Compare commits
| Author | SHA1 | Date | |
|---|---|---|---|
 Sebastian SchmidtandGitHub
|
7d05709f62 |
@@ -87,9 +87,6 @@ build:ios_fat --config=ios
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build:ios_fat --ios_multi_cpus=armv7,arm64
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build:ios_fat --watchos_cpus=armv7k
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build:ios_sim_fat --config=ios
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build:ios_sim_fat --ios_multi_cpus=x86_64,sim_arm64
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build:darwin_x86_64 --apple_platform_type=macos
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build:darwin_x86_64 --macos_minimum_os=10.12
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build:darwin_x86_64 --cpu=darwin_x86_64
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@@ -0,0 +1,34 @@
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# Copyright 2021 The MediaPipe Authors.
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||||
#
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||||
# Licensed under the Apache License, Version 2.0 (the "License");
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||||
# you may not use this file except in compliance with the License.
|
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
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||||
# Unless required by applicable law or agreed to in writing, software
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||||
# 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.
|
||||
# ============================================================================
|
||||
#
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||||
# This file was assembled from multiple pieces, whose use is documented
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# throughout. Please refer to the TensorFlow dockerfiles documentation
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# for more information.
|
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|
||||
# Number of days of inactivity before an Issue or Pull Request becomes stale
|
||||
daysUntilStale: 7
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||||
# Number of days of inactivity before a stale Issue or Pull Request is closed
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||||
daysUntilClose: 7
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||||
# Only issues or pull requests with all of these labels are checked if stale. Defaults to `[]` (disabled)
|
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onlyLabels:
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- stat:awaiting response
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||||
# Comment to post when marking as stale. Set to `false` to disable
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||||
markComment: >
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||||
This issue has been automatically marked as stale because it has not had
|
||||
recent activity. It will be closed if no further activity occurs. Thank you.
|
||||
# Comment to post when removing the stale label. Set to `false` to disable
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||||
unmarkComment: false
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||||
closeComment: >
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||||
Closing as stale. Please reopen if you'd like to work on this further.
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||||
@@ -1,66 +0,0 @@
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# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
|
||||
#
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||||
# 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.
|
||||
# ==============================================================================
|
||||
|
||||
# This workflow alerts and then closes the stale issues/PRs after specific time
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# You can adjust the behavior by modifying this file.
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||||
# For more information, see:
|
||||
# https://github.com/actions/stale
|
||||
|
||||
name: 'Close stale issues and PRs'
|
||||
"on":
|
||||
schedule:
|
||||
- cron: "30 1 * * *"
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||||
permissions:
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||||
contents: read
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||||
issues: write
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pull-requests: write
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jobs:
|
||||
stale:
|
||||
runs-on: ubuntu-latest
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||||
steps:
|
||||
- uses: 'actions/stale@v7'
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||||
with:
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||||
# Comma separated list of labels that can be assigned to issues to exclude them from being marked as stale.
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||||
exempt-issue-labels: 'override-stale'
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||||
# Comma separated list of labels that can be assigned to PRs to exclude them from being marked as stale.
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||||
exempt-pr-labels: "override-stale"
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||||
# Limit the No. of API calls in one run default value is 30.
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operations-per-run: 500
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# Prevent to remove stale label when PRs or issues are updated.
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||||
remove-stale-when-updated: false
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||||
# comment on issue if not active for more then 7 days.
|
||||
stale-issue-message: 'This issue has been marked stale because it has no recent activity since 7 days. It will be closed if no further activity occurs. Thank you.'
|
||||
# comment on PR if not active for more then 14 days.
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||||
stale-pr-message: 'This PR has been marked stale because it has no recent activity since 14 days. It will be closed if no further activity occurs. Thank you.'
|
||||
# comment on issue if stale for more then 7 days.
|
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close-issue-message: This issue was closed due to lack of activity after being marked stale for past 7 days.
|
||||
# comment on PR if stale for more then 14 days.
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||||
close-pr-message: This PR was closed due to lack of activity after being marked stale for past 14 days.
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||||
# Number of days of inactivity before an Issue Request becomes stale
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||||
days-before-issue-stale: 7
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||||
# Number of days of inactivity before a stale Issue is closed
|
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days-before-issue-close: 7
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# reason for closed the issue default value is not_planned
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close-issue-reason: completed
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# Number of days of inactivity before a stale PR is closed
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||||
days-before-pr-close: 14
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||||
# Number of days of inactivity before an PR Request becomes stale
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days-before-pr-stale: 14
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||||
# Check for label to stale or close the issue/PR
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||||
any-of-labels: 'stat:awaiting response'
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# override stale to stalled for PR
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stale-pr-label: 'stale'
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# override stale to stalled for Issue
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stale-issue-label: "stale"
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@@ -4,6 +4,8 @@ title: Home
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||||
nav_order: 1
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||||
---
|
||||
|
||||
|
||||
|
||||
----
|
||||
|
||||
**Attention:** *Thanks for your interest in MediaPipe! We have moved to
|
||||
@@ -12,111 +14,86 @@ as the primary developer documentation site for MediaPipe as of April 3, 2023.*
|
||||
|
||||
*This notice and web page will be removed on June 1, 2023.*
|
||||
|
||||
|
||||
----
|
||||
|
||||
**Attention**: MediaPipe Solutions Preview is an early release. [Learn
|
||||
more](https://developers.google.com/mediapipe/solutions/about#notice).
|
||||
<br><br><br><br><br><br><br><br><br><br>
|
||||
<br><br><br><br><br><br><br><br><br><br>
|
||||
<br><br><br><br><br><br><br><br><br><br>
|
||||
|
||||
**On-device machine learning for everyone**
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
Delight your customers with innovative machine learning features. MediaPipe
|
||||
contains everything that you need to customize and deploy to mobile (Android,
|
||||
iOS), web, desktop, edge devices, and IoT, effortlessly.
|
||||
## Live ML anywhere
|
||||
|
||||
* [See demos](https://goo.gle/mediapipe-studio)
|
||||
* [Learn more](https://developers.google.com/mediapipe/solutions)
|
||||
[MediaPipe](https://google.github.io/mediapipe/) offers cross-platform, customizable
|
||||
ML solutions for live and streaming media.
|
||||
|
||||
## Get started
|
||||
 | 
|
||||
:------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------:
|
||||
***End-to-End acceleration***: *Built-in fast ML inference and processing accelerated even on common hardware* | ***Build once, deploy anywhere***: *Unified solution works across Android, iOS, desktop/cloud, web and IoT*
|
||||
 | 
|
||||
***Ready-to-use solutions***: *Cutting-edge ML solutions demonstrating full power of the framework* | ***Free and open source***: *Framework and solutions both under Apache 2.0, fully extensible and customizable*
|
||||
|
||||
You can get started with MediaPipe Solutions by by checking out any of the
|
||||
developer guides for
|
||||
[vision](https://developers.google.com/mediapipe/solutions/vision/object_detector),
|
||||
[text](https://developers.google.com/mediapipe/solutions/text/text_classifier),
|
||||
and
|
||||
[audio](https://developers.google.com/mediapipe/solutions/audio/audio_classifier)
|
||||
tasks. If you need help setting up a development environment for use with
|
||||
MediaPipe Tasks, check out the setup guides for
|
||||
[Android](https://developers.google.com/mediapipe/solutions/setup_android), [web
|
||||
apps](https://developers.google.com/mediapipe/solutions/setup_web), and
|
||||
[Python](https://developers.google.com/mediapipe/solutions/setup_python).
|
||||
----
|
||||
|
||||
## Solutions
|
||||
## ML solutions in MediaPipe
|
||||
|
||||
MediaPipe Solutions provides a suite of libraries and tools for you to quickly
|
||||
apply artificial intelligence (AI) and machine learning (ML) techniques in your
|
||||
applications. You can plug these solutions into your applications immediately,
|
||||
customize them to your needs, and use them across multiple development
|
||||
platforms. MediaPipe Solutions is part of the MediaPipe [open source
|
||||
project](https://github.com/google/mediapipe), so you can further customize the
|
||||
solutions code to meet your application needs.
|
||||
Face Detection | Face Mesh | Iris | Hands | Pose | Holistic
|
||||
:----------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------: | :------:
|
||||
[](https://google.github.io/mediapipe/solutions/face_detection) | [](https://google.github.io/mediapipe/solutions/face_mesh) | [](https://google.github.io/mediapipe/solutions/iris) | [](https://google.github.io/mediapipe/solutions/hands) | [](https://google.github.io/mediapipe/solutions/pose) | [](https://google.github.io/mediapipe/solutions/holistic)
|
||||
|
||||
These libraries and resources provide the core functionality for each MediaPipe
|
||||
Solution:
|
||||
Hair Segmentation | Object Detection | Box Tracking | Instant Motion Tracking | Objectron | KNIFT
|
||||
:-------------------------------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------: | :---:
|
||||
[](https://google.github.io/mediapipe/solutions/hair_segmentation) | [](https://google.github.io/mediapipe/solutions/object_detection) | [](https://google.github.io/mediapipe/solutions/box_tracking) | [](https://google.github.io/mediapipe/solutions/instant_motion_tracking) | [](https://google.github.io/mediapipe/solutions/objectron) | [](https://google.github.io/mediapipe/solutions/knift)
|
||||
|
||||
* **MediaPipe Tasks**: Cross-platform APIs and libraries for deploying
|
||||
solutions. [Learn
|
||||
more](https://developers.google.com/mediapipe/solutions/tasks).
|
||||
* **MediaPipe models**: Pre-trained, ready-to-run models for use with each
|
||||
solution.
|
||||
<!-- []() in the first cell is needed to preserve table formatting in GitHub Pages. -->
|
||||
<!-- Whenever this table is updated, paste a copy to solutions/solutions.md. -->
|
||||
|
||||
These tools let you customize and evaluate solutions:
|
||||
[]() | [Android](https://google.github.io/mediapipe/getting_started/android) | [iOS](https://google.github.io/mediapipe/getting_started/ios) | [C++](https://google.github.io/mediapipe/getting_started/cpp) | [Python](https://google.github.io/mediapipe/getting_started/python) | [JS](https://google.github.io/mediapipe/getting_started/javascript) | [Coral](https://github.com/google/mediapipe/tree/master/mediapipe/examples/coral/README.md)
|
||||
:---------------------------------------------------------------------------------------- | :-------------------------------------------------------------: | :-----------------------------------------------------: | :-----------------------------------------------------: | :-----------------------------------------------------------: | :-----------------------------------------------------------: | :--------------------------------------------------------------------:
|
||||
[Face Detection](https://google.github.io/mediapipe/solutions/face_detection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅
|
||||
[Face Mesh](https://google.github.io/mediapipe/solutions/face_mesh) | ✅ | ✅ | ✅ | ✅ | ✅ |
|
||||
[Iris](https://google.github.io/mediapipe/solutions/iris) | ✅ | ✅ | ✅ | | |
|
||||
[Hands](https://google.github.io/mediapipe/solutions/hands) | ✅ | ✅ | ✅ | ✅ | ✅ |
|
||||
[Pose](https://google.github.io/mediapipe/solutions/pose) | ✅ | ✅ | ✅ | ✅ | ✅ |
|
||||
[Holistic](https://google.github.io/mediapipe/solutions/holistic) | ✅ | ✅ | ✅ | ✅ | ✅ |
|
||||
[Selfie Segmentation](https://google.github.io/mediapipe/solutions/selfie_segmentation) | ✅ | ✅ | ✅ | ✅ | ✅ |
|
||||
[Hair Segmentation](https://google.github.io/mediapipe/solutions/hair_segmentation) | ✅ | | ✅ | | |
|
||||
[Object Detection](https://google.github.io/mediapipe/solutions/object_detection) | ✅ | ✅ | ✅ | | | ✅
|
||||
[Box Tracking](https://google.github.io/mediapipe/solutions/box_tracking) | ✅ | ✅ | ✅ | | |
|
||||
[Instant Motion Tracking](https://google.github.io/mediapipe/solutions/instant_motion_tracking) | ✅ | | | | |
|
||||
[Objectron](https://google.github.io/mediapipe/solutions/objectron) | ✅ | | ✅ | ✅ | ✅ |
|
||||
[KNIFT](https://google.github.io/mediapipe/solutions/knift) | ✅ | | | | |
|
||||
[AutoFlip](https://google.github.io/mediapipe/solutions/autoflip) | | | ✅ | | |
|
||||
[MediaSequence](https://google.github.io/mediapipe/solutions/media_sequence) | | | ✅ | | |
|
||||
[YouTube 8M](https://google.github.io/mediapipe/solutions/youtube_8m) | | | ✅ | | |
|
||||
|
||||
* **MediaPipe Model Maker**: Customize models for solutions with your data.
|
||||
[Learn more](https://developers.google.com/mediapipe/solutions/model_maker).
|
||||
* **MediaPipe Studio**: Visualize, evaluate, and benchmark solutions in your
|
||||
browser. [Learn
|
||||
more](https://developers.google.com/mediapipe/solutions/studio).
|
||||
See also
|
||||
[MediaPipe Models and Model Cards](https://google.github.io/mediapipe/solutions/models)
|
||||
for ML models released in MediaPipe.
|
||||
|
||||
### Legacy solutions
|
||||
## Getting started
|
||||
|
||||
We have ended support for [these MediaPipe Legacy Solutions](https://developers.google.com/mediapipe/solutions/guide#legacy)
|
||||
as of March 1, 2023. All other MediaPipe Legacy Solutions will be upgraded to
|
||||
a new MediaPipe Solution. See the [Solutions guide](https://developers.google.com/mediapipe/solutions/guide#legacy)
|
||||
for details. The [code repository](https://github.com/google/mediapipe/tree/master/mediapipe)
|
||||
and prebuilt binaries for all MediaPipe Legacy Solutions will continue to be
|
||||
provided on an as-is basis.
|
||||
To start using MediaPipe
|
||||
[solutions](https://google.github.io/mediapipe/solutions/solutions) with only a few
|
||||
lines code, see example code and demos in
|
||||
[MediaPipe in Python](https://google.github.io/mediapipe/getting_started/python) and
|
||||
[MediaPipe in JavaScript](https://google.github.io/mediapipe/getting_started/javascript).
|
||||
|
||||
For more on the legacy solutions, see the [documentation](https://github.com/google/mediapipe/tree/master/docs/solutions).
|
||||
To use MediaPipe in C++, Android and iOS, which allow further customization of
|
||||
the [solutions](https://google.github.io/mediapipe/solutions/solutions) as well as
|
||||
building your own, learn how to
|
||||
[install](https://google.github.io/mediapipe/getting_started/install) MediaPipe and
|
||||
start building example applications in
|
||||
[C++](https://google.github.io/mediapipe/getting_started/cpp),
|
||||
[Android](https://google.github.io/mediapipe/getting_started/android) and
|
||||
[iOS](https://google.github.io/mediapipe/getting_started/ios).
|
||||
|
||||
## Framework
|
||||
The source code is hosted in the
|
||||
[MediaPipe Github repository](https://github.com/google/mediapipe), and you can
|
||||
run code search using
|
||||
[Google Open Source Code Search](https://cs.opensource.google/mediapipe/mediapipe).
|
||||
|
||||
To start using MediaPipe Framework, [install MediaPipe
|
||||
Framework](https://developers.google.com/mediapipe/framework/getting_started/install)
|
||||
and start building example applications in C++, Android, and iOS.
|
||||
|
||||
[MediaPipe Framework](https://developers.google.com/mediapipe/framework) is the
|
||||
low-level component used to build efficient on-device machine learning
|
||||
pipelines, similar to the premade MediaPipe Solutions.
|
||||
|
||||
Before using MediaPipe Framework, familiarize yourself with the following key
|
||||
[Framework
|
||||
concepts](https://developers.google.com/mediapipe/framework/framework_concepts/overview.md):
|
||||
|
||||
* [Packets](https://developers.google.com/mediapipe/framework/framework_concepts/packets.md)
|
||||
* [Graphs](https://developers.google.com/mediapipe/framework/framework_concepts/graphs.md)
|
||||
* [Calculators](https://developers.google.com/mediapipe/framework/framework_concepts/calculators.md)
|
||||
|
||||
## Community
|
||||
|
||||
* [Slack community](https://mediapipe.page.link/joinslack) for MediaPipe
|
||||
users.
|
||||
* [Discuss](https://groups.google.com/forum/#!forum/mediapipe) - General
|
||||
community discussion around MediaPipe.
|
||||
* [Awesome MediaPipe](https://mediapipe.page.link/awesome-mediapipe) - A
|
||||
curated list of awesome MediaPipe related frameworks, libraries and
|
||||
software.
|
||||
|
||||
## Contributing
|
||||
|
||||
We welcome contributions. Please follow these
|
||||
[guidelines](https://github.com/google/mediapipe/blob/master/CONTRIBUTING.md).
|
||||
|
||||
We use GitHub issues for tracking requests and bugs. Please post questions to
|
||||
the MediaPipe Stack Overflow with a `mediapipe` tag.
|
||||
|
||||
## Resources
|
||||
|
||||
### Publications
|
||||
## Publications
|
||||
|
||||
* [Bringing artworks to life with AR](https://developers.googleblog.com/2021/07/bringing-artworks-to-life-with-ar.html)
|
||||
in Google Developers Blog
|
||||
@@ -125,8 +102,7 @@ the MediaPipe Stack Overflow with a `mediapipe` tag.
|
||||
* [SignAll SDK: Sign language interface using MediaPipe is now available for
|
||||
developers](https://developers.googleblog.com/2021/04/signall-sdk-sign-language-interface-using-mediapipe-now-available.html)
|
||||
in Google Developers Blog
|
||||
* [MediaPipe Holistic - Simultaneous Face, Hand and Pose Prediction, on
|
||||
Device](https://ai.googleblog.com/2020/12/mediapipe-holistic-simultaneous-face.html)
|
||||
* [MediaPipe Holistic - Simultaneous Face, Hand and Pose Prediction, on Device](https://ai.googleblog.com/2020/12/mediapipe-holistic-simultaneous-face.html)
|
||||
in Google AI Blog
|
||||
* [Background Features in Google Meet, Powered by Web ML](https://ai.googleblog.com/2020/10/background-features-in-google-meet.html)
|
||||
in Google AI Blog
|
||||
@@ -154,6 +130,43 @@ the MediaPipe Stack Overflow with a `mediapipe` tag.
