(*image_mat);
} else {
input_mat->copyTo(*image_mat);
}
} else {
image_mat = absl::make_unique<cv::Mat>(
options_.canvas_height_px(), options_.canvas_width_px(), CV_8UC3,
cv::Scalar(options_.canvas_color().r(), options_.canvas_color().g(),
options_.canvas_color().b()));
*target_format = ImageFormat::SRGB;
}
return absl::OkStatus();
}
template <typename Type, const char* Tag>
absl::Status AnnotationOverlayCalculator::CreateRenderTargetGpu(
CalculatorContext* cc, std::unique_ptr<cv::Mat>& image_mat) {
@@ -18,6 +18,7 @@
#include <memory>
#include <vector>
#include "absl/log/absl_check.h"
#include "absl/memory/memory.h"
#include "mediapipe/calculators/util/association_calculator.pb.h"
#include "mediapipe/framework/calculator_context.h"
@@ -72,7 +73,7 @@ class AssociationCalculator : public CalculatorBase {
prev_input_stream_id_ = cc->Inputs().GetId("PREV", 0);
}
options_ = cc->Options<::mediapipe::AssociationCalculatorOptions>();
CHECK_GE(options_.min_similarity_threshold(), 0);
ABSL_CHECK_GE(options_.min_similarity_threshold(), 0);
return absl::OkStatus();
}
@@ -19,6 +19,7 @@
#include "mediapipe/framework/port/integral_types.h"
#include "mediapipe/framework/port/proto_ns.h"
#include "mediapipe/framework/port/status.h"
#include "mediapipe/framework/port/status_macros.h"
#include "mediapipe/util/label_map.pb.h"
#include "mediapipe/util/resource_util.h"
@@ -85,7 +86,8 @@ absl::Status DetectionLabelIdToTextCalculator::Open(CalculatorContext* cc) {
ASSIGN_OR_RETURN(string_path,
PathToResourceAsFile(options.label_map_path()));
std::string label_map_string;
MP_RETURN_IF_ERROR(file::GetContents(string_path, &label_map_string));
MP_RETURN_IF_ERROR(
mediapipe::GetResourceContents(string_path, &label_map_string));
std::istringstream stream(label_map_string);
std::string line;
@@ -12,6 +12,7 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#include "absl/log/absl_check.h"
#include "absl/memory/memory.h"
#include "absl/strings/str_cat.h"
#include "absl/strings/str_join.h"
@@ -233,13 +234,13 @@ void DetectionsToRenderDataCalculator::AddLabels(
const Detection& detection,
const DetectionsToRenderDataCalculatorOptions& options,
float text_line_height, RenderData* render_data) {
CHECK(detection.label().empty() || detection.label_id().empty() ||
detection.label_size() == detection.label_id_size())
ABSL_CHECK(detection.label().empty() || detection.label_id().empty() ||
detection.label_size() == detection.label_id_size())
<< "String or integer labels should be of same size. Or only one of them "
"is present.";
const auto num_labels =
std::max(detection.label_size(), detection.label_id_size());
CHECK_EQ(detection.score_size(), num_labels)
ABSL_CHECK_EQ(detection.score_size(), num_labels)
<< "Number of scores and labels should match for detection.";
// Extracts all "label(_id),score" for the detection.
@@ -361,9 +362,9 @@ void DetectionsToRenderDataCalculator::AddDetectionToRenderData(
const Detection& detection,
const DetectionsToRenderDataCalculatorOptions& options,
RenderData* render_data) {
CHECK(detection.location_data().format() == LocationData::BOUNDING_BOX ||
detection.location_data().format() ==
LocationData::RELATIVE_BOUNDING_BOX)
ABSL_CHECK(detection.location_data().format() == LocationData::BOUNDING_BOX ||
detection.location_data().format() ==
LocationData::RELATIVE_BOUNDING_BOX)
<< "Only Detection with formats of BOUNDING_BOX or RELATIVE_BOUNDING_BOX "
"are supported.";
double text_line_height;
@@ -19,6 +19,7 @@
#include <string>
#include <vector>
#include "absl/log/absl_check.h"
#include "absl/strings/str_cat.h"
#include "mediapipe/calculators/util/labels_to_render_data_calculator.pb.h"
#include "mediapipe/framework/calculator_framework.h"
@@ -114,7 +115,8 @@ absl::Status LabelsToRenderDataCalculator::Process(CalculatorContext* cc) {
video_height_ = video_header.height;
return absl::OkStatus();
} else {
CHECK_EQ(options_.location(), LabelsToRenderDataCalculatorOptions::TOP_LEFT)
ABSL_CHECK_EQ(options_.location(),
LabelsToRenderDataCalculatorOptions::TOP_LEFT)
<< "Only TOP_LEFT is supported without VIDEO_PRESTREAM.";
}
@@ -144,7 +146,7 @@ absl::Status LabelsToRenderDataCalculator::Process(CalculatorContext* cc) {
if (cc->Inputs().HasTag(kScoresTag)) {
std::vector<float> score_vector =
cc->Inputs().Tag(kScoresTag).Get<std::vector<float>>();
CHECK_EQ(label_vector.size(), score_vector.size());
ABSL_CHECK_EQ(label_vector.size(), score_vector.size());
scores.resize(label_vector.size());
for (int i = 0; i < label_vector.size(); ++i) {
scores[i] = score_vector[i];
@@ -18,6 +18,7 @@
#include <set>
#include <utility>
#include "absl/log/absl_check.h"
#include "absl/memory/memory.h"
#include "mediapipe/calculators/util/landmarks_refinement_calculator.pb.h"
#include "mediapipe/framework/api2/node.h"
@@ -102,7 +103,8 @@ void RefineZ(
->set_z(z_average);
}
} else {
CHECK(false) << "Z refinement is either not specified or not supported";
ABSL_CHECK(false)
<< "Z refinement is either not specified or not supported";
}
}

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