|
||||
in Google AI Blog
|
||||
* [MediaPipe: A Framework for Building Perception Pipelines](https://arxiv.org/abs/1906.08172)
|
||||
|
||||
### Videos
|
||||
## Videos
|
||||
|
||||
* [YouTube Channel](https://www.youtube.com/c/MediaPipe)
|
||||
|
||||
## Events
|
||||
|
||||
* [MediaPipe Seattle Meetup, Google Building Waterside, 13 Feb 2020](https://mediapipe.page.link/seattle2020)
|
||||
* [AI Nextcon 2020, 12-16 Feb 2020, Seattle](http://aisea20.xnextcon.com/)
|
||||
* [MediaPipe Madrid Meetup, 16 Dec 2019](https://www.meetup.com/Madrid-AI-Developers-Group/events/266329088/)
|
||||
* [MediaPipe London Meetup, Google 123 Building, 12 Dec 2019](https://www.meetup.com/London-AI-Tech-Talk/events/266329038)
|
||||
* [ML Conference, Berlin, 11 Dec 2019](https://mlconference.ai/machine-learning-advanced-development/mediapipe-building-real-time-cross-platform-mobile-web-edge-desktop-video-audio-ml-pipelines/)
|
||||
* [MediaPipe Berlin Meetup, Google Berlin, 11 Dec 2019](https://www.meetup.com/Berlin-AI-Tech-Talk/events/266328794/)
|
||||
* [The 3rd Workshop on YouTube-8M Large Scale Video Understanding Workshop,
|
||||
Seoul, Korea ICCV
|
||||
2019](https://research.google.com/youtube8m/workshop2019/index.html)
|
||||
* [AI DevWorld 2019, 10 Oct 2019, San Jose, CA](https://aidevworld.com)
|
||||
* [Google Industry Workshop at ICIP 2019, 24 Sept 2019, Taipei, Taiwan](http://2019.ieeeicip.org/?action=page4&id=14#Google)
|
||||
([presentation](https://docs.google.com/presentation/d/e/2PACX-1vRIBBbO_LO9v2YmvbHHEt1cwyqH6EjDxiILjuT0foXy1E7g6uyh4CesB2DkkEwlRDO9_lWfuKMZx98T/pub?start=false&loop=false&delayms=3000&slide=id.g556cc1a659_0_5))
|
||||
* [Open sourced at CVPR 2019, 17~20 June, Long Beach, CA](https://sites.google.com/corp/view/perception-cv4arvr/mediapipe)
|
||||
|
||||
## Community
|
||||
|
||||
* [Awesome MediaPipe](https://mediapipe.page.link/awesome-mediapipe) - A
|
||||
curated list of awesome MediaPipe related frameworks, libraries and software
|
||||
* [Slack community](https://mediapipe.page.link/joinslack) for MediaPipe users
|
||||
* [Discuss](https://groups.google.com/forum/#!forum/mediapipe) - General
|
||||
community discussion around MediaPipe
|
||||
|
||||
## Alpha disclaimer
|
||||
|
||||
MediaPipe is currently in alpha at v0.7. We may be still making breaking API
|
||||
changes and expect to get to stable APIs by v1.0.
|
||||
|
||||
## Contributing
|
||||
|
||||
We welcome contributions. Please follow these
|
||||
[guidelines](https://github.com/google/mediapipe/blob/master/CONTRIBUTING.md).
|
||||
|
||||
We use GitHub issues for tracking requests and bugs. Please post questions to
|
||||
the MediaPipe Stack Overflow with a `mediapipe` tag.
|
||||
|
||||
@@ -239,16 +239,6 @@ http_archive(
|
||||
repo_mapping = {"@com_google_glog" : "@com_github_glog_glog_no_gflags"},
|
||||
)
|
||||
|
||||
http_archive(
|
||||
name = "darts_clone",
|
||||
build_file = "@//third_party:darts_clone.BUILD",
|
||||
sha256 = "c97f55d05c98da6fcaf7f9ecc6a6dc6bc5b18b8564465f77abff8879d446491c",
|
||||
strip_prefix = "darts-clone-e40ce4627526985a7767444b6ed6893ab6ff8983",
|
||||
urls = [
|
||||
"https://github.com/s-yata/darts-clone/archive/e40ce4627526985a7767444b6ed6893ab6ff8983.zip",
|
||||
],
|
||||
)
|
||||
|
||||
http_archive(
|
||||
name = "org_tensorflow_text",
|
||||
sha256 = "f64647276f7288d1b1fe4c89581d51404d0ce4ae97f2bcc4c19bd667549adca8",
|
||||
@@ -375,22 +365,6 @@ http_archive(
|
||||
url = "https://github.com/opencv/opencv/releases/download/3.2.0/opencv-3.2.0-ios-framework.zip",
|
||||
)
|
||||
|
||||
# Building an opencv.xcframework from the OpenCV 4.5.3 sources is necessary for
|
||||
# MediaPipe iOS Task Libraries to be supported on arm64(M1) Macs. An
|
||||
# `opencv.xcframework` archive has not been released and it is recommended to
|
||||
# build the same from source using a script provided in OpenCV 4.5.0 upwards.
|
||||
# OpenCV is fixed to version to 4.5.3 since swift support can only be disabled
|
||||
# from 4.5.3 upwards. This is needed to avoid errors when the library is linked
|
||||
# in Xcode. Swift support will be added in when the final binary MediaPipe iOS
|
||||
# Task libraries are built.
|
||||
http_archive(
|
||||
name = "ios_opencv_source",
|
||||
sha256 = "a61e7a4618d353140c857f25843f39b2abe5f451b018aab1604ef0bc34cd23d5",
|
||||
build_file = "@//third_party:opencv_ios_source.BUILD",
|
||||
type = "zip",
|
||||
url = "https://github.com/opencv/opencv/archive/refs/tags/4.5.3.zip",
|
||||
)
|
||||
|
||||
http_archive(
|
||||
name = "stblib",
|
||||
strip_prefix = "stb-b42009b3b9d4ca35bc703f5310eedc74f584be58",
|
||||
@@ -484,9 +458,9 @@ http_archive(
|
||||
)
|
||||
|
||||
# TensorFlow repo should always go after the other external dependencies.
|
||||
# TF on 2023-04-12.
|
||||
_TENSORFLOW_GIT_COMMIT = "d712c0c9e24519cc8cd3720279666720d1000eee"
|
||||
_TENSORFLOW_SHA256 = "ba98de6ea5f720071246691a1536ecd5e1b1763033e8c82a1e721a06d3dfd4c1"
|
||||
# TF on 2023-03-08.
|
||||
_TENSORFLOW_GIT_COMMIT = "24f7ee636d62e1f8d8330357f8bbd65956dfb84d"
|
||||
_TENSORFLOW_SHA256 = "7f8a96dd99215c0cdc77230d3dbce43e60102b64a89203ad04aa09b0a187a4bd"
|
||||
http_archive(
|
||||
name = "org_tensorflow",
|
||||
urls = [
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
# Copyright 2022 The MediaPipe Authors.
|
||||
# Copyright 2022 The MediaPipe Authors. All Rights Reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
@@ -14,7 +14,6 @@
|
||||
# ==============================================================================
|
||||
"""Generate Java reference docs for MediaPipe."""
|
||||
import pathlib
|
||||
import shutil
|
||||
|
||||
from absl import app
|
||||
from absl import flags
|
||||
@@ -42,9 +41,7 @@ def main(_) -> None:
|
||||
mp_root = pathlib.Path(__file__)
|
||||
while (mp_root := mp_root.parent).name != 'mediapipe':
|
||||
# Find the nearest `mediapipe` dir.
|
||||
if not mp_root.name:
|
||||
# We've hit the filesystem root - abort.
|
||||
raise FileNotFoundError('"mediapipe" root not found')
|
||||
pass
|
||||
|
||||
# Find the root from which all packages are relative.
|
||||
root = mp_root.parent
|
||||
@@ -54,14 +51,6 @@ def main(_) -> None:
|
||||
if (mp_root / 'mediapipe').exists():
|
||||
mp_root = mp_root / 'mediapipe'
|
||||
|
||||
# We need to copy this into the tasks dir to ensure we don't leave broken
|
||||
# links in the generated docs.
|
||||
old_api_dir = 'java/com/google/mediapipe/framework/image'
|
||||
shutil.copytree(
|
||||
mp_root / old_api_dir,
|
||||
mp_root / 'tasks' / old_api_dir,
|
||||
dirs_exist_ok=True)
|
||||
|
||||
gen_java.gen_java_docs(
|
||||
package='com.google.mediapipe',
|
||||
source_path=mp_root / 'tasks/java',
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
# Copyright 2022 The MediaPipe Authors.
|
||||
# Copyright 2022 The MediaPipe Authors. All Rights Reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
# Copyright 2022 The MediaPipe Authors.
|
||||
# Copyright 2022 The MediaPipe Authors. All Rights Reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
|
||||
+104
-91
@@ -4,6 +4,8 @@ title: Home
|
||||
nav_order: 1
|
||||
---
|
||||
|
||||
|
||||
|
||||
----
|
||||
|
||||
**Attention:** *Thanks for your interest in MediaPipe! We have moved to
|
||||
@@ -12,111 +14,86 @@ as the primary developer documentation site for MediaPipe as of April 3, 2023.*
|
||||
|
||||
*This notice and web page will be removed on June 1, 2023.*
|
||||
|
||||
|
||||
----
|
||||
|
||||
**Attention**: MediaPipe Solutions Preview is an early release. [Learn
|
||||
more](https://developers.google.com/mediapipe/solutions/about#notice).
|
||||
<br><br><br><br><br><br><br><br><br><br>
|
||||
<br><br><br><br><br><br><br><br><br><br>
|
||||
<br><br><br><br><br><br><br><br><br><br>
|
||||
|
||||
**On-device machine learning for everyone**
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
Delight your customers with innovative machine learning features. MediaPipe
|
||||
contains everything that you need to customize and deploy to mobile (Android,
|
||||
iOS), web, desktop, edge devices, and IoT, effortlessly.
|
||||
## Live ML anywhere
|
||||
|
||||
* [See demos](https://goo.gle/mediapipe-studio)
|
||||
* [Learn more](https://developers.google.com/mediapipe/solutions)
|
||||
[MediaPipe](https://google.github.io/mediapipe/) offers cross-platform, customizable
|
||||
ML solutions for live and streaming media.
|
||||
|
||||
## Get started
|
||||
 | 
|
||||
:------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------:
|
||||
***End-to-End acceleration***: *Built-in fast ML inference and processing accelerated even on common hardware* | ***Build once, deploy anywhere***: *Unified solution works across Android, iOS, desktop/cloud, web and IoT*
|
||||
 | 
|
||||
***Ready-to-use solutions***: *Cutting-edge ML solutions demonstrating full power of the framework* | ***Free and open source***: *Framework and solutions both under Apache 2.0, fully extensible and customizable*
|
||||
|
||||
You can get started with MediaPipe Solutions by by checking out any of the
|
||||
developer guides for
|
||||
[vision](https://developers.google.com/mediapipe/solutions/vision/object_detector),
|
||||
[text](https://developers.google.com/mediapipe/solutions/text/text_classifier),
|
||||
and
|
||||
[audio](https://developers.google.com/mediapipe/solutions/audio/audio_classifier)
|
||||
tasks. If you need help setting up a development environment for use with
|
||||
MediaPipe Tasks, check out the setup guides for
|
||||
[Android](https://developers.google.com/mediapipe/solutions/setup_android), [web
|
||||
apps](https://developers.google.com/mediapipe/solutions/setup_web), and
|
||||
[Python](https://developers.google.com/mediapipe/solutions/setup_python).
|
||||
----
|
||||
|
||||
## Solutions
|
||||
## ML solutions in MediaPipe
|
||||
|
||||
MediaPipe Solutions provides a suite of libraries and tools for you to quickly
|
||||
apply artificial intelligence (AI) and machine learning (ML) techniques in your
|
||||
applications. You can plug these solutions into your applications immediately,
|
||||
customize them to your needs, and use them across multiple development
|
||||
platforms. MediaPipe Solutions is part of the MediaPipe [open source
|
||||
project](https://github.com/google/mediapipe), so you can further customize the
|
||||
solutions code to meet your application needs.
|
||||
Face Detection | Face Mesh | Iris | Hands | Pose | Holistic
|
||||
:----------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------: | :------:
|
||||
[](https://google.github.io/mediapipe/solutions/face_detection) | [](https://google.github.io/mediapipe/solutions/face_mesh) | [](https://google.github.io/mediapipe/solutions/iris) | [](https://google.github.io/mediapipe/solutions/hands) | [](https://google.github.io/mediapipe/solutions/pose) | [](https://google.github.io/mediapipe/solutions/holistic)
|
||||
|
||||
These libraries and resources provide the core functionality for each MediaPipe
|
||||
Solution:
|
||||
Hair Segmentation | Object Detection | Box Tracking | Instant Motion Tracking | Objectron | KNIFT
|
||||
:-------------------------------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------------------------------------------------------------------------: | :---:
|
||||
[](https://google.github.io/mediapipe/solutions/hair_segmentation) | [](https://google.github.io/mediapipe/solutions/object_detection) | [](https://google.github.io/mediapipe/solutions/box_tracking) | [](https://google.github.io/mediapipe/solutions/instant_motion_tracking) | [](https://google.github.io/mediapipe/solutions/objectron) | [](https://google.github.io/mediapipe/solutions/knift)
|
||||
|
||||
* **MediaPipe Tasks**: Cross-platform APIs and libraries for deploying
|
||||
solutions. [Learn
|
||||
more](https://developers.google.com/mediapipe/solutions/tasks).
|
||||
* **MediaPipe models**: Pre-trained, ready-to-run models for use with each
|
||||
solution.
|
||||
<!-- []() in the first cell is needed to preserve table formatting in GitHub Pages. -->
|
||||
<!-- Whenever this table is updated, paste a copy to solutions/solutions.md. -->
|
||||
|
||||
These tools let you customize and evaluate solutions:
|
||||
[]() | [Android](https://google.github.io/mediapipe/getting_started/android) | [iOS](https://google.github.io/mediapipe/getting_started/ios) | [C++](https://google.github.io/mediapipe/getting_started/cpp) | [Python](https://google.github.io/mediapipe/getting_started/python) | [JS](https://google.github.io/mediapipe/getting_started/javascript) | [Coral](https://github.com/google/mediapipe/tree/master/mediapipe/examples/coral/README.md)
|
||||
:---------------------------------------------------------------------------------------- | :-------------------------------------------------------------: | :-----------------------------------------------------: | :-----------------------------------------------------: | :-----------------------------------------------------------: | :-----------------------------------------------------------: | :--------------------------------------------------------------------:
|
||||
[Face Detection](https://google.github.io/mediapipe/solutions/face_detection) | ✅ | ✅ | ✅ | ✅ | ✅ | ✅
|
||||
[Face Mesh](https://google.github.io/mediapipe/solutions/face_mesh) | ✅ | ✅ | ✅ | ✅ | ✅ |
|
||||
[Iris](https://google.github.io/mediapipe/solutions/iris) | ✅ | ✅ | ✅ | | |
|
||||
[Hands](https://google.github.io/mediapipe/solutions/hands) | ✅ | ✅ | ✅ | ✅ | ✅ |
|
||||
[Pose](https://google.github.io/mediapipe/solutions/pose) | ✅ | ✅ | ✅ | ✅ | ✅ |
|
||||
[Holistic](https://google.github.io/mediapipe/solutions/holistic) | ✅ | ✅ | ✅ | ✅ | ✅ |
|
||||
[Selfie Segmentation](https://google.github.io/mediapipe/solutions/selfie_segmentation) | ✅ | ✅ | ✅ | ✅ | ✅ |
|
||||
[Hair Segmentation](https://google.github.io/mediapipe/solutions/hair_segmentation) | ✅ | | ✅ | | |
|
||||
[Object Detection](https://google.github.io/mediapipe/solutions/object_detection) | ✅ | ✅ | ✅ | | | ✅
|
||||
[Box Tracking](https://google.github.io/mediapipe/solutions/box_tracking) | ✅ | ✅ | ✅ | | |
|
||||
[Instant Motion Tracking](https://google.github.io/mediapipe/solutions/instant_motion_tracking) | ✅ | | | | |
|
||||
[Objectron](https://google.github.io/mediapipe/solutions/objectron) | ✅ | | ✅ | ✅ | ✅ |
|
||||
[KNIFT](https://google.github.io/mediapipe/solutions/knift) | ✅ | | | | |
|
||||
[AutoFlip](https://google.github.io/mediapipe/solutions/autoflip) | | | ✅ | | |
|
||||
[MediaSequence](https://google.github.io/mediapipe/solutions/media_sequence) | | | ✅ | | |
|
||||
[YouTube 8M](https://google.github.io/mediapipe/solutions/youtube_8m) | | | ✅ | | |
|
||||
|
||||
* **MediaPipe Model Maker**: Customize models for solutions with your data.
|
||||
[Learn more](https://developers.google.com/mediapipe/solutions/model_maker).
|
||||
* **MediaPipe Studio**: Visualize, evaluate, and benchmark solutions in your
|
||||
browser. [Learn
|
||||
more](https://developers.google.com/mediapipe/solutions/studio).
|
||||
See also
|
||||
[MediaPipe Models and Model Cards](https://google.github.io/mediapipe/solutions/models)
|
||||
for ML models released in MediaPipe.
|
||||
|
||||
### Legacy solutions
|
||||
## Getting started
|
||||
|
||||
We have ended support for [these MediaPipe Legacy Solutions](https://developers.google.com/mediapipe/solutions/guide#legacy)
|
||||
as of March 1, 2023. All other MediaPipe Legacy Solutions will be upgraded to
|
||||
a new MediaPipe Solution. See the [Solutions guide](https://developers.google.com/mediapipe/solutions/guide#legacy)
|
||||
for details. The [code repository](https://github.com/google/mediapipe/tree/master/mediapipe)
|
||||
and prebuilt binaries for all MediaPipe Legacy Solutions will continue to be
|
||||
provided on an as-is basis.
|
||||
To start using MediaPipe
|
||||
[solutions](https://google.github.io/mediapipe/solutions/solutions) with only a few
|
||||
lines code, see example code and demos in
|
||||
[MediaPipe in Python](https://google.github.io/mediapipe/getting_started/python) and
|
||||
[MediaPipe in JavaScript](https://google.github.io/mediapipe/getting_started/javascript).
|
||||
|
||||
For more on the legacy solutions, see the [documentation](https://github.com/google/mediapipe/tree/master/docs/solutions).
|
||||
To use MediaPipe in C++, Android and iOS, which allow further customization of
|
||||
the [solutions](https://google.github.io/mediapipe/solutions/solutions) as well as
|
||||
building your own, learn how to
|
||||
[install](https://google.github.io/mediapipe/getting_started/install) MediaPipe and
|
||||
start building example applications in
|
||||
[C++](https://google.github.io/mediapipe/getting_started/cpp),
|
||||
[Android](https://google.github.io/mediapipe/getting_started/android) and
|
||||
[iOS](https://google.github.io/mediapipe/getting_started/ios).
|
||||
|
||||
## Framework
|
||||
The source code is hosted in the
|
||||
[MediaPipe Github repository](https://github.com/google/mediapipe), and you can
|
||||
run code search using
|
||||
[Google Open Source Code Search](https://cs.opensource.google/mediapipe/mediapipe).
|
||||
|
||||
To start using MediaPipe Framework, [install MediaPipe
|
||||
Framework](https://developers.google.com/mediapipe/framework/getting_started/install)
|
||||
and start building example applications in C++, Android, and iOS.
|
||||
|
||||
[MediaPipe Framework](https://developers.google.com/mediapipe/framework) is the
|
||||
low-level component used to build efficient on-device machine learning
|
||||
pipelines, similar to the premade MediaPipe Solutions.
|
||||
|
||||
Before using MediaPipe Framework, familiarize yourself with the following key
|
||||
[Framework
|
||||
concepts](https://developers.google.com/mediapipe/framework/framework_concepts/overview.md):
|
||||
|
||||
* [Packets](https://developers.google.com/mediapipe/framework/framework_concepts/packets.md)
|
||||
* [Graphs](https://developers.google.com/mediapipe/framework/framework_concepts/graphs.md)
|
||||
* [Calculators](https://developers.google.com/mediapipe/framework/framework_concepts/calculators.md)
|
||||
|
||||
## Community
|
||||
|
||||
* [Slack community](https://mediapipe.page.link/joinslack) for MediaPipe
|
||||
users.
|
||||
* [Discuss](https://groups.google.com/forum/#!forum/mediapipe) - General
|
||||
community discussion around MediaPipe.
|
||||
* [Awesome MediaPipe](https://mediapipe.page.link/awesome-mediapipe) - A
|
||||
curated list of awesome MediaPipe related frameworks, libraries and
|
||||
software.
|
||||
|
||||
## Contributing
|
||||
|
||||
We welcome contributions. Please follow these
|
||||
[guidelines](https://github.com/google/mediapipe/blob/master/CONTRIBUTING.md).
|
||||
|
||||
We use GitHub issues for tracking requests and bugs. Please post questions to
|
||||
the MediaPipe Stack Overflow with a `mediapipe` tag.
|
||||
|
||||
## Resources
|
||||
|
||||
### Publications
|
||||
## Publications
|
||||
|
||||
* [Bringing artworks to life with AR](https://developers.googleblog.com/2021/07/bringing-artworks-to-life-with-ar.html)
|
||||
in Google Developers Blog
|
||||
@@ -125,8 +102,7 @@ the MediaPipe Stack Overflow with a `mediapipe` tag.
|
||||
* [SignAll SDK: Sign language interface using MediaPipe is now available for
|
||||
developers](https://developers.googleblog.com/2021/04/signall-sdk-sign-language-interface-using-mediapipe-now-available.html)
|
||||
in Google Developers Blog
|
||||
* [MediaPipe Holistic - Simultaneous Face, Hand and Pose Prediction, on
|
||||
Device](https://ai.googleblog.com/2020/12/mediapipe-holistic-simultaneous-face.html)
|
||||
* [MediaPipe Holistic - Simultaneous Face, Hand and Pose Prediction, on Device](https://ai.googleblog.com/2020/12/mediapipe-holistic-simultaneous-face.html)
|
||||
in Google AI Blog
|
||||
* [Background Features in Google Meet, Powered by Web ML](https://ai.googleblog.com/2020/10/background-features-in-google-meet.html)
|
||||
in Google AI Blog
|
||||
@@ -154,6 +130,43 @@ the MediaPipe Stack Overflow with a `mediapipe` tag.
|
||||
in Google AI Blog
|
||||
* [MediaPipe: A Framework for Building Perception Pipelines](https://arxiv.org/abs/1906.08172)
|
||||
|
||||
### Videos
|
||||
## Videos
|
||||
|
||||
* [YouTube Channel](https://www.youtube.com/c/MediaPipe)
|
||||
|
||||
## Events
|
||||
|
||||
* [MediaPipe Seattle Meetup, Google Building Waterside, 13 Feb 2020](https://mediapipe.page.link/seattle2020)
|
||||
* [AI Nextcon 2020, 12-16 Feb 2020, Seattle](http://aisea20.xnextcon.com/)
|
||||
* [MediaPipe Madrid Meetup, 16 Dec 2019](https://www.meetup.com/Madrid-AI-Developers-Group/events/266329088/)
|
||||
* [MediaPipe London Meetup, Google 123 Building, 12 Dec 2019](https://www.meetup.com/London-AI-Tech-Talk/events/266329038)
|
||||
* [ML Conference, Berlin, 11 Dec 2019](https://mlconference.ai/machine-learning-advanced-development/mediapipe-building-real-time-cross-platform-mobile-web-edge-desktop-video-audio-ml-pipelines/)
|
||||
* [MediaPipe Berlin Meetup, Google Berlin, 11 Dec 2019](https://www.meetup.com/Berlin-AI-Tech-Talk/events/266328794/)
|
||||
* [The 3rd Workshop on YouTube-8M Large Scale Video Understanding Workshop,
|
||||
Seoul, Korea ICCV
|
||||
2019](https://research.google.com/youtube8m/workshop2019/index.html)
|
||||
* [AI DevWorld 2019, 10 Oct 2019, San Jose, CA](https://aidevworld.com)
|
||||
* [Google Industry Workshop at ICIP 2019, 24 Sept 2019, Taipei, Taiwan](http://2019.ieeeicip.org/?action=page4&id=14#Google)
|
||||
([presentation](https://docs.google.com/presentation/d/e/2PACX-1vRIBBbO_LO9v2YmvbHHEt1cwyqH6EjDxiILjuT0foXy1E7g6uyh4CesB2DkkEwlRDO9_lWfuKMZx98T/pub?start=false&loop=false&delayms=3000&slide=id.g556cc1a659_0_5))
|
||||
* [Open sourced at CVPR 2019, 17~20 June, Long Beach, CA](https://sites.google.com/corp/view/perception-cv4arvr/mediapipe)
|
||||
|
||||
## Community
|
||||
|
||||
* [Awesome MediaPipe](https://mediapipe.page.link/awesome-mediapipe) - A
|
||||
curated list of awesome MediaPipe related frameworks, libraries and software
|
||||
* [Slack community](https://mediapipe.page.link/joinslack) for MediaPipe users
|
||||
* [Discuss](https://groups.google.com/forum/#!forum/mediapipe) - General
|
||||
community discussion around MediaPipe
|
||||
|
||||
## Alpha disclaimer
|
||||
|
||||
MediaPipe is currently in alpha at v0.7. We may be still making breaking API
|
||||
changes and expect to get to stable APIs by v1.0.
|
||||
|
||||
## Contributing
|
||||
|
||||
We welcome contributions. Please follow these
|
||||
[guidelines](https://github.com/google/mediapipe/blob/master/CONTRIBUTING.md).
|
||||
|
||||
We use GitHub issues for tracking requests and bugs. Please post questions to
|
||||
the MediaPipe Stack Overflow with a `mediapipe` tag.
|
||||
|
||||
@@ -141,7 +141,6 @@ config_setting(
|
||||
"ios_armv7",
|
||||
"ios_arm64",
|
||||
"ios_arm64e",
|
||||
"ios_sim_arm64",
|
||||
]
|
||||
]
|
||||
|
||||
|
||||
@@ -433,9 +433,9 @@ absl::Status SpectrogramCalculator::ProcessVectorToOutput(
|
||||
absl::Status SpectrogramCalculator::ProcessVector(const Matrix& input_stream,
|
||||
CalculatorContext* cc) {
|
||||
switch (output_type_) {
|
||||
// These blocks deliberately ignore clang-format to preserve the
|
||||
// "silhouette" of the different cases.
|
||||
// clang-format off
|
||||
// These blocks deliberately ignore clang-format to preserve the
|
||||
// "silhouette" of the different cases.
|
||||
// clang-format off
|
||||
case SpectrogramCalculatorOptions::COMPLEX: {
|
||||
return ProcessVectorToOutput(
|
||||
input_stream,
|
||||
|
||||
@@ -78,7 +78,7 @@ class ConstantSidePacketCalculator : public CalculatorBase {
|
||||
} else if (packet_options.has_string_value()) {
|
||||
packet.Set<std::string>();
|
||||
} else if (packet_options.has_uint64_value()) {
|
||||
packet.Set<uint64_t>();
|
||||
packet.Set<uint64>();
|
||||
} else if (packet_options.has_classification_list_value()) {
|
||||
packet.Set<ClassificationList>();
|
||||
} else if (packet_options.has_landmark_list_value()) {
|
||||
@@ -112,7 +112,7 @@ class ConstantSidePacketCalculator : public CalculatorBase {
|
||||
} else if (packet_options.has_string_value()) {
|
||||
packet.Set(MakePacket<std::string>(packet_options.string_value()));
|
||||
} else if (packet_options.has_uint64_value()) {
|
||||
packet.Set(MakePacket<uint64_t>(packet_options.uint64_value()));
|
||||
packet.Set(MakePacket<uint64>(packet_options.uint64_value()));
|
||||
} else if (packet_options.has_classification_list_value()) {
|
||||
packet.Set(MakePacket<ClassificationList>(
|
||||
packet_options.classification_list_value()));
|
||||
|
||||
@@ -42,7 +42,7 @@ constexpr char kOptionsTag[] = "OPTIONS";
|
||||
//
|
||||
// Increasing `max_in_flight` to 2 or more can yield the better throughput
|
||||
// when the graph exhibits a high degree of pipeline parallelism. Decreasing
|
||||
// `max_in_queue` to 0 can yield a better average latency, but at the cost of
|
||||
// `max_in_flight` to 0 can yield a better average latency, but at the cost of
|
||||
// lower throughput (lower framerate) due to the time during which the graph
|
||||
// is idle awaiting the next input frame.
|
||||
//
|
||||
|
||||
@@ -26,15 +26,19 @@ constexpr char kStateChangeTag[] = "STATE_CHANGE";
|
||||
constexpr char kDisallowTag[] = "DISALLOW";
|
||||
constexpr char kAllowTag[] = "ALLOW";
|
||||
|
||||
std::string ToString(GateCalculatorOptions::GateState state) {
|
||||
enum GateState {
|
||||
GATE_UNINITIALIZED,
|
||||
GATE_ALLOW,
|
||||
GATE_DISALLOW,
|
||||
};
|
||||
|
||||
std::string ToString(GateState state) {
|
||||
switch (state) {
|
||||
case GateCalculatorOptions::UNSPECIFIED:
|
||||
return "UNSPECIFIED";
|
||||
case GateCalculatorOptions::GATE_UNINITIALIZED:
|
||||
case GATE_UNINITIALIZED:
|
||||
return "UNINITIALIZED";
|
||||
case GateCalculatorOptions::GATE_ALLOW:
|
||||
case GATE_ALLOW:
|
||||
return "ALLOW";
|
||||
case GateCalculatorOptions::GATE_DISALLOW:
|
||||
case GATE_DISALLOW:
|
||||
return "DISALLOW";
|
||||
}
|
||||
DLOG(FATAL) << "Unknown GateState";
|
||||
@@ -149,12 +153,10 @@ class GateCalculator : public CalculatorBase {
|
||||
|
||||
cc->SetOffset(TimestampDiff(0));
|
||||
num_data_streams_ = cc->Inputs().NumEntries("");
|
||||
|
||||
const auto& options = cc->Options<::mediapipe::GateCalculatorOptions>();
|
||||
last_gate_state_ = options.initial_gate_state();
|
||||
|
||||
last_gate_state_ = GATE_UNINITIALIZED;
|
||||
RET_CHECK_OK(CopyInputHeadersToOutputs(cc->Inputs(), &cc->Outputs()));
|
||||
|
||||
const auto& options = cc->Options<::mediapipe::GateCalculatorOptions>();
|
||||
empty_packets_as_allow_ = options.empty_packets_as_allow();
|
||||
|
||||
if (!use_side_packet_for_allow_disallow_ &&
|
||||
@@ -182,12 +184,10 @@ class GateCalculator : public CalculatorBase {
|
||||
allow = !cc->Inputs().Tag(kDisallowTag).Get<bool>();
|
||||
}
|
||||
}
|
||||
const GateCalculatorOptions::GateState new_gate_state =
|
||||
allow ? GateCalculatorOptions::GATE_ALLOW
|
||||
: GateCalculatorOptions::GATE_DISALLOW;
|
||||
const GateState new_gate_state = allow ? GATE_ALLOW : GATE_DISALLOW;
|
||||
|
||||
if (cc->Outputs().HasTag(kStateChangeTag)) {
|
||||
if (last_gate_state_ != GateCalculatorOptions::GATE_UNINITIALIZED &&
|
||||
if (last_gate_state_ != GATE_UNINITIALIZED &&
|
||||
last_gate_state_ != new_gate_state) {
|
||||
VLOG(2) << "State transition in " << cc->NodeName() << " @ "
|
||||
<< cc->InputTimestamp().Value() << " from "
|
||||
@@ -223,8 +223,7 @@ class GateCalculator : public CalculatorBase {
|
||||
}
|
||||
|
||||
private:
|
||||
GateCalculatorOptions::GateState last_gate_state_ =
|
||||
GateCalculatorOptions::GATE_UNINITIALIZED;
|
||||
GateState last_gate_state_ = GATE_UNINITIALIZED;
|
||||
int num_data_streams_;
|
||||
bool empty_packets_as_allow_;
|
||||
bool use_side_packet_for_allow_disallow_ = false;
|
||||
|
||||
@@ -31,13 +31,4 @@ message GateCalculatorOptions {
|
||||
// Whether to allow or disallow the input streams to pass when no
|
||||
// ALLOW/DISALLOW input or side input is specified.
|
||||
optional bool allow = 2 [default = false];
|
||||
|
||||
enum GateState {
|
||||
UNSPECIFIED = 0;
|
||||
GATE_UNINITIALIZED = 1;
|
||||
GATE_ALLOW = 2;
|
||||
GATE_DISALLOW = 3;
|
||||
}
|
||||
|
||||
optional GateState initial_gate_state = 3 [default = GATE_UNINITIALIZED];
|
||||
}
|
||||
|
||||
@@ -35,14 +35,14 @@ class GateCalculatorTest : public ::testing::Test {
|
||||
}
|
||||
|
||||
// Use this when ALLOW/DISALLOW input is provided as a side packet.
|
||||
void RunTimeStep(int64_t timestamp, bool stream_payload) {
|
||||
void RunTimeStep(int64 timestamp, bool stream_payload) {
|
||||
runner_->MutableInputs()->Get("", 0).packets.push_back(
|
||||
MakePacket<bool>(stream_payload).At(Timestamp(timestamp)));
|
||||
MP_ASSERT_OK(runner_->Run()) << "Calculator execution failed.";
|
||||
}
|
||||
|
||||
// Use this when ALLOW/DISALLOW input is provided as an input stream.
|
||||
void RunTimeStep(int64_t timestamp, const std::string& control_tag,
|
||||
void RunTimeStep(int64 timestamp, const std::string& control_tag,
|
||||
bool control) {
|
||||
runner_->MutableInputs()->Get("", 0).packets.push_back(
|
||||
MakePacket<bool>(true).At(Timestamp(timestamp)));
|
||||
@@ -134,9 +134,9 @@ TEST_F(GateCalculatorTest, AllowByALLOWOptionToTrue) {
|
||||
}
|
||||
)");
|
||||
|
||||
constexpr int64_t kTimestampValue0 = 42;
|
||||
constexpr int64 kTimestampValue0 = 42;
|
||||
RunTimeStep(kTimestampValue0, true);
|
||||
constexpr int64_t kTimestampValue1 = 43;
|
||||
constexpr int64 kTimestampValue1 = 43;
|
||||
RunTimeStep(kTimestampValue1, false);
|
||||
|
||||
const std::vector<Packet>& output = runner()->Outputs().Get("", 0).packets;
|
||||
@@ -159,9 +159,9 @@ TEST_F(GateCalculatorTest, DisallowByALLOWOptionSetToFalse) {
|
||||
}
|
||||
)");
|
||||
|
||||
constexpr int64_t kTimestampValue0 = 42;
|
||||
constexpr int64 kTimestampValue0 = 42;
|
||||
RunTimeStep(kTimestampValue0, true);
|
||||
constexpr int64_t kTimestampValue1 = 43;
|
||||
constexpr int64 kTimestampValue1 = 43;
|
||||
RunTimeStep(kTimestampValue1, false);
|
||||
|
||||
const std::vector<Packet>& output = runner()->Outputs().Get("", 0).packets;
|
||||
@@ -175,9 +175,9 @@ TEST_F(GateCalculatorTest, DisallowByALLOWOptionNotSet) {
|
||||
output_stream: "test_output"
|
||||
)");
|
||||
|
||||
constexpr int64_t kTimestampValue0 = 42;
|
||||
constexpr int64 kTimestampValue0 = 42;
|
||||
RunTimeStep(kTimestampValue0, true);
|
||||
constexpr int64_t kTimestampValue1 = 43;
|
||||
constexpr int64 kTimestampValue1 = 43;
|
||||
RunTimeStep(kTimestampValue1, false);
|
||||
|
||||
const std::vector<Packet>& output = runner()->Outputs().Get("", 0).packets;
|
||||
@@ -193,9 +193,9 @@ TEST_F(GateCalculatorTest, AllowByALLOWSidePacketSetToTrue) {
|
||||
)");
|
||||
runner()->MutableSidePackets()->Tag(kAllowTag) = Adopt(new bool(true));
|
||||
|
||||
constexpr int64_t kTimestampValue0 = 42;
|
||||
constexpr int64 kTimestampValue0 = 42;
|
||||
RunTimeStep(kTimestampValue0, true);
|
||||
constexpr int64_t kTimestampValue1 = 43;
|
||||
constexpr int64 kTimestampValue1 = 43;
|
||||
RunTimeStep(kTimestampValue1, false);
|
||||
|
||||
const std::vector<Packet>& output = runner()->Outputs().Get("", 0).packets;
|
||||
@@ -215,9 +215,9 @@ TEST_F(GateCalculatorTest, AllowByDisallowSidePacketSetToFalse) {
|
||||
)");
|
||||
runner()->MutableSidePackets()->Tag(kDisallowTag) = Adopt(new bool(false));
|
||||
|
||||
constexpr int64_t kTimestampValue0 = 42;
|
||||
constexpr int64 kTimestampValue0 = 42;
|
||||
RunTimeStep(kTimestampValue0, true);
|
||||
constexpr int64_t kTimestampValue1 = 43;
|
||||
constexpr int64 kTimestampValue1 = 43;
|
||||
RunTimeStep(kTimestampValue1, false);
|
||||
|
||||
const std::vector<Packet>& output = runner()->Outputs().Get("", 0).packets;
|
||||
@@ -237,9 +237,9 @@ TEST_F(GateCalculatorTest, DisallowByALLOWSidePacketSetToFalse) {
|
||||
)");
|
||||
runner()->MutableSidePackets()->Tag(kAllowTag) = Adopt(new bool(false));
|
||||
|
||||
constexpr int64_t kTimestampValue0 = 42;
|
||||
constexpr int64 kTimestampValue0 = 42;
|
||||
RunTimeStep(kTimestampValue0, true);
|
||||
constexpr int64_t kTimestampValue1 = 43;
|
||||
constexpr int64 kTimestampValue1 = 43;
|
||||
RunTimeStep(kTimestampValue1, false);
|
||||
|
||||
const std::vector<Packet>& output = runner()->Outputs().Get("", 0).packets;
|
||||
@@ -255,9 +255,9 @@ TEST_F(GateCalculatorTest, DisallowByDISALLOWSidePacketSetToTrue) {
|
||||
)");
|
||||
runner()->MutableSidePackets()->Tag(kDisallowTag) = Adopt(new bool(true));
|
||||
|
||||
constexpr int64_t kTimestampValue0 = 42;
|
||||
constexpr int64 kTimestampValue0 = 42;
|
||||
RunTimeStep(kTimestampValue0, true);
|
||||
constexpr int64_t kTimestampValue1 = 43;
|
||||
constexpr int64 kTimestampValue1 = 43;
|
||||
RunTimeStep(kTimestampValue1, false);
|
||||
|
||||
const std::vector<Packet>& output = runner()->Outputs().Get("", 0).packets;
|
||||
@@ -272,13 +272,13 @@ TEST_F(GateCalculatorTest, Allow) {
|
||||
output_stream: "test_output"
|
||||
)");
|
||||
|
||||
constexpr int64_t kTimestampValue0 = 42;
|
||||
constexpr int64 kTimestampValue0 = 42;
|
||||
RunTimeStep(kTimestampValue0, "ALLOW", true);
|
||||
constexpr int64_t kTimestampValue1 = 43;
|
||||
constexpr int64 kTimestampValue1 = 43;
|
||||
RunTimeStep(kTimestampValue1, "ALLOW", false);
|
||||
constexpr int64_t kTimestampValue2 = 44;
|
||||
constexpr int64 kTimestampValue2 = 44;
|
||||
RunTimeStep(kTimestampValue2, "ALLOW", true);
|
||||
constexpr int64_t kTimestampValue3 = 45;
|
||||
constexpr int64 kTimestampValue3 = 45;
|
||||
RunTimeStep(kTimestampValue3, "ALLOW", false);
|
||||
|
||||
const std::vector<Packet>& output = runner()->Outputs().Get("", 0).packets;
|
||||
@@ -297,13 +297,13 @@ TEST_F(GateCalculatorTest, Disallow) {
|
||||
output_stream: "test_output"
|
||||
)");
|
||||
|
||||
constexpr int64_t kTimestampValue0 = 42;
|
||||
constexpr int64 kTimestampValue0 = 42;
|
||||
RunTimeStep(kTimestampValue0, "DISALLOW", true);
|
||||
constexpr int64_t kTimestampValue1 = 43;
|
||||
constexpr int64 kTimestampValue1 = 43;
|
||||
RunTimeStep(kTimestampValue1, "DISALLOW", false);
|
||||
constexpr int64_t kTimestampValue2 = 44;
|
||||
constexpr int64 kTimestampValue2 = 44;
|
||||
RunTimeStep(kTimestampValue2, "DISALLOW", true);
|
||||
constexpr int64_t kTimestampValue3 = 45;
|
||||
constexpr int64 kTimestampValue3 = 45;
|
||||
RunTimeStep(kTimestampValue3, "DISALLOW", false);
|
||||
|
||||
const std::vector<Packet>& output = runner()->Outputs().Get("", 0).packets;
|
||||
@@ -323,13 +323,13 @@ TEST_F(GateCalculatorTest, AllowWithStateChange) {
|
||||
output_stream: "STATE_CHANGE:state_changed"
|
||||
)");
|
||||
|
||||
constexpr int64_t kTimestampValue0 = 42;
|
||||
constexpr int64 kTimestampValue0 = 42;
|
||||
RunTimeStep(kTimestampValue0, "ALLOW", false);
|
||||
constexpr int64_t kTimestampValue1 = 43;
|
||||
constexpr int64 kTimestampValue1 = 43;
|
||||
RunTimeStep(kTimestampValue1, "ALLOW", true);
|
||||
constexpr int64_t kTimestampValue2 = 44;
|
||||
constexpr int64 kTimestampValue2 = 44;
|
||||
RunTimeStep(kTimestampValue2, "ALLOW", true);
|
||||
constexpr int64_t kTimestampValue3 = 45;
|
||||
constexpr int64 kTimestampValue3 = 45;
|
||||
RunTimeStep(kTimestampValue3, "ALLOW", false);
|
||||
|
||||
const std::vector<Packet>& output =
|
||||
@@ -379,13 +379,13 @@ TEST_F(GateCalculatorTest, DisallowWithStateChange) {
|
||||
output_stream: "STATE_CHANGE:state_changed"
|
||||
)");
|
||||
|
||||
constexpr int64_t kTimestampValue0 = 42;
|
||||
constexpr int64 kTimestampValue0 = 42;
|
||||
RunTimeStep(kTimestampValue0, "DISALLOW", true);
|
||||
constexpr int64_t kTimestampValue1 = 43;
|
||||
constexpr int64 kTimestampValue1 = 43;
|
||||
RunTimeStep(kTimestampValue1, "DISALLOW", false);
|
||||
constexpr int64_t kTimestampValue2 = 44;
|
||||
constexpr int64 kTimestampValue2 = 44;
|
||||
RunTimeStep(kTimestampValue2, "DISALLOW", false);
|
||||
constexpr int64_t kTimestampValue3 = 45;
|
||||
constexpr int64 kTimestampValue3 = 45;
|
||||
RunTimeStep(kTimestampValue3, "DISALLOW", true);
|
||||
|
||||
const std::vector<Packet>& output =
|
||||
@@ -432,7 +432,7 @@ TEST_F(GateCalculatorTest, DisallowInitialNoStateTransition) {
|
||||
output_stream: "STATE_CHANGE:state_changed"
|
||||
)");
|
||||
|
||||
constexpr int64_t kTimestampValue0 = 42;
|
||||
constexpr int64 kTimestampValue0 = 42;
|
||||
RunTimeStep(kTimestampValue0, "DISALLOW", false);
|
||||
|
||||
const std::vector<Packet>& output =
|
||||
@@ -450,7 +450,7 @@ TEST_F(GateCalculatorTest, AllowInitialNoStateTransition) {
|
||||
output_stream: "STATE_CHANGE:state_changed"
|
||||
)");
|
||||
|
||||
constexpr int64_t kTimestampValue0 = 42;
|
||||
constexpr int64 kTimestampValue0 = 42;
|
||||
RunTimeStep(kTimestampValue0, "ALLOW", true);
|
||||
|
||||
const std::vector<Packet>& output =
|
||||
@@ -458,29 +458,5 @@ TEST_F(GateCalculatorTest, AllowInitialNoStateTransition) {
|
||||
ASSERT_EQ(0, output.size());
|
||||
}
|
||||
|
||||
// Must detect allow value for first timestamp as a state change when the
|
||||
// initial state is set to GATE_DISALLOW.
|
||||
TEST_F(GateCalculatorTest, StateChangeTriggeredWithInitialGateStateOption) {
|
||||
SetRunner(R"(
|
||||
calculator: "GateCalculator"
|
||||
input_stream: "test_input"
|
||||
input_stream: "ALLOW:allow"
|
||||
output_stream: "test_output"
|
||||
output_stream: "STATE_CHANGE:state_change"
|
||||
options: {
|
||||
[mediapipe.GateCalculatorOptions.ext] {
|
||||
initial_gate_state: GATE_DISALLOW
|
||||
}
|
||||
}
|
||||
)");
|
||||
|
||||
constexpr int64_t kTimestampValue0 = 42;
|
||||
RunTimeStep(kTimestampValue0, "ALLOW", true);
|
||||
|
||||
const std::vector<Packet>& output =
|
||||
runner()->Outputs().Get("STATE_CHANGE", 0).packets;
|
||||
ASSERT_EQ(1, output.size());
|
||||
}
|
||||
|
||||
} // namespace
|
||||
} // namespace mediapipe
|
||||
|
||||
@@ -35,7 +35,7 @@ class MatrixToVectorCalculatorTest
|
||||
void SetUp() override { calculator_name_ = "MatrixToVectorCalculator"; }
|
||||
|
||||
void AppendInput(const std::vector<float>& column_major_data,
|
||||
int64_t timestamp) {
|
||||
int64 timestamp) {
|
||||
ASSERT_EQ(num_input_samples_ * num_input_channels_,
|
||||
column_major_data.size());
|
||||
Eigen::Map<const Matrix> data_map(&column_major_data[0],
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
/* Copyright 2022 The MediaPipe Authors.
|
||||
/* Copyright 2022 The MediaPipe Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
/* Copyright 2022 The MediaPipe Authors.
|
||||
/* Copyright 2022 The MediaPipe Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
|
||||
@@ -18,7 +18,7 @@
|
||||
|
||||
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) {
|
||||
int64 ReflectBetween(int64 ts, int64 ts_min, int64 ts_max) {
|
||||
if (ts < ts_min) return 2 * ts_min - ts - 1;
|
||||
if (ts >= ts_max) return 2 * ts_max - ts - 1;
|
||||
return ts;
|
||||
@@ -47,7 +47,7 @@ constexpr char kOptionsTag[] = "OPTIONS";
|
||||
// Returns a TimestampDiff (assuming microseconds) corresponding to the
|
||||
// given time in seconds.
|
||||
TimestampDiff TimestampDiffFromSeconds(double seconds) {
|
||||
return TimestampDiff(MathUtil::SafeRound<int64_t, double>(
|
||||
return TimestampDiff(MathUtil::SafeRound<int64, double>(
|
||||
seconds * Timestamp::kTimestampUnitsPerSecond));
|
||||
}
|
||||
} // namespace
|
||||
@@ -117,8 +117,8 @@ absl::Status PacketResamplerCalculator::Open(CalculatorContext* cc) {
|
||||
<< "The output frame rate must be smaller than "
|
||||
<< Timestamp::kTimestampUnitsPerSecond;
|
||||
|
||||
frame_time_usec_ = static_cast<int64_t>(1000000.0 / frame_rate_);
|
||||
jitter_usec_ = static_cast<int64_t>(1000000.0 * jitter_ / frame_rate_);
|
||||
frame_time_usec_ = static_cast<int64>(1000000.0 / frame_rate_);
|
||||
jitter_usec_ = static_cast<int64>(1000000.0 * jitter_ / frame_rate_);
|
||||
RET_CHECK_LE(jitter_usec_, frame_time_usec_);
|
||||
|
||||
video_header_.frame_rate = frame_rate_;
|
||||
@@ -198,18 +198,17 @@ PacketResamplerCalculator::GetSamplingStrategy(
|
||||
return absl::make_unique<JitterWithoutReflectionStrategy>(this);
|
||||
}
|
||||
|
||||
Timestamp PacketResamplerCalculator::PeriodIndexToTimestamp(
|
||||
int64_t index) const {
|
||||
Timestamp PacketResamplerCalculator::PeriodIndexToTimestamp(int64 index) const {
|
||||
CHECK_EQ(jitter_, 0.0);
|
||||
CHECK_NE(first_timestamp_, Timestamp::Unset());
|
||||
return first_timestamp_ + TimestampDiffFromSeconds(index / frame_rate_);
|
||||
}
|
||||
|
||||
int64_t PacketResamplerCalculator::TimestampToPeriodIndex(
|
||||
int64 PacketResamplerCalculator::TimestampToPeriodIndex(
|
||||
Timestamp timestamp) const {
|
||||
CHECK_EQ(jitter_, 0.0);
|
||||
CHECK_NE(first_timestamp_, Timestamp::Unset());
|
||||
return MathUtil::SafeRound<int64_t, double>(
|
||||
return MathUtil::SafeRound<int64, double>(
|
||||
(timestamp - first_timestamp_).Seconds() * frame_rate_);
|
||||
}
|
||||
|
||||
@@ -290,11 +289,11 @@ absl::Status LegacyJitterWithReflectionStrategy::Process(
|
||||
}
|
||||
|
||||
while (true) {
|
||||
const int64_t last_diff =
|
||||
const int64 last_diff =
|
||||
(next_output_timestamp_ - calculator_->last_packet_.Timestamp())
|
||||
.Value();
|
||||
RET_CHECK_GT(last_diff, 0);
|
||||
const int64_t curr_diff =
|
||||
const int64 curr_diff =
|
||||
(next_output_timestamp_ - cc->InputTimestamp()).Value();
|
||||
if (curr_diff > 0) {
|
||||
break;
|
||||
@@ -560,11 +559,11 @@ absl::Status JitterWithoutReflectionStrategy::Process(CalculatorContext* cc) {
|
||||
}
|
||||
|
||||
while (true) {
|
||||
const int64_t last_diff =
|
||||
const int64 last_diff =
|
||||
(next_output_timestamp_ - calculator_->last_packet_.Timestamp())
|
||||
.Value();
|
||||
RET_CHECK_GT(last_diff, 0);
|
||||
const int64_t curr_diff =
|
||||
const int64 curr_diff =
|
||||
(next_output_timestamp_ - cc->InputTimestamp()).Value();
|
||||
if (curr_diff > 0) {
|
||||
break;
|
||||
@@ -632,7 +631,7 @@ absl::Status NoJitterStrategy::Process(CalculatorContext* cc) {
|
||||
} else {
|
||||
// Initialize first_timestamp_ with the first packet timestamp
|
||||
// aligned to the base_timestamp_.
|
||||
int64_t first_index = MathUtil::SafeRound<int64_t, double>(
|
||||
int64 first_index = MathUtil::SafeRound<int64, double>(
|
||||
(cc->InputTimestamp() - base_timestamp_).Seconds() *
|
||||
calculator_->frame_rate_);
|
||||
calculator_->first_timestamp_ =
|
||||
@@ -647,7 +646,7 @@ absl::Status NoJitterStrategy::Process(CalculatorContext* cc) {
|
||||
}
|
||||
}
|
||||
const Timestamp received_timestamp = cc->InputTimestamp();
|
||||
const int64_t received_timestamp_idx =
|
||||
const int64 received_timestamp_idx =
|
||||
calculator_->TimestampToPeriodIndex(received_timestamp);
|
||||
// Only consider the received packet if it belongs to the current period
|
||||
// (== period_count_) or to a newer one (> period_count_).
|
||||
|
||||
@@ -51,9 +51,9 @@ class SimpleRunner : public CalculatorRunner {
|
||||
|
||||
virtual ~SimpleRunner() {}
|
||||
|
||||
void SetInput(const std::vector<int64_t>& timestamp_list) {
|
||||
void SetInput(const std::vector<int64>& timestamp_list) {
|
||||
MutableInputs()->Index(0).packets.clear();
|
||||
for (const int64_t ts : timestamp_list) {
|
||||
for (const int64 ts : timestamp_list) {
|
||||
MutableInputs()->Index(0).packets.push_back(
|
||||
Adopt(new std::string(absl::StrCat("Frame #", ts)))
|
||||
.At(Timestamp(ts)));
|
||||
@@ -72,8 +72,8 @@ class SimpleRunner : public CalculatorRunner {
|
||||
}
|
||||
|
||||
void CheckOutputTimestamps(
|
||||
const std::vector<int64_t>& expected_frames,
|
||||
const std::vector<int64_t>& expected_timestamps) const {
|
||||
const std::vector<int64>& expected_frames,
|
||||
const std::vector<int64>& expected_timestamps) const {
|
||||
EXPECT_EQ(expected_frames.size(), Outputs().Index(0).packets.size());
|
||||
EXPECT_EQ(expected_timestamps.size(), Outputs().Index(0).packets.size());
|
||||
int count = 0;
|
||||
@@ -112,7 +112,7 @@ MATCHER_P2(PacketAtTimestamp, payload, timestamp,
|
||||
*result_listener << "at incorrect timestamp = " << arg.Timestamp().Value();
|
||||
return false;
|
||||
}
|
||||
int64_t actual_payload = arg.template Get<int64_t>();
|
||||
int64 actual_payload = arg.template Get<int64>();
|
||||
if (actual_payload != payload) {
|
||||
*result_listener << "with incorrect payload = " << actual_payload;
|
||||
return false;
|
||||
@@ -137,18 +137,18 @@ class ReproducibleJitterWithReflectionStrategyForTesting
|
||||
//
|
||||
// An EXPECT will fail if sequence is less than the number requested during
|
||||
// processing.
|
||||
static std::vector<uint64_t> random_sequence;
|
||||
static std::vector<uint64> random_sequence;
|
||||
|
||||
protected:
|
||||
virtual uint64_t GetNextRandom(uint64_t n) {
|
||||
virtual uint64 GetNextRandom(uint64 n) {
|
||||
EXPECT_LT(sequence_index_, random_sequence.size());
|
||||
return random_sequence[sequence_index_++] % n;
|
||||
}
|
||||
|
||||
private:
|
||||
int32_t sequence_index_ = 0;
|
||||
int32 sequence_index_ = 0;
|
||||
};
|
||||
std::vector<uint64_t>
|
||||
std::vector<uint64>
|
||||
ReproducibleJitterWithReflectionStrategyForTesting::random_sequence;
|
||||
|
||||
// PacketResamplerCalculator child class which injects a specified stream
|
||||
@@ -469,7 +469,7 @@ TEST(PacketResamplerCalculatorTest, SetVideoHeader) {
|
||||
}
|
||||
)pb"));
|
||||
|
||||
for (const int64_t ts : {0, 5000, 10010, 15001, 19990}) {
|
||||
for (const int64 ts : {0, 5000, 10010, 15001, 19990}) {
|
||||
runner.MutableInputs()->Tag(kDataTag).packets.push_back(
|
||||
Adopt(new std::string(absl::StrCat("Frame #", ts))).At(Timestamp(ts)));
|
||||
}
|
||||
|
||||
@@ -97,7 +97,7 @@ class PacketThinnerCalculator : public CalculatorBase {
|
||||
cc->Inputs().Index(0).SetAny();
|
||||
cc->Outputs().Index(0).SetSameAs(&cc->Inputs().Index(0));
|
||||
if (cc->InputSidePackets().HasTag(kPeriodTag)) {
|
||||
cc->InputSidePackets().Tag(kPeriodTag).Set<int64_t>();
|
||||
cc->InputSidePackets().Tag(kPeriodTag).Set<int64>();
|
||||
}
|
||||
return absl::OkStatus();
|
||||
}
|
||||
@@ -173,7 +173,7 @@ absl::Status PacketThinnerCalculator::Open(CalculatorContext* cc) {
|
||||
|
||||
if (cc->InputSidePackets().HasTag(kPeriodTag)) {
|
||||
period_ =
|
||||
TimestampDiff(cc->InputSidePackets().Tag(kPeriodTag).Get<int64_t>());
|
||||
TimestampDiff(cc->InputSidePackets().Tag(kPeriodTag).Get<int64>());
|
||||
} else {
|
||||
period_ = TimestampDiff(options.period());
|
||||
}
|
||||
@@ -300,13 +300,13 @@ Timestamp PacketThinnerCalculator::NearestSyncTimestamp(Timestamp now) const {
|
||||
|
||||
// Computation is done using int64 arithmetic. No easy way to avoid
|
||||
// since Timestamps don't support div and multiply.
|
||||
const int64_t now64 = now.Value();
|
||||
const int64_t start64 = start_time_.Value();
|
||||
const int64_t period64 = period_.Value();
|
||||
const int64 now64 = now.Value();
|
||||
const int64 start64 = start_time_.Value();
|
||||
const int64 period64 = period_.Value();
|
||||
CHECK_LE(0, period64);
|
||||
|
||||
// Round now64 to its closest interval (units of period64).
|
||||
int64_t sync64 =
|
||||
int64 sync64 =
|
||||
(now64 - start64 + period64 / 2) / period64 * period64 + start64;
|
||||
CHECK_LE(abs(now64 - sync64), period64 / 2)
|
||||
<< "start64: " << start64 << "; now64: " << now64
|
||||
|
||||
@@ -43,8 +43,8 @@ constexpr char kDisallowTag[] = "DISALLOW";
|
||||
|
||||
// Returns the timestamp values for a vector of Packets.
|
||||
// TODO: puth this kind of test util in a common place.
|
||||
std::vector<int64_t> TimestampValues(const std::vector<Packet>& packets) {
|
||||
std::vector<int64_t> result;
|
||||
std::vector<int64> TimestampValues(const std::vector<Packet>& packets) {
|
||||
std::vector<int64> result;
|
||||
for (const Packet& packet : packets) {
|
||||
result.push_back(packet.Timestamp().Value());
|
||||
}
|
||||
@@ -371,7 +371,7 @@ TEST(PreviousLoopbackCalculator, EmptyLoopForever) {
|
||||
for (int main_ts = 0; main_ts < 50; ++main_ts) {
|
||||
send_packet("in", main_ts);
|
||||
MP_EXPECT_OK(graph_.WaitUntilIdle());
|
||||
std::vector<int64_t> ts_values = TimestampValues(outputs);
|
||||
std::vector<int64> ts_values = TimestampValues(outputs);
|
||||
EXPECT_EQ(ts_values.size(), main_ts + 1);
|
||||
for (int j = 0; j < main_ts + 1; ++j) {
|
||||
EXPECT_EQ(ts_values[j], j);
|
||||
|
||||
@@ -121,7 +121,7 @@ absl::Status SidePacketToStreamCalculator::GetContract(CalculatorContract* cc) {
|
||||
if (cc->Outputs().HasTag(kTagAtTimestamp)) {
|
||||
RET_CHECK_EQ(num_entries + 1, cc->InputSidePackets().NumEntries())
|
||||
<< "For AT_TIMESTAMP tag, 2 input side packets are required.";
|
||||
cc->InputSidePackets().Tag(kTagSideInputTimestamp).Set<int64_t>();
|
||||
cc->InputSidePackets().Tag(kTagSideInputTimestamp).Set<int64>();
|
||||
} else {
|
||||
RET_CHECK_EQ(num_entries, cc->InputSidePackets().NumEntries())
|
||||
<< "Same number of input side packets and output streams is required.";
|
||||
@@ -178,8 +178,8 @@ absl::Status SidePacketToStreamCalculator::Close(CalculatorContext* cc) {
|
||||
.AddPacket(cc->InputSidePackets().Index(i).At(timestamp));
|
||||
}
|
||||
} else if (cc->Outputs().HasTag(kTagAtTimestamp)) {
|
||||
int64_t timestamp =
|
||||
cc->InputSidePackets().Tag(kTagSideInputTimestamp).Get<int64_t>();
|
||||
int64 timestamp =
|
||||
cc->InputSidePackets().Tag(kTagSideInputTimestamp).Get<int64>();
|
||||
for (int i = 0; i < cc->Outputs().NumEntries(output_tag_); ++i) {
|
||||
cc->Outputs()
|
||||
.Get(output_tag_, i)
|
||||
|
||||
@@ -64,16 +64,16 @@ REGISTER_CALCULATOR(StringToIntCalculator);
|
||||
using StringToUintCalculator = StringToIntCalculatorTemplate<unsigned int>;
|
||||
REGISTER_CALCULATOR(StringToUintCalculator);
|
||||
|
||||
using StringToInt32Calculator = StringToIntCalculatorTemplate<int32_t>;
|
||||
using StringToInt32Calculator = StringToIntCalculatorTemplate<int32>;
|
||||
REGISTER_CALCULATOR(StringToInt32Calculator);
|
||||
|
||||
using StringToUint32Calculator = StringToIntCalculatorTemplate<uint32_t>;
|
||||
using StringToUint32Calculator = StringToIntCalculatorTemplate<uint32>;
|
||||
REGISTER_CALCULATOR(StringToUint32Calculator);
|
||||
|
||||
using StringToInt64Calculator = StringToIntCalculatorTemplate<int64_t>;
|
||||
using StringToInt64Calculator = StringToIntCalculatorTemplate<int64>;
|
||||
REGISTER_CALCULATOR(StringToInt64Calculator);
|
||||
|
||||
using StringToUint64Calculator = StringToIntCalculatorTemplate<uint64_t>;
|
||||
using StringToUint64Calculator = StringToIntCalculatorTemplate<uint64>;
|
||||
REGISTER_CALCULATOR(StringToUint64Calculator);
|
||||
|
||||
} // namespace mediapipe
|
||||
|
||||
@@ -75,16 +75,16 @@ absl::Status FindInterpolationAlgorithm(
|
||||
|
||||
void CropImageFrame(const ImageFrame& original, int col_start, int row_start,
|
||||
int crop_width, int crop_height, ImageFrame* cropped) {
|
||||
const uint8_t* src = original.PixelData();
|
||||
uint8_t* dst = cropped->MutablePixelData();
|
||||
const uint8* src = original.PixelData();
|
||||
uint8* dst = cropped->MutablePixelData();
|
||||
|
||||
int des_y = 0;
|
||||
for (int y = row_start; y < row_start + crop_height; ++y) {
|
||||
const uint8_t* src_line = src + y * original.WidthStep();
|
||||
const uint8_t* src_pixel = src_line + col_start *
|
||||
original.NumberOfChannels() *
|
||||
original.ByteDepth();
|
||||
uint8_t* dst_line = dst + des_y * cropped->WidthStep();
|
||||
const uint8* src_line = src + y * original.WidthStep();
|
||||
const uint8* src_pixel = src_line + col_start *
|
||||
original.NumberOfChannels() *
|
||||
original.ByteDepth();
|
||||
uint8* dst_line = dst + des_y * cropped->WidthStep();
|
||||
std::memcpy(
|
||||
dst_line, src_pixel,
|
||||
crop_width * cropped->NumberOfChannels() * cropped->ByteDepth());
|
||||
@@ -591,9 +591,9 @@ absl::Status ScaleImageCalculator::Process(CalculatorContext* cc) {
|
||||
const int y_size = output_width_ * output_height_;
|
||||
const int uv_size = output_width_ * output_height_ / 4;
|
||||
std::unique_ptr<uint8_t[]> yuv_data(new uint8_t[y_size + uv_size * 2]);
|
||||
uint8_t* y = yuv_data.get();
|
||||
uint8_t* u = y + y_size;
|
||||
uint8_t* v = u + uv_size;
|
||||
uint8* y = yuv_data.get();
|
||||
uint8* u = y + y_size;
|
||||
uint8* v = u + uv_size;
|
||||
RET_CHECK_EQ(0, I420Scale(yuv_image->data(0), yuv_image->stride(0),
|
||||
yuv_image->data(1), yuv_image->stride(1),
|
||||
yuv_image->data(2), yuv_image->stride(2),
|
||||
|
||||
@@ -166,7 +166,7 @@ class WarpAffineRunnerHolder<mediapipe::Image> {
|
||||
const ImageFrame image_frame(frame_ptr->Format(), frame_ptr->Width(),
|
||||
frame_ptr->Height(), frame_ptr->WidthStep(),
|
||||
const_cast<uint8_t*>(frame_ptr->PixelData()),
|
||||
[](uint8_t* data){});
|
||||
[](uint8* data){});
|
||||
ASSIGN_OR_RETURN(auto result,
|
||||
runner->Run(image_frame, matrix, size, border_mode));
|
||||
return mediapipe::Image(std::make_shared<ImageFrame>(std::move(result)));
|
||||
|
||||
@@ -101,7 +101,7 @@ void RunTest(const std::string& graph_text, const std::string& tag,
|
||||
|
||||
ImageFrame input_image(
|
||||
input.channels() == 4 ? ImageFormat::SRGBA : ImageFormat::SRGB,
|
||||
input.cols, input.rows, input.step, input.data, [](uint8_t*) {});
|
||||
input.cols, input.rows, input.step, input.data, [](uint8*) {});
|
||||
MP_ASSERT_OK(graph.AddPacketToInputStream(
|
||||
"input_image",
|
||||
MakePacket<ImageFrame>(std::move(input_image)).At(Timestamp(0))));
|
||||
|
||||
@@ -401,8 +401,8 @@ cc_library_with_tflite(
|
||||
hdrs = ["inference_calculator.h"],
|
||||
tflite_deps = [
|
||||
"//mediapipe/util/tflite:tflite_model_loader",
|
||||
"@org_tensorflow//tensorflow/lite:framework_stable",
|
||||
"@org_tensorflow//tensorflow/lite/kernels:builtin_ops",
|
||||
"@org_tensorflow//tensorflow/lite/core/shims:framework_stable",
|
||||
"@org_tensorflow//tensorflow/lite/core/shims:builtin_ops",
|
||||
],
|
||||
deps = [
|
||||
":inference_calculator_cc_proto",
|
||||
@@ -506,7 +506,7 @@ cc_library_with_tflite(
|
||||
name = "tflite_delegate_ptr",
|
||||
hdrs = ["tflite_delegate_ptr.h"],
|
||||
tflite_deps = [
|
||||
"@org_tensorflow//tensorflow/lite/c:c_api_types",
|
||||
"@org_tensorflow//tensorflow/lite/core/shims:c_api_types",
|
||||
],
|
||||
)
|
||||
|
||||
@@ -517,8 +517,8 @@ cc_library_with_tflite(
|
||||
tflite_deps = [
|
||||
":tflite_delegate_ptr",
|
||||
"//mediapipe/util/tflite:tflite_model_loader",
|
||||
"@org_tensorflow//tensorflow/lite:framework_stable",
|
||||
"@org_tensorflow//tensorflow/lite/c:c_api_types",
|
||||
"@org_tensorflow//tensorflow/lite/core/shims:c_api_types",
|
||||
"@org_tensorflow//tensorflow/lite/core/shims:framework_stable",
|
||||
],
|
||||
deps = [
|
||||
":inference_runner",
|
||||
@@ -546,8 +546,8 @@ cc_library(
|
||||
"@com_google_absl//absl/memory",
|
||||
"@com_google_absl//absl/status",
|
||||
"@com_google_absl//absl/status:statusor",
|
||||
"@org_tensorflow//tensorflow/lite:framework_stable",
|
||||
"@org_tensorflow//tensorflow/lite/c:c_api_types",
|
||||
"@org_tensorflow//tensorflow/lite/core/shims:c_api_types",
|
||||
"@org_tensorflow//tensorflow/lite/core/shims:framework_stable",
|
||||
"@org_tensorflow//tensorflow/lite/delegates/xnnpack:xnnpack_delegate",
|
||||
] + select({
|
||||
"//conditions:default": [],
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
/* Copyright 2022 The MediaPipe Authors.
|
||||
/* Copyright 2022 The MediaPipe Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
|
||||
@@ -95,8 +95,7 @@ absl::Status FrameBufferProcessor::Convert(const mediapipe::Image& input,
|
||||
static_cast<int>(range_max) == 255);
|
||||
}
|
||||
|
||||
auto input_frame =
|
||||
input.GetGpuBuffer(/*upload_to_gpu=*/false).GetReadView<FrameBuffer>();
|
||||
auto input_frame = input.GetGpuBuffer().GetReadView<FrameBuffer>();
|
||||
const auto& output_shape = output_tensor.shape();
|
||||
MP_RETURN_IF_ERROR(ValidateTensorShape(output_shape));
|
||||
FrameBuffer::Dimension output_dimension{/*width=*/output_shape.dims[2],
|
||||
|
||||
@@ -94,8 +94,8 @@ InferenceCalculator::GetOpResolverAsPacket(CalculatorContext* cc) {
|
||||
return kSideInCustomOpResolver(cc).As<tflite::OpResolver>();
|
||||
}
|
||||
return PacketAdopting<tflite::OpResolver>(
|
||||
std::make_unique<
|
||||
tflite::ops::builtin::BuiltinOpResolverWithoutDefaultDelegates>());
|
||||
std::make_unique<tflite_shims::ops::builtin::
|
||||
BuiltinOpResolverWithoutDefaultDelegates>());
|
||||
}
|
||||
|
||||
} // namespace api2
|
||||
|
||||
@@ -26,7 +26,7 @@
|
||||
#include "mediapipe/framework/formats/tensor.h"
|
||||
#include "mediapipe/util/tflite/tflite_model_loader.h"
|
||||
#include "tensorflow/lite/core/api/op_resolver.h"
|
||||
#include "tensorflow/lite/kernels/register.h"
|
||||
#include "tensorflow/lite/core/shims/cc/kernels/register.h"
|
||||
|
||||
namespace mediapipe {
|
||||
namespace api2 {
|
||||
@@ -97,8 +97,8 @@ class InferenceCalculator : public NodeIntf {
|
||||
// Deprecated. Prefers to use "OP_RESOLVER" input side packet instead.
|
||||
// TODO: Removes the "CUSTOM_OP_RESOLVER" side input after the
|
||||
// migration.
|
||||
static constexpr SideInput<tflite::ops::builtin::BuiltinOpResolver>::Optional
|
||||
kSideInCustomOpResolver{"CUSTOM_OP_RESOLVER"};
|
||||
static constexpr SideInput<tflite_shims::ops::builtin::BuiltinOpResolver>::
|
||||
Optional kSideInCustomOpResolver{"CUSTOM_OP_RESOLVER"};
|
||||
static constexpr SideInput<tflite::OpResolver>::Optional kSideInOpResolver{
|
||||
"OP_RESOLVER"};
|
||||
static constexpr SideInput<TfLiteModelPtr>::Optional kSideInModel{"MODEL"};
|
||||
|
||||
@@ -24,7 +24,7 @@
|
||||
#include "mediapipe/calculators/tensor/inference_calculator_utils.h"
|
||||
#include "mediapipe/calculators/tensor/inference_interpreter_delegate_runner.h"
|
||||
#include "mediapipe/calculators/tensor/inference_runner.h"
|
||||
#include "tensorflow/lite/interpreter.h"
|
||||
#include "tensorflow/lite/core/shims/cc/interpreter.h"
|
||||
#if defined(MEDIAPIPE_ANDROID)
|
||||
#include "tensorflow/lite/delegates/nnapi/nnapi_delegate.h"
|
||||
#endif // ANDROID
|
||||
|
||||
@@ -22,9 +22,9 @@
|
||||
#include "mediapipe/framework/formats/tensor.h"
|
||||
#include "mediapipe/framework/mediapipe_profiling.h"
|
||||
#include "mediapipe/framework/port/ret_check.h"
|
||||
#include "tensorflow/lite/c/c_api_types.h"
|
||||
#include "tensorflow/lite/interpreter.h"
|
||||
#include "tensorflow/lite/interpreter_builder.h"
|
||||
#include "tensorflow/lite/core/shims/c/c_api_types.h"
|
||||
#include "tensorflow/lite/core/shims/cc/interpreter.h"
|
||||
#include "tensorflow/lite/core/shims/cc/interpreter_builder.h"
|
||||
#include "tensorflow/lite/string_util.h"
|
||||
|
||||
#define PERFETTO_TRACK_EVENT_NAMESPACE mediapipe
|
||||
@@ -33,8 +33,8 @@ namespace mediapipe {
|
||||
|
||||
namespace {
|
||||
|
||||
using Interpreter = ::tflite::Interpreter;
|
||||
using InterpreterBuilder = ::tflite::InterpreterBuilder;
|
||||
using Interpreter = ::tflite_shims::Interpreter;
|
||||
using InterpreterBuilder = ::tflite_shims::InterpreterBuilder;
|
||||
|
||||
template <typename T>
|
||||
void CopyTensorBufferToInterpreter(const Tensor& input_tensor,
|
||||
|
||||
@@ -23,8 +23,8 @@
|
||||
#include "mediapipe/calculators/tensor/tflite_delegate_ptr.h"
|
||||
#include "mediapipe/framework/api2/packet.h"
|
||||
#include "mediapipe/util/tflite/tflite_model_loader.h"
|
||||
#include "tensorflow/lite/c/c_api_types.h"
|
||||
#include "tensorflow/lite/core/api/op_resolver.h"
|
||||
#include "tensorflow/lite/core/shims/c/c_api_types.h"
|
||||
|
||||
namespace mediapipe {
|
||||
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
/* Copyright 2022 The MediaPipe Authors.
|
||||
/* Copyright 2022 The MediaPipe Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
|
||||
@@ -18,7 +18,7 @@
|
||||
#include <functional>
|
||||
#include <memory>
|
||||
|
||||
#include "tensorflow/lite/c/c_api_types.h"
|
||||
#include "tensorflow/lite/core/shims/c/c_api_types.h"
|
||||
|
||||
namespace mediapipe {
|
||||
|
||||
|
||||
@@ -400,16 +400,6 @@ cc_library(
|
||||
# compile your binary with the flag TENSORFLOW_PROTOS=lite.
|
||||
cc_library(
|
||||
name = "tensorflow_inference_calculator_no_envelope_loader",
|
||||
deps = [
|
||||
":tensorflow_inference_calculator_for_boq",
|
||||
],
|
||||
alwayslink = 1,
|
||||
)
|
||||
|
||||
# This dependency removed tensorflow_jellyfish_deps and xprofilez_with_server because they failed
|
||||
# Boq conformance test. Weigh your use case to see if this will work for you.
|
||||
cc_library(
|
||||
name = "tensorflow_inference_calculator_for_boq",
|
||||
srcs = ["tensorflow_inference_calculator.cc"],
|
||||
deps = [
|
||||
":tensorflow_inference_calculator_cc_proto",
|
||||
@@ -595,24 +585,6 @@ cc_library(
|
||||
# See yaqs/1092546221614039040
|
||||
cc_library(
|
||||
name = "tensorflow_session_from_saved_model_generator_no_envelope_loader",
|
||||
defines = select({
|
||||
"//mediapipe:android": ["__ANDROID__"],
|
||||
"//conditions:default": [],
|
||||
}),
|
||||
deps = [
|
||||
":tensorflow_session_from_saved_model_generator_for_boq",
|
||||
] + select({
|
||||
"//conditions:default": [
|
||||
"//learning/brain/frameworks/uptc/public:uptc_session_no_envelope_loader",
|
||||
],
|
||||
}),
|
||||
alwayslink = 1,
|
||||
)
|
||||
|
||||
# Same library as tensorflow_session_from_saved_model_generator without uptc_session,
|
||||
# envelop_loader and remote_session dependencies.
|
||||
cc_library(
|
||||
name = "tensorflow_session_from_saved_model_generator_for_boq",
|
||||
srcs = ["tensorflow_session_from_saved_model_generator.cc"],
|
||||
defines = select({
|
||||
"//mediapipe:android": ["__ANDROID__"],
|
||||
|
||||
@@ -61,12 +61,12 @@ constexpr char kSessionBundleTag[] = "SESSION_BUNDLE";
|
||||
// overload GPU/TPU/...
|
||||
class SimpleSemaphore {
|
||||
public:
|
||||
explicit SimpleSemaphore(uint32_t initial_count) : count_(initial_count) {}
|
||||
explicit SimpleSemaphore(uint32 initial_count) : count_(initial_count) {}
|
||||
SimpleSemaphore(const SimpleSemaphore&) = delete;
|
||||
SimpleSemaphore(SimpleSemaphore&&) = delete;
|
||||
|
||||
// Acquires the semaphore by certain amount.
|
||||
void Acquire(uint32_t amount) {
|
||||
void Acquire(uint32 amount) {
|
||||
mutex_.Lock();
|
||||
while (count_ < amount) {
|
||||
cond_.Wait(&mutex_);
|
||||
@@ -76,7 +76,7 @@ class SimpleSemaphore {
|
||||
}
|
||||
|
||||
// Releases the semaphore by certain amount.
|
||||
void Release(uint32_t amount) {
|
||||
void Release(uint32 amount) {
|
||||
mutex_.Lock();
|
||||
count_ += amount;
|
||||
cond_.SignalAll();
|
||||
@@ -84,7 +84,7 @@ class SimpleSemaphore {
|
||||
}
|
||||
|
||||
private:
|
||||
uint32_t count_;
|
||||
uint32 count_;
|
||||
absl::Mutex mutex_;
|
||||
absl::CondVar cond_;
|
||||
};
|
||||
@@ -488,7 +488,7 @@ class TensorFlowInferenceCalculator : public CalculatorBase {
|
||||
// necessary.
|
||||
absl::Status OutputBatch(CalculatorContext* cc,
|
||||
std::unique_ptr<InferenceState> inference_state) {
|
||||
const int64_t start_time = absl::ToUnixMicros(clock_->TimeNow());
|
||||
const int64 start_time = absl::ToUnixMicros(clock_->TimeNow());
|
||||
std::vector<std::pair<mediapipe::ProtoString, tf::Tensor>> input_tensors;
|
||||
|
||||
for (auto& keyed_tensors : inference_state->input_tensor_batches_) {
|
||||
@@ -544,7 +544,7 @@ class TensorFlowInferenceCalculator : public CalculatorBase {
|
||||
get_session_run_throttle(options_.max_concurrent_session_runs());
|
||||
session_run_throttle->Acquire(1);
|
||||
}
|
||||
const int64_t run_start_time = absl::ToUnixMicros(clock_->TimeNow());
|
||||
const int64 run_start_time = absl::ToUnixMicros(clock_->TimeNow());
|
||||
tf::Status tf_status;
|
||||
{
|
||||
#if !defined(MEDIAPIPE_MOBILE) && !defined(__APPLE__)
|
||||
@@ -562,7 +562,7 @@ class TensorFlowInferenceCalculator : public CalculatorBase {
|
||||
// informative error message.
|
||||
RET_CHECK(tf_status.ok()) << "Run failed: " << tf_status.ToString();
|
||||
|
||||
const int64_t run_end_time = absl::ToUnixMicros(clock_->TimeNow());
|
||||
const int64 run_end_time = absl::ToUnixMicros(clock_->TimeNow());
|
||||
cc->GetCounter(kTotalSessionRunsTimeUsecsCounterSuffix)
|
||||
->IncrementBy(run_end_time - run_start_time);
|
||||
cc->GetCounter(kTotalNumSessionRunsCounterSuffix)->Increment();
|
||||
@@ -611,7 +611,7 @@ class TensorFlowInferenceCalculator : public CalculatorBase {
|
||||
}
|
||||
|
||||
// Get end time and report.
|
||||
const int64_t end_time = absl::ToUnixMicros(clock_->TimeNow());
|
||||
const int64 end_time = absl::ToUnixMicros(clock_->TimeNow());
|
||||
cc->GetCounter(kTotalUsecsCounterSuffix)
|
||||
->IncrementBy(end_time - start_time);
|
||||
cc->GetCounter(kTotalProcessedTimestampsCounterSuffix)
|
||||
@@ -650,7 +650,7 @@ class TensorFlowInferenceCalculator : public CalculatorBase {
|
||||
|
||||
// The static singleton semaphore to throttle concurrent session runs.
|
||||
static SimpleSemaphore* get_session_run_throttle(
|
||||
int32_t max_concurrent_session_runs) {
|
||||
int32 max_concurrent_session_runs) {
|
||||
static SimpleSemaphore* session_run_throttle =
|
||||
new SimpleSemaphore(max_concurrent_session_runs);
|
||||
return session_run_throttle;
|
||||
|
||||
@@ -197,15 +197,15 @@ class UnpackMediaSequenceCalculator : public CalculatorBase {
|
||||
// timestamp and the associated feature. This information is used in process
|
||||
// to output batches of packets in order.
|
||||
timestamps_.clear();
|
||||
int64_t last_timestamp_seen = Timestamp::PreStream().Value();
|
||||
int64 last_timestamp_seen = Timestamp::PreStream().Value();
|
||||
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();
|
||||
int64_t recent_timestamp = Timestamp::PreStream().Value();
|
||||
int64 recent_timestamp = Timestamp::PreStream().Value();
|
||||
for (int i = 0; i < map_kv.second.feature_size(); ++i) {
|
||||
int64_t next_timestamp =
|
||||
int64 next_timestamp =
|
||||
mpms::GetInt64sAt(*sequence_, map_kv.first, i).Get(0);
|
||||
RET_CHECK_GT(next_timestamp, recent_timestamp)
|
||||
<< "Timestamps must be sequential. If you're seeing this message "
|
||||
@@ -361,8 +361,8 @@ class UnpackMediaSequenceCalculator : public CalculatorBase {
|
||||
// any particular call to Process(). At the every end, we output the
|
||||
// poststream packets. If we only have poststream packets,
|
||||
// last_timestamp_key_ will be empty.
|
||||
int64_t start_timestamp = 0;
|
||||
int64_t end_timestamp = 0;
|
||||
int64 start_timestamp = 0;
|
||||
int64 end_timestamp = 0;
|
||||
if (last_timestamp_key_.empty() || process_poststream_) {
|
||||
process_poststream_ = true;
|
||||
start_timestamp = Timestamp::PostStream().Value();
|
||||
@@ -481,14 +481,14 @@ class UnpackMediaSequenceCalculator : public CalculatorBase {
|
||||
// Store a map from the keys for each stream to the timestamps for each
|
||||
// key. This allows us to identify which packets to output for each stream
|
||||
// for timestamps within a given time window.
|
||||
std::map<std::string, std::vector<int64_t>> timestamps_;
|
||||
std::map<std::string, std::vector<int64>> timestamps_;
|
||||
// Store the stream with the latest timestamp in the SequenceExample.
|
||||
std::string last_timestamp_key_;
|
||||
// Store the index of the current timestamp. Will be less than
|
||||
// timestamps_[last_timestamp_key_].size().
|
||||
int current_timestamp_index_;
|
||||
// Store the very first timestamp, so we output everything on the first frame.
|
||||
int64_t first_timestamp_seen_;
|
||||
int64 first_timestamp_seen_;
|
||||
// List of keypoint names.
|
||||
std::vector<std::string> keypoint_names_;
|
||||
// Default keypoint location when missing.
|
||||
|
||||
@@ -54,7 +54,7 @@ class VectorToTensorFloatCalculatorTest : public ::testing::Test {
|
||||
}
|
||||
}
|
||||
|
||||
const int64_t time = 1234;
|
||||
const int64 time = 1234;
|
||||
runner_->MutableInputs()->Index(0).packets.push_back(
|
||||
Adopt(input.release()).At(Timestamp(time)));
|
||||
|
||||
@@ -91,7 +91,7 @@ TEST_F(VectorToTensorFloatCalculatorTest, ConvertsFromVectorFloat) {
|
||||
// 2^i can be represented exactly in floating point numbers if 'i' is small.
|
||||
input->at(i) = static_cast<float>(1 << i);
|
||||
}
|
||||
const int64_t time = 1234;
|
||||
const int64 time = 1234;
|
||||
runner_->MutableInputs()->Index(0).packets.push_back(
|
||||
Adopt(input.release()).At(Timestamp(time)));
|
||||
|
||||
|
||||
@@ -1285,14 +1285,12 @@ cc_library(
|
||||
srcs = ["flat_color_image_calculator.cc"],
|
||||
deps = [
|
||||
":flat_color_image_calculator_cc_proto",
|
||||
"//mediapipe/framework:calculator_contract",
|
||||
"//mediapipe/framework:calculator_framework",
|
||||
"//mediapipe/framework/api2:node",
|
||||
"//mediapipe/framework/formats:image",
|
||||
"//mediapipe/framework/formats:image_frame",
|
||||
"//mediapipe/framework/formats:image_frame_opencv",
|
||||
"//mediapipe/framework/port:opencv_core",
|
||||
"//mediapipe/framework/port:ret_check",
|
||||
"//mediapipe/util:color_cc_proto",
|
||||
"@com_google_absl//absl/status",
|
||||
"@com_google_absl//absl/strings",
|
||||
|
||||
@@ -471,7 +471,7 @@ absl::Status AnnotationOverlayCalculator::CreateRenderTargetCpu(
|
||||
auto input_mat = formats::MatView(&input_frame);
|
||||
if (input_frame.Format() == ImageFormat::GRAY8) {
|
||||
cv::Mat rgb_mat;
|
||||
cv::cvtColor(input_mat, rgb_mat, cv::COLOR_GRAY2RGB);
|
||||
cv::cvtColor(input_mat, rgb_mat, CV_GRAY2RGB);
|
||||
rgb_mat.copyTo(*image_mat);
|
||||
} else {
|
||||
input_mat.copyTo(*image_mat);
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
/* Copyright 2022 The MediaPipe Authors.
|
||||
/* Copyright 2022 The MediaPipe Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
|
||||
@@ -15,13 +15,14 @@
|
||||
#include <memory>
|
||||
|
||||
#include "absl/status/status.h"
|
||||
#include "absl/strings/str_cat.h"
|
||||
#include "mediapipe/calculators/util/flat_color_image_calculator.pb.h"
|
||||
#include "mediapipe/framework/api2/node.h"
|
||||
#include "mediapipe/framework/calculator_contract.h"
|
||||
#include "mediapipe/framework/calculator_framework.h"
|
||||
#include "mediapipe/framework/formats/image.h"
|
||||
#include "mediapipe/framework/formats/image_frame.h"
|
||||
#include "mediapipe/framework/formats/image_frame_opencv.h"
|
||||
#include "mediapipe/framework/port/opencv_core_inc.h"
|
||||
#include "mediapipe/util/color.pb.h"
|
||||
|
||||
namespace mediapipe {
|
||||
@@ -31,7 +32,6 @@ namespace {
|
||||
using ::mediapipe::api2::Input;
|
||||
using ::mediapipe::api2::Node;
|
||||
using ::mediapipe::api2::Output;
|
||||
using ::mediapipe::api2::SideOutput;
|
||||
} // namespace
|
||||
|
||||
// A calculator for generating an image filled with a single color.
|
||||
@@ -45,8 +45,7 @@ using ::mediapipe::api2::SideOutput;
|
||||
//
|
||||
// Outputs:
|
||||
// IMAGE (Image)
|
||||
// Image filled with the requested color. Can be either an output_stream
|
||||
// or an output_side_packet.
|
||||
// Image filled with the requested color.
|
||||
//
|
||||
// Example useage:
|
||||
// node {
|
||||
@@ -69,10 +68,9 @@ class FlatColorImageCalculator : public Node {
|
||||
public:
|
||||
static constexpr Input<Image>::Optional kInImage{"IMAGE"};
|
||||
static constexpr Input<Color>::Optional kInColor{"COLOR"};
|
||||
static constexpr Output<Image>::Optional kOutImage{"IMAGE"};
|
||||
static constexpr SideOutput<Image>::Optional kOutSideImage{"IMAGE"};
|
||||
static constexpr Output<Image> kOutImage{"IMAGE"};
|
||||
|
||||
MEDIAPIPE_NODE_CONTRACT(kInImage, kInColor, kOutImage, kOutSideImage);
|
||||
MEDIAPIPE_NODE_CONTRACT(kInImage, kInColor, kOutImage);
|
||||
|
||||
static absl::Status UpdateContract(CalculatorContract* cc) {
|
||||
const auto& options = cc->Options<FlatColorImageCalculatorOptions>();
|
||||
@@ -83,13 +81,6 @@ class FlatColorImageCalculator : public Node {
|
||||
RET_CHECK(kInColor(cc).IsConnected() ^ options.has_color())
|
||||
<< "Either set COLOR input stream, or set through options";
|
||||
|
||||
RET_CHECK(kOutImage(cc).IsConnected() ^ kOutSideImage(cc).IsConnected())
|
||||
<< "Set IMAGE either as output stream, or as output side packet";
|
||||
|
||||
RET_CHECK(!kOutSideImage(cc).IsConnected() ||
|
||||
(options.has_output_height() && options.has_output_width()))
|
||||
<< "Set size through options, when setting IMAGE as output side packet";
|
||||
|
||||
return absl::OkStatus();
|
||||
}
|
||||
|
||||
@@ -97,9 +88,6 @@ class FlatColorImageCalculator : public Node {
|
||||
absl::Status Process(CalculatorContext* cc) override;
|
||||
|
||||
private:
|
||||
std::optional<std::shared_ptr<ImageFrame>> CreateOutputFrame(
|
||||
CalculatorContext* cc);
|
||||
|
||||
bool use_dimension_from_option_ = false;
|
||||
bool use_color_from_option_ = false;
|
||||
};
|
||||
@@ -108,31 +96,10 @@ MEDIAPIPE_REGISTER_NODE(FlatColorImageCalculator);
|
||||
absl::Status FlatColorImageCalculator::Open(CalculatorContext* cc) {
|
||||
use_dimension_from_option_ = !kInImage(cc).IsConnected();
|
||||
use_color_from_option_ = !kInColor(cc).IsConnected();
|
||||
|
||||
if (!kOutImage(cc).IsConnected()) {
|
||||
std::optional<std::shared_ptr<ImageFrame>> output_frame =
|
||||
CreateOutputFrame(cc);
|
||||
if (output_frame.has_value()) {
|
||||
kOutSideImage(cc).Set(Image(output_frame.value()));
|
||||
}
|
||||
}
|
||||
return absl::OkStatus();
|
||||
}
|
||||
|
||||
absl::Status FlatColorImageCalculator::Process(CalculatorContext* cc) {
|
||||
if (kOutImage(cc).IsConnected()) {
|
||||
std::optional<std::shared_ptr<ImageFrame>> output_frame =
|
||||
CreateOutputFrame(cc);
|
||||
if (output_frame.has_value()) {
|
||||
kOutImage(cc).Send(Image(output_frame.value()));
|
||||
}
|
||||
}
|
||||
|
||||
return absl::OkStatus();
|
||||
}
|
||||
|
||||
std::optional<std::shared_ptr<ImageFrame>>
|
||||
FlatColorImageCalculator::CreateOutputFrame(CalculatorContext* cc) {
|
||||
const auto& options = cc->Options<FlatColorImageCalculatorOptions>();
|
||||
|
||||
int output_height = -1;
|
||||
@@ -145,7 +112,7 @@ FlatColorImageCalculator::CreateOutputFrame(CalculatorContext* cc) {
|
||||
output_height = input_image.height();
|
||||
output_width = input_image.width();
|
||||
} else {
|
||||
return std::nullopt;
|
||||
return absl::OkStatus();
|
||||
}
|
||||
|
||||
Color color;
|
||||
@@ -154,7 +121,7 @@ FlatColorImageCalculator::CreateOutputFrame(CalculatorContext* cc) {
|
||||
} else if (!kInColor(cc).IsEmpty()) {
|
||||
color = kInColor(cc).Get();
|
||||
} else {
|
||||
return std::nullopt;
|
||||
return absl::OkStatus();
|
||||
}
|
||||
|
||||
auto output_frame = std::make_shared<ImageFrame>(ImageFormat::SRGB,
|
||||
@@ -163,7 +130,9 @@ FlatColorImageCalculator::CreateOutputFrame(CalculatorContext* cc) {
|
||||
|
||||
output_mat.setTo(cv::Scalar(color.r(), color.g(), color.b()));
|
||||
|
||||
return output_frame;
|
||||
kOutImage(cc).Send(Image(output_frame));
|
||||
|
||||
return absl::OkStatus();
|
||||
}
|
||||
|
||||
} // namespace mediapipe
|
||||
|
||||
@@ -113,35 +113,6 @@ TEST(FlatColorImageCalculatorTest, SpecifyDimensionThroughOptions) {
|
||||
}
|
||||
}
|
||||
|
||||
TEST(FlatColorImageCalculatorTest, ProducesOutputSidePacket) {
|
||||
CalculatorRunner runner(R"pb(
|
||||
calculator: "FlatColorImageCalculator"
|
||||
output_side_packet: "IMAGE:out_packet"
|
||||
options {
|
||||
[mediapipe.FlatColorImageCalculatorOptions.ext] {
|
||||
output_width: 1
|
||||
output_height: 1
|
||||
color: {
|
||||
r: 100,
|
||||
g: 200,
|
||||
b: 255,
|
||||
}
|
||||
}
|
||||
}
|
||||
)pb");
|
||||
|
||||
MP_ASSERT_OK(runner.Run());
|
||||
|
||||
const auto& image = runner.OutputSidePackets().Tag(kImageTag).Get<Image>();
|
||||
EXPECT_EQ(image.width(), 1);
|
||||
EXPECT_EQ(image.height(), 1);
|
||||
auto image_frame = image.GetImageFrameSharedPtr();
|
||||
const uint8_t* pixel_data = image_frame->PixelData();
|
||||
EXPECT_EQ(pixel_data[0], 100);
|
||||
EXPECT_EQ(pixel_data[1], 200);
|
||||
EXPECT_EQ(pixel_data[2], 255);
|
||||
}
|
||||
|
||||
TEST(FlatColorImageCalculatorTest, FailureMissingDimension) {
|
||||
CalculatorRunner runner(R"pb(
|
||||
calculator: "FlatColorImageCalculator"
|
||||
@@ -235,56 +206,5 @@ TEST(FlatColorImageCalculatorTest, FailureDuplicateColor) {
|
||||
HasSubstr("Either set COLOR input stream"));
|
||||
}
|
||||
|
||||
TEST(FlatColorImageCalculatorTest, FailureDuplicateOutputs) {
|
||||
CalculatorRunner runner(R"pb(
|
||||
calculator: "FlatColorImageCalculator"
|
||||
output_stream: "IMAGE:out_image"
|
||||
output_side_packet: "IMAGE:out_packet"
|
||||
options {
|
||||
[mediapipe.FlatColorImageCalculatorOptions.ext] {
|
||||
output_width: 1
|
||||
output_height: 1
|
||||
color: {
|
||||
r: 100,
|
||||
g: 200,
|
||||
b: 255,
|
||||
}
|
||||
}
|
||||
}
|
||||
)pb");
|
||||
|
||||
ASSERT_THAT(
|
||||
runner.Run().message(),
|
||||
HasSubstr("Set IMAGE either as output stream, or as output side packet"));
|
||||
}
|
||||
|
||||
TEST(FlatColorImageCalculatorTest, FailureSettingInputImageOnOutputSidePacket) {
|
||||
CalculatorRunner runner(R"pb(
|
||||
calculator: "FlatColorImageCalculator"
|
||||
input_stream: "IMAGE:image"
|
||||
output_side_packet: "IMAGE:out_packet"
|
||||
options {
|
||||
[mediapipe.FlatColorImageCalculatorOptions.ext] {
|
||||
color: {
|
||||
r: 100,
|
||||
g: 200,
|
||||
b: 255,
|
||||
}
|
||||
}
|
||||
}
|
||||
)pb");
|
||||
|
||||
auto image_frame = std::make_shared<ImageFrame>(ImageFormat::SRGB,
|
||||
kImageWidth, kImageHeight);
|
||||
|
||||
for (int ts = 0; ts < 3; ++ts) {
|
||||
runner.MutableInputs()->Tag(kImageTag).packets.push_back(
|
||||
MakePacket<Image>(image_frame).At(Timestamp(ts)));
|
||||
}
|
||||
ASSERT_THAT(runner.Run().message(),
|
||||
HasSubstr("Set size through options, when setting IMAGE as "
|
||||
"output side packet"));
|
||||
}
|
||||
|
||||
} // namespace
|
||||
} // namespace mediapipe
|
||||
|
||||
@@ -18,9 +18,6 @@ package mediapipe;
|
||||
|
||||
import "mediapipe/framework/calculator.proto";
|
||||
|
||||
option java_package = "com.google.mediapipe.calculator.proto";
|
||||
option java_outer_classname = "LogicCalculatorOptionsProto";
|
||||
|
||||
message LogicCalculatorOptions {
|
||||
extend CalculatorOptions {
|
||||
optional LogicCalculatorOptions ext = 338731246;
|
||||
|
||||
@@ -48,7 +48,6 @@ cc_library(
|
||||
"//mediapipe/framework/port:opencv_video",
|
||||
"//mediapipe/framework/port:parse_text_proto",
|
||||
"//mediapipe/framework/port:status",
|
||||
"//mediapipe/util:resource_util",
|
||||
"@com_google_absl//absl/flags:flag",
|
||||
"@com_google_absl//absl/flags:parse",
|
||||
],
|
||||
@@ -74,7 +73,6 @@ cc_library(
|
||||
"//mediapipe/gpu:gl_calculator_helper",
|
||||
"//mediapipe/gpu:gpu_buffer",
|
||||
"//mediapipe/gpu:gpu_shared_data_internal",
|
||||
"//mediapipe/util:resource_util",
|
||||
"@com_google_absl//absl/flags:flag",
|
||||
"@com_google_absl//absl/flags:parse",
|
||||
],
|
||||
|
||||
@@ -28,8 +28,11 @@
|
||||
#include "mediapipe/framework/port/ret_check.h"
|
||||
#include "mediapipe/framework/port/status.h"
|
||||
|
||||
using mediapipe::Adopt;
|
||||
using mediapipe::CalculatorBase;
|
||||
using mediapipe::ImageFrame;
|
||||
using mediapipe::PacketTypeSet;
|
||||
using mediapipe::autoflip::Border;
|
||||
|
||||
constexpr char kDetectedBorders[] = "DETECTED_BORDERS";
|
||||
constexpr int kMinBorderDistance = 5;
|
||||
|
||||
@@ -28,12 +28,16 @@
|
||||
#include "mediapipe/framework/port/status.h"
|
||||
#include "mediapipe/framework/port/status_matchers.h"
|
||||
|
||||
using mediapipe::Adopt;
|
||||
using mediapipe::CalculatorGraphConfig;
|
||||
using mediapipe::CalculatorRunner;
|
||||
using mediapipe::ImageFormat;
|
||||
using mediapipe::ImageFrame;
|
||||
using mediapipe::Packet;
|
||||
using mediapipe::PacketTypeSet;
|
||||
using mediapipe::ParseTextProtoOrDie;
|
||||
using mediapipe::Timestamp;
|
||||
using mediapipe::autoflip::Border;
|
||||
|
||||
namespace mediapipe {
|
||||
namespace autoflip {
|
||||
|
||||
@@ -31,11 +31,14 @@
|
||||
#include "mediapipe/framework/port/status.h"
|
||||
#include "mediapipe/framework/port/status_matchers.h"
|
||||
|
||||
using mediapipe::Adopt;
|
||||
using mediapipe::CalculatorGraphConfig;
|
||||
using mediapipe::CalculatorRunner;
|
||||
using mediapipe::ImageFormat;
|
||||
using mediapipe::ImageFrame;
|
||||
using mediapipe::PacketTypeSet;
|
||||
using mediapipe::ParseTextProtoOrDie;
|
||||
using mediapipe::Timestamp;
|
||||
|
||||
namespace mediapipe {
|
||||
namespace autoflip {
|
||||
|
||||
@@ -28,6 +28,8 @@
|
||||
using mediapipe::Packet;
|
||||
using mediapipe::PacketTypeSet;
|
||||
using mediapipe::autoflip::DetectionSet;
|
||||
using mediapipe::autoflip::SalientRegion;
|
||||
using mediapipe::autoflip::SignalType;
|
||||
|
||||
constexpr char kIsShotBoundaryTag[] = "IS_SHOT_BOUNDARY";
|
||||
constexpr char kSignalInputsTag[] = "SIGNAL";
|
||||
|
||||
@@ -190,16 +190,14 @@ TEST(PaddingEffectGeneratorTest, ScaleToMultipleOfTwo) {
|
||||
double target_aspect_ratio = 0.5;
|
||||
int expect_width = 14;
|
||||
int expect_height = input_height;
|
||||
ImageFrame test_frame(/*format=*/ImageFormat::SRGB, input_width,
|
||||
input_height);
|
||||
cv::Mat mat = formats::MatView(&test_frame);
|
||||
mat = cv::Scalar(0, 0, 0);
|
||||
auto test_frame = absl::make_unique<ImageFrame>(/*format=*/ImageFormat::SRGB,
|
||||
input_width, input_height);
|
||||
|
||||
PaddingEffectGenerator generator(test_frame.Width(), test_frame.Height(),
|
||||
PaddingEffectGenerator generator(test_frame->Width(), test_frame->Height(),
|
||||
target_aspect_ratio,
|
||||
/*scale_to_multiple_of_two=*/true);
|
||||
ImageFrame result_frame;
|
||||
MP_ASSERT_OK(generator.Process(test_frame, 0.3, 40, 0.0, &result_frame));
|
||||
MP_ASSERT_OK(generator.Process(*test_frame, 0.3, 40, 0.0, &result_frame));
|
||||
EXPECT_EQ(result_frame.Width(), expect_width);
|
||||
EXPECT_EQ(result_frame.Height(), expect_height);
|
||||
}
|
||||
|
||||
@@ -26,7 +26,6 @@
|
||||
#include "mediapipe/framework/port/opencv_video_inc.h"
|
||||
#include "mediapipe/framework/port/parse_text_proto.h"
|
||||
#include "mediapipe/framework/port/status.h"
|
||||
#include "mediapipe/util/resource_util.h"
|
||||
|
||||
constexpr char kInputStream[] = "input_video";
|
||||
constexpr char kOutputStream[] = "output_video";
|
||||
|
||||
@@ -30,7 +30,6 @@
|
||||
#include "mediapipe/gpu/gl_calculator_helper.h"
|
||||
#include "mediapipe/gpu/gpu_buffer.h"
|
||||
#include "mediapipe/gpu/gpu_shared_data_internal.h"
|
||||
#include "mediapipe/util/resource_util.h"
|
||||
|
||||
constexpr char kInputStream[] = "input_video";
|
||||
constexpr char kOutputStream[] = "output_video";
|
||||
|
||||
@@ -147,18 +147,12 @@ def main():
|
||||
f"Looking for profiles for app ids with prefix '{bundle_id_prefix}' in '{profile_dir}'"
|
||||
)
|
||||
|
||||
profiles_found = False
|
||||
for name in os.listdir(profile_dir):
|
||||
if not name.endswith(".mobileprovision"):
|
||||
continue
|
||||
profiles_found = True
|
||||
profile_path = os.path.join(profile_dir, name)
|
||||
process_profile(profile_path, our_app_id_re)
|
||||
|
||||
if not profiles_found:
|
||||
print("Error: Unable to find any provisioning profiles " +
|
||||
f"(*.mobileprovision files) in '{profile_dir}'")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
|
||||
@@ -33,9 +33,7 @@ bzl_library(
|
||||
srcs = [
|
||||
"transitive_protos.bzl",
|
||||
],
|
||||
visibility = [
|
||||
"//mediapipe/framework:__subpackages__",
|
||||
],
|
||||
visibility = ["//mediapipe/framework:__subpackages__"],
|
||||
)
|
||||
|
||||
bzl_library(
|
||||
|
||||
@@ -52,7 +52,7 @@ int select = cc->Inputs().Tag(kSelectTag).Get<int>();
|
||||
write
|
||||
|
||||
```
|
||||
int select = kSelect(cc).Get(); // alternative: *kSelect(cc)
|
||||
int select = kSelectTag(cc).Get(); // alternative: *kSelectTag(cc)
|
||||
```
|
||||
|
||||
Sets of multiple ports can be declared with `::Multiple`. Note, also, that a tag
|
||||
|
||||
@@ -223,16 +223,6 @@ class SourceImpl {
|
||||
return !(*this == other);
|
||||
}
|
||||
|
||||
Src& SetName(const char* name) {
|
||||
base_->name_ = std::string(name);
|
||||
return *this;
|
||||
}
|
||||
|
||||
Src& SetName(absl::string_view name) {
|
||||
base_->name_ = std::string(name);
|
||||
return *this;
|
||||
}
|
||||
|
||||
Src& SetName(std::string name) {
|
||||
base_->name_ = std::move(name);
|
||||
return *this;
|
||||
|
||||
@@ -19,6 +19,8 @@ namespace mediapipe {
|
||||
namespace api2 {
|
||||
namespace test {
|
||||
|
||||
using testing::ElementsAre;
|
||||
|
||||
// Returns the packet values for a vector of Packets.
|
||||
template <typename T>
|
||||
std::vector<T> PacketValues(const std::vector<mediapipe::Packet>& packets) {
|
||||
|
||||
@@ -467,11 +467,6 @@ class SideFallbackT : public Base {
|
||||
// CalculatorContext (e.g. kOut(cc)), and provides a type-safe interface to
|
||||
// OutputStreamShard. Like that class, this class will not be usually named in
|
||||
// calculator code, but used as a temporary object (e.g. kOut(cc).Send(...)).
|
||||
//
|
||||
// If not connected (!IsConnected()) SetNextTimestampBound is safe to call and
|
||||
// does nothing.
|
||||
// All the sub-classes that define Send should implement it to be safe to to
|
||||
// call if not connected and do nothing in such case.
|
||||
class OutputShardAccessBase {
|
||||
public:
|
||||
OutputShardAccessBase(const CalculatorContext& cc, OutputStreamShard* output)
|
||||
|
||||
@@ -23,13 +23,15 @@ package mediapipe;
|
||||
option java_package = "com.google.mediapipe.proto";
|
||||
option java_outer_classname = "CalculatorOptionsProto";
|
||||
|
||||
// Options for Calculators, DEPRECATED. New calculators are encouraged to use
|
||||
// proto3 syntax options:
|
||||
// Options for Calculators. Each Calculator implementation should
|
||||
// have its own options proto, which should look like this:
|
||||
//
|
||||
// message MyCalculatorOptions {
|
||||
// // proto3 does not expect "optional"
|
||||
// string field_needed_by_my_calculator = 1;
|
||||
// int32 another_field = 2;
|
||||
// extend CalculatorOptions {
|
||||
// optional MyCalculatorOptions ext = <unique id, e.g. the CL#>;
|
||||
// }
|
||||
// optional string field_needed_by_my_calculator = 1;
|
||||
// optional int32 another_field = 2;
|
||||
// // etc
|
||||
// }
|
||||
message CalculatorOptions {
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
/* Copyright 2023 The MediaPipe Authors.
|
||||
/* Copyright 2023 The MediaPipe Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
/* Copyright 2023 The MediaPipe Authors.
|
||||
/* Copyright 2023 The MediaPipe Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
|
||||
@@ -113,11 +113,11 @@ class Image {
|
||||
#endif // MEDIAPIPE_GPU_BUFFER_USE_CV_PIXEL_BUFFER
|
||||
#endif // !MEDIAPIPE_DISABLE_GPU
|
||||
|
||||
// Provides access to the underlying GpuBuffer storage.
|
||||
// Automatically uploads from CPU to GPU if needed and requested through the
|
||||
// `upload_to_gpu` argument.
|
||||
const mediapipe::GpuBuffer GetGpuBuffer(bool upload_to_gpu = true) const {
|
||||
if (!use_gpu_ && upload_to_gpu) ConvertToGpu();
|
||||
// Get a GPU view. Automatically uploads from CPU if needed.
|
||||
const mediapipe::GpuBuffer GetGpuBuffer() const {
|
||||
#if !MEDIAPIPE_DISABLE_GPU
|
||||
if (use_gpu_ == false) ConvertToGpu();
|
||||
#endif // !MEDIAPIPE_DISABLE_GPU
|
||||
return gpu_buffer_;
|
||||
}
|
||||
|
||||
|
||||
@@ -1,31 +0,0 @@
|
||||
"""Rules implementation for mediapipe_proto_alias.bzl, do not load directly."""
|
||||
|
||||
def _copy_header_impl(ctx):
|
||||
source = ctx.attr.source.replace("//", "").replace(":", "/")
|
||||
files = []
|
||||
for dep in ctx.attr.deps:
|
||||
for header in dep[CcInfo].compilation_context.direct_headers:
|
||||
if (header.short_path == source):
|
||||
files.append(header)
|
||||
if len(files) != 1:
|
||||
fail("Expected exactly 1 source, got ", str(files))
|
||||
dest_file = ctx.actions.declare_file(ctx.attr.filename)
|
||||
|
||||
# Use expand_template() with no substitutions as a simple copier.
|
||||
ctx.actions.expand_template(
|
||||
template = files[0],
|
||||
output = dest_file,
|
||||
substitutions = {},
|
||||
)
|
||||
return [DefaultInfo(files = depset([dest_file]))]
|
||||
|
||||
copy_header = rule(
|
||||
implementation = _copy_header_impl,
|
||||
attrs = {
|
||||
"filename": attr.string(),
|
||||
"source": attr.string(),
|
||||
"deps": attr.label_list(providers = [CcInfo]),
|
||||
},
|
||||
output_to_genfiles = True,
|
||||
outputs = {"out": "%{filename}"},
|
||||
)
|
||||
@@ -15,7 +15,9 @@
|
||||
|
||||
licenses(["notice"])
|
||||
|
||||
package(default_visibility = ["//mediapipe/framework:__subpackages__"])
|
||||
package(
|
||||
default_visibility = ["//mediapipe/framework:__subpackages__"],
|
||||
)
|
||||
|
||||
cc_library(
|
||||
name = "simple_calculator",
|
||||
|
||||
@@ -310,7 +310,7 @@ class Scheduler {
|
||||
absl::Mutex state_mutex_;
|
||||
|
||||
// Current state of the scheduler.
|
||||
std::atomic<State> state_ = STATE_NOT_STARTED;
|
||||
std::atomic<State> state_ = ATOMIC_VAR_INIT(STATE_NOT_STARTED);
|
||||
|
||||
// True if all graph input streams are closed.
|
||||
bool graph_input_streams_closed_ ABSL_GUARDED_BY(state_mutex_) = false;
|
||||
|
||||
@@ -131,9 +131,9 @@ class FixedSizeInputStreamHandler : public DefaultInputStreamHandler {
|
||||
ABSL_EXCLUSIVE_LOCKS_REQUIRED(erase_mutex_) {
|
||||
// Record the most recent first kept timestamp on any stream.
|
||||
for (const auto& stream : input_stream_managers_) {
|
||||
int32_t queue_size = (stream->QueueSize() >= trigger_queue_size_)
|
||||
? target_queue_size_
|
||||
: trigger_queue_size_ - 1;
|
||||
int32 queue_size = (stream->QueueSize() >= trigger_queue_size_)
|
||||
? target_queue_size_
|
||||
: trigger_queue_size_ - 1;
|
||||
if (stream->QueueSize() > queue_size) {
|
||||
kept_timestamp_ = std::max(
|
||||
kept_timestamp_, stream->GetMinTimestampAmongNLatest(queue_size + 1)
|
||||
@@ -214,8 +214,8 @@ class FixedSizeInputStreamHandler : public DefaultInputStreamHandler {
|
||||
}
|
||||
|
||||
private:
|
||||
int32_t trigger_queue_size_;
|
||||
int32_t target_queue_size_;
|
||||
int32 trigger_queue_size_;
|
||||
int32 target_queue_size_;
|
||||
bool fixed_min_size_;
|
||||
// Indicates that GetNodeReadiness has returned kReadyForProcess once, and
|
||||
// the corresponding call to FillInputSet has not yet completed.
|
||||
|
||||
@@ -30,15 +30,15 @@ namespace mediapipe {
|
||||
|
||||
namespace {
|
||||
|
||||
const int64_t kMaxPacketId = 100;
|
||||
const int64_t kSlowCalculatorRate = 10;
|
||||
const int64 kMaxPacketId = 100;
|
||||
const int64 kSlowCalculatorRate = 10;
|
||||
|
||||
// Rate limiter for TestSlowCalculator.
|
||||
ABSL_CONST_INIT absl::Mutex g_source_mutex(absl::kConstInit);
|
||||
int64_t g_source_counter ABSL_GUARDED_BY(g_source_mutex);
|
||||
int64 g_source_counter ABSL_GUARDED_BY(g_source_mutex);
|
||||
|
||||
// Rate limiter for TestSourceCalculator.
|
||||
int64_t g_slow_counter ABSL_GUARDED_BY(g_source_mutex);
|
||||
int64 g_slow_counter ABSL_GUARDED_BY(g_source_mutex);
|
||||
|
||||
// Flag that indicates that the source is done.
|
||||
bool g_source_done ABSL_GUARDED_BY(g_source_mutex);
|
||||
@@ -47,7 +47,7 @@ class TestSourceCalculator : public CalculatorBase {
|
||||
public:
|
||||
TestSourceCalculator() : current_packet_id_(0) {}
|
||||
static absl::Status GetContract(CalculatorContract* cc) {
|
||||
cc->Outputs().Index(0).Set<int64_t>();
|
||||
cc->Outputs().Index(0).Set<int64>();
|
||||
return absl::OkStatus();
|
||||
}
|
||||
absl::Status Open(CalculatorContext* cc) override {
|
||||
@@ -62,7 +62,7 @@ class TestSourceCalculator : public CalculatorBase {
|
||||
g_source_done = true;
|
||||
return tool::StatusStop();
|
||||
}
|
||||
cc->Outputs().Index(0).Add(new int64_t(0), Timestamp(current_packet_id_));
|
||||
cc->Outputs().Index(0).Add(new int64(0), Timestamp(current_packet_id_));
|
||||
++current_packet_id_;
|
||||
{
|
||||
absl::MutexLock lock(&g_source_mutex);
|
||||
@@ -78,7 +78,7 @@ class TestSourceCalculator : public CalculatorBase {
|
||||
return g_source_counter <= kSlowCalculatorRate * g_slow_counter ||
|
||||
g_source_counter <= 1;
|
||||
}
|
||||
int64_t current_packet_id_;
|
||||
int64 current_packet_id_;
|
||||
};
|
||||
|
||||
REGISTER_CALCULATOR(TestSourceCalculator);
|
||||
@@ -87,8 +87,8 @@ class TestSlowCalculator : public CalculatorBase {
|
||||
public:
|
||||
TestSlowCalculator() = default;
|
||||
static absl::Status GetContract(CalculatorContract* cc) {
|
||||
cc->Inputs().Index(0).Set<int64_t>();
|
||||
cc->Outputs().Index(0).Set<int64_t>();
|
||||
cc->Inputs().Index(0).Set<int64>();
|
||||
cc->Outputs().Index(0).Set<int64>();
|
||||
return absl::OkStatus();
|
||||
}
|
||||
absl::Status Open(CalculatorContext* cc) override {
|
||||
@@ -97,7 +97,7 @@ class TestSlowCalculator : public CalculatorBase {
|
||||
return absl::OkStatus();
|
||||
}
|
||||
absl::Status Process(CalculatorContext* cc) override {
|
||||
cc->Outputs().Index(0).Add(new int64_t(0),
|
||||
cc->Outputs().Index(0).Add(new int64(0),
|
||||
cc->Inputs().Index(0).Value().Timestamp());
|
||||
{
|
||||
absl::MutexLock lock(&g_source_mutex);
|
||||
@@ -118,9 +118,8 @@ class TestSlowCalculator : public CalculatorBase {
|
||||
REGISTER_CALCULATOR(TestSlowCalculator);
|
||||
|
||||
// Return the values of the timestamps of a vector of Packets.
|
||||
static std::vector<int64_t> TimestampValues(
|
||||
const std::vector<Packet>& packets) {
|
||||
std::vector<int64_t> result;
|
||||
static std::vector<int64> TimestampValues(const std::vector<Packet>& packets) {
|
||||
std::vector<int64> result;
|
||||
for (const Packet& p : packets) {
|
||||
result.push_back(p.Timestamp().Value());
|
||||
}
|
||||
@@ -175,7 +174,7 @@ TEST_P(FixedSizeInputStreamHandlerTest, DropsPackets) {
|
||||
// consumed. In this way, the TestSlowCalculator consumes and outputs only
|
||||
// every tenth packet.
|
||||
EXPECT_EQ(output_packets.size(), 11);
|
||||
std::vector<int64_t> expected_ts = {0, 9, 19, 29, 39, 49, 59, 69, 79, 89, 99};
|
||||
std::vector<int64> expected_ts = {0, 9, 19, 29, 39, 49, 59, 69, 79, 89, 99};
|
||||
EXPECT_THAT(TimestampValues(output_packets),
|
||||
testing::ContainerEq(expected_ts));
|
||||
}
|
||||
@@ -345,18 +344,18 @@ TEST_P(FixedSizeInputStreamHandlerTest, LateArrivalDrop) {
|
||||
|
||||
if (GetParam()) {
|
||||
EXPECT_THAT(TimestampValues(output_packets[0]),
|
||||
testing::ContainerEq(std::vector<int64_t>{1, 2, 3, 4, 5, 6}));
|
||||
testing::ContainerEq(std::vector<int64>{1, 2, 3, 4, 5, 6}));
|
||||
EXPECT_THAT(TimestampValues(output_packets[1]),
|
||||
testing::ContainerEq(std::vector<int64_t>{3, 4, 5, 6, 7}));
|
||||
testing::ContainerEq(std::vector<int64>{3, 4, 5, 6, 7}));
|
||||
EXPECT_THAT(TimestampValues(output_packets[2]),
|
||||
testing::ContainerEq(std::vector<int64_t>{4, 5, 6, 7}));
|
||||
testing::ContainerEq(std::vector<int64>{4, 5, 6, 7}));
|
||||
} else {
|
||||
EXPECT_THAT(TimestampValues(output_packets[0]),
|
||||
testing::ContainerEq(std::vector<int64_t>{5, 6}));
|
||||
testing::ContainerEq(std::vector<int64>{5, 6}));
|
||||
EXPECT_THAT(TimestampValues(output_packets[1]),
|
||||
testing::ContainerEq(std::vector<int64_t>{5, 6, 7}));
|
||||
testing::ContainerEq(std::vector<int64>{5, 6, 7}));
|
||||
EXPECT_THAT(TimestampValues(output_packets[2]),
|
||||
testing::ContainerEq(std::vector<int64_t>{5, 6, 7}));
|
||||
testing::ContainerEq(std::vector<int64>{5, 6, 7}));
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -791,7 +791,6 @@ cc_library(
|
||||
"@com_google_absl//absl/status",
|
||||
"@com_google_absl//absl/status:statusor",
|
||||
"@com_google_absl//absl/strings",
|
||||
"@com_google_absl//absl/strings:str_format",
|
||||
"@stblib//:stb_image",
|
||||
"@stblib//:stb_image_write",
|
||||
],
|
||||
|
||||
@@ -1,53 +0,0 @@
|
||||
# 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.
|
||||
|
||||
"""MediaPipe Task Library Helper Rules for iOS"""
|
||||
|
||||
MPP_TASK_MINIMUM_OS_VERSION = "11.0"
|
||||
|
||||
# When the static framework is built with bazel, the all header files are moved
|
||||
# to the "Headers" directory with no header path prefixes. This auxiliary rule
|
||||
# is used for stripping the path prefix to the C/iOS API header files included by
|
||||
# other C/iOS API header files.
|
||||
# In case of C header files, includes start with a keyword of "#include'.
|
||||
# Imports in iOS header files start with a keyword of '#import'.
|
||||
def strip_api_include_path_prefix(name, hdr_labels, prefix = ""):
|
||||
"""Create modified header files with the import path stripped out.
|
||||
|
||||
Args:
|
||||
name: The name to be used as a prefix to the generated genrules.
|
||||
hdr_labels: List of header labels to strip out the include path. Each
|
||||
label must end with a colon followed by the header file name.
|
||||
prefix: Optional prefix path to prepend to the header inclusion path.
|
||||
"""
|
||||
for hdr_label in hdr_labels:
|
||||
hdr_filename = hdr_label.split(":")[-1]
|
||||
|
||||
# The last path component of iOS header files is sources/some_file.h
|
||||
# Hence it wiill contain a '/'. So the string can be split at '/' to get
|
||||
# the header file name.
|
||||
if "/" in hdr_filename:
|
||||
hdr_filename = hdr_filename.split("/")[-1]
|
||||
|
||||
hdr_basename = hdr_filename.split(".")[0]
|
||||
native.genrule(
|
||||
name = "{}_{}".format(name, hdr_basename),
|
||||
srcs = [hdr_label],
|
||||
outs = [hdr_filename],
|
||||
cmd = """
|
||||
sed 's|#\\([a-z]*\\) ".*/\\([^/]\\{{1,\\}}\\.h\\)"|#\\1 "{}\\2"|'\
|
||||
"$(location {})"\
|
||||
> "$@"
|
||||
""".format(prefix, hdr_label),
|
||||
)
|
||||
@@ -54,7 +54,6 @@ def mediapipe_proto_library_impl(
|
||||
def_java_proto = True,
|
||||
def_jspb_proto = True,
|
||||
def_go_proto = True,
|
||||
def_dart_proto = True,
|
||||
def_options_lib = True):
|
||||
"""Defines the proto_library targets needed for all mediapipe platforms.
|
||||
|
||||
@@ -76,7 +75,6 @@ def mediapipe_proto_library_impl(
|
||||
def_java_proto: define the java_proto_library target
|
||||
def_jspb_proto: define the jspb_proto_library target
|
||||
def_go_proto: define the go_proto_library target
|
||||
def_dart_proto: define the dart_proto_library target
|
||||
def_options_lib: define the mediapipe_options_library target
|
||||
"""
|
||||
|
||||
@@ -260,7 +258,6 @@ def mediapipe_proto_library(
|
||||
def_java_proto = True,
|
||||
def_jspb_proto = True,
|
||||
def_go_proto = True,
|
||||
def_dart_proto = True,
|
||||
def_options_lib = True,
|
||||
def_rewrite = True,
|
||||
portable_deps = None): # @unused
|
||||
@@ -286,7 +283,6 @@ def mediapipe_proto_library(
|
||||
def_java_proto: define the java_proto_library target
|
||||
def_jspb_proto: define the jspb_proto_library target
|
||||
def_go_proto: define the go_proto_library target
|
||||
def_dart_proto: define the dart_proto_library target
|
||||
def_options_lib: define the mediapipe_options_library target
|
||||
def_rewrite: define a sibling mediapipe_proto_library with package "mediapipe"
|
||||
"""
|
||||
@@ -308,7 +304,6 @@ def mediapipe_proto_library(
|
||||
def_java_proto = def_java_proto,
|
||||
def_jspb_proto = def_jspb_proto,
|
||||
def_go_proto = def_go_proto,
|
||||
def_dart_proto = def_dart_proto,
|
||||
def_options_lib = def_options_lib,
|
||||
)
|
||||
|
||||
@@ -338,7 +333,6 @@ def mediapipe_proto_library(
|
||||
def_java_proto = def_java_proto,
|
||||
def_jspb_proto = def_jspb_proto,
|
||||
def_go_proto = def_go_proto,
|
||||
def_dart_proto = def_dart_proto,
|
||||
# A clone of mediapipe_options_library() will redefine some classes.
|
||||
def_options_lib = False,
|
||||
)
|
||||
|
||||
@@ -60,7 +60,7 @@ std::string GetUnusedSidePacketName(
|
||||
}
|
||||
std::string candidate = input_side_packet_name_base;
|
||||
int iter = 2;
|
||||
while (input_side_packets.contains(candidate)) {
|
||||
while (mediapipe::ContainsKey(input_side_packets, candidate)) {
|
||||
candidate = absl::StrCat(input_side_packet_name_base, "_",
|
||||
absl::StrFormat("%02d", iter));
|
||||
++iter;
|
||||
|
||||
@@ -27,6 +27,10 @@ namespace options_field_util {
|
||||
|
||||
using ::mediapipe::proto_ns::internal::WireFormatLite;
|
||||
using FieldType = WireFormatLite::FieldType;
|
||||
using ::mediapipe::proto_ns::io::ArrayInputStream;
|
||||
using ::mediapipe::proto_ns::io::CodedInputStream;
|
||||
using ::mediapipe::proto_ns::io::CodedOutputStream;
|
||||
using ::mediapipe::proto_ns::io::StringOutputStream;
|
||||
|
||||
// Utility functions for OptionsFieldUtil.
|
||||
namespace {
|
||||
|
||||
@@ -101,7 +101,7 @@ void TestSuccessTagMap(const std::vector<std::string>& tag_index_names,
|
||||
EXPECT_EQ(tags.size(), tag_map->Mapping().size())
|
||||
<< "Parameters: in " << tag_map->DebugString();
|
||||
for (int i = 0; i < tags.size(); ++i) {
|
||||
EXPECT_TRUE(tag_map->Mapping().contains(tags[i]))
|
||||
EXPECT_TRUE(mediapipe::ContainsKey(tag_map->Mapping(), tags[i]))
|
||||
<< "Parameters: Trying to find \"" << tags[i] << "\" in\n"
|
||||
<< tag_map->DebugString();
|
||||
}
|
||||
|
||||
@@ -974,7 +974,7 @@ class TemplateParser::Parser::ParserImpl {
|
||||
}
|
||||
|
||||
// Consumes an identifier and saves its value in the identifier parameter.
|
||||
// Returns false if the token is not of type IDENTIFIER.
|
||||
// Returns false if the token is not of type IDENTFIER.
|
||||
bool ConsumeIdentifier(std::string* identifier) {
|
||||
if (LookingAtType(io::Tokenizer::TYPE_IDENTIFIER)) {
|
||||
*identifier = tokenizer_.current().text;
|
||||
@@ -1672,9 +1672,7 @@ class TemplateParser::Parser::MediaPipeParserImpl
|
||||
if (field_type == ProtoUtilLite::FieldType::TYPE_MESSAGE) {
|
||||
*args = {""};
|
||||
} else {
|
||||
constexpr char kPlaceholderValue[] = "1";
|
||||
MEDIAPIPE_CHECK_OK(
|
||||
ProtoUtilLite::Serialize({kPlaceholderValue}, field_type, args));
|
||||
MEDIAPIPE_CHECK_OK(ProtoUtilLite::Serialize({"1"}, field_type, args));
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -26,7 +26,6 @@
|
||||
#include "absl/status/status.h"
|
||||
#include "absl/strings/match.h"
|
||||
#include "absl/strings/str_cat.h"
|
||||
#include "absl/strings/str_format.h"
|
||||
#include "absl/strings/str_join.h"
|
||||
#include "absl/strings/substitute.h"
|
||||
#include "mediapipe/framework/calculator.pb.h"
|
||||
@@ -312,13 +311,6 @@ std::unique_ptr<ImageFrame> LoadTestPng(absl::string_view path,
|
||||
// Returns the path to the output if successful.
|
||||
absl::StatusOr<std::string> SavePngTestOutput(
|
||||
const mediapipe::ImageFrame& image, absl::string_view prefix) {
|
||||
absl::flat_hash_set<ImageFormat::Format> supported_formats = {
|
||||
ImageFormat::GRAY8, ImageFormat::SRGB, ImageFormat::SRGBA,
|
||||
ImageFormat::LAB8, ImageFormat::SBGRA};
|
||||
if (!supported_formats.contains(image.Format())) {
|
||||
return absl::CancelledError(
|
||||
absl::StrFormat("Format %d can not be saved to PNG.", image.Format()));
|
||||
}
|
||||
std::string now_string = absl::FormatTime(absl::Now());
|
||||
std::string output_relative_path =
|
||||
absl::StrCat(prefix, "_", now_string, ".png");
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
/* Copyright 2023 The MediaPipe Authors.
|
||||
/* Copyright 2023 The MediaPipe Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
|
||||
@@ -340,9 +340,7 @@ absl::Status GlContext::FinishInitialization(bool create_thread) {
|
||||
}
|
||||
|
||||
LOG(INFO) << "GL version: " << gl_major_version_ << "." << gl_minor_version_
|
||||
<< " (" << version_string
|
||||
<< "), renderer: " << glGetString(GL_RENDERER);
|
||||
|
||||
<< " (" << version_string << ")";
|
||||
{
|
||||
auto status = GetGlExtensions();
|
||||
if (!status.ok()) {
|
||||
|
||||
@@ -454,8 +454,8 @@ class GlContext : public std::enable_shared_from_this<GlContext> {
|
||||
// Number of glFinish calls completed on the GL thread.
|
||||
// Changes should be guarded by mutex_. However, we use simple atomic
|
||||
// loads for efficiency on the fast path.
|
||||
std::atomic<int64_t> gl_finish_count_ = 0;
|
||||
std::atomic<int64_t> gl_finish_count_target_ = 0;
|
||||
std::atomic<int64_t> gl_finish_count_ = ATOMIC_VAR_INIT(0);
|
||||
std::atomic<int64_t> gl_finish_count_target_ = ATOMIC_VAR_INIT(0);
|
||||
|
||||
GlContext* context_waiting_on_ ABSL_GUARDED_BY(mutex_) = nullptr;
|
||||
|
||||
|
||||
@@ -67,14 +67,53 @@ absl::Status GlContext::CreateContextInternal(
|
||||
// TODO: Investigate this option in more detail, esp. on Safari.
|
||||
attrs.preserveDrawingBuffer = 0;
|
||||
|
||||
// Quick patch for -s DISABLE_DEPRECATED_FIND_EVENT_TARGET_BEHAVIOR so it also
|
||||
// looks for our #canvas target in Module.canvas, where we expect it to be.
|
||||
// -s OFFSCREENCANVAS_SUPPORT=1 will no longer work with this under the new
|
||||
// event target behavior, but it was never supposed to be tapping into our
|
||||
// canvas anyways. See b/278155946 for more background.
|
||||
EM_ASM({ specialHTMLTargets["#canvas"] = Module.canvas; });
|
||||
// Since the Emscripten canvas target finding function is visible from here,
|
||||
// we hijack findCanvasEventTarget directly for enforcing old Module.canvas
|
||||
// behavior if the user desires, falling back to the new DOM element CSS
|
||||
// selector behavior next if that is specified, and finally just allowing the
|
||||
// lookup to proceed on a null target.
|
||||
// TODO: Ensure this works with all options (in particular,
|
||||
// multithreading options, like the special-case combination of USE_PTHREADS
|
||||
// and OFFSCREEN_FRAMEBUFFER)
|
||||
// clang-format off
|
||||
EM_ASM(
|
||||
let init_once = true;
|
||||
if (init_once) {
|
||||
const cachedFindCanvasEventTarget = findCanvasEventTarget;
|
||||
|
||||
if (typeof cachedFindCanvasEventTarget !== 'function') {
|
||||
if (typeof console !== 'undefined') {
|
||||
console.error('Expected Emscripten global function '
|
||||
+ '"findCanvasEventTarget" not found. WebGL context creation '
|
||||
+ 'may fail.');
|
||||
}
|
||||
return;
|
||||
}
|
||||
|
||||
findCanvasEventTarget = function(target) {
|
||||
if (target == 0) {
|
||||
if (Module && Module.canvas) {
|
||||
return Module.canvas;
|
||||
} else if (Module && Module.canvasCssSelector) {
|
||||
return cachedFindCanvasEventTarget(Module.canvasCssSelector);
|
||||
}
|
||||
if (typeof console !== 'undefined') {
|
||||
console.warn('Module properties canvas and canvasCssSelector not ' +
|
||||
'found during WebGL context creation.');
|
||||
}
|
||||
}
|
||||
// We still go through with the find attempt, although for most use
|
||||
// cases it will not succeed, just in case the user does want to fall-
|
||||
// back.
|
||||
return cachedFindCanvasEventTarget(target);
|
||||
}; // NOLINT: Necessary semicolon.
|
||||
init_once = false;
|
||||
}
|
||||
);
|
||||
// clang-format on
|
||||
|
||||
EMSCRIPTEN_WEBGL_CONTEXT_HANDLE context_handle =
|
||||
emscripten_webgl_create_context("#canvas", &attrs);
|
||||
emscripten_webgl_create_context(nullptr, &attrs);
|
||||
|
||||
// Check for failure
|
||||
if (context_handle <= 0) {
|
||||
|
||||
@@ -64,7 +64,7 @@ std::unique_ptr<GlTextureBuffer> GlTextureBuffer::Create(
|
||||
int actual_ws = image_frame.WidthStep();
|
||||
int alignment = 0;
|
||||
std::unique_ptr<ImageFrame> temp;
|
||||
const uint8_t* data = image_frame.PixelData();
|
||||
const uint8* data = image_frame.PixelData();
|
||||
|
||||
// Let's see if the pixel data is tightly aligned to one of the alignments
|
||||
// supported by OpenGL, preferring 4 if possible since it's the default.
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
/* Copyright 2023 The MediaPipe Authors.
|
||||
/* Copyright 2023 The MediaPipe Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
/* Copyright 2023 The MediaPipe Authors.
|
||||
/* Copyright 2023 The MediaPipe Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
/* Copyright 2023 The MediaPipe Authors.
|
||||
/* Copyright 2023 The MediaPipe Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
@@ -167,7 +167,7 @@ GpuBufferStorageYuvImage::GpuBufferStorageYuvImage(int width, int height,
|
||||
GpuBufferFormat format) {
|
||||
libyuv::FourCC fourcc = FourCCForGpuBufferFormat(format);
|
||||
int y_stride = std::ceil(1.0f * width / kDefaultDataAligment);
|
||||
auto y_data = std::make_unique<uint8_t[]>(y_stride * height);
|
||||
auto y_data = std::make_unique<uint8[]>(y_stride * height);
|
||||
switch (fourcc) {
|
||||
case libyuv::FOURCC_NV12:
|
||||
case libyuv::FOURCC_NV21: {
|
||||
@@ -175,7 +175,7 @@ GpuBufferStorageYuvImage::GpuBufferStorageYuvImage(int width, int height,
|
||||
int uv_width = 2 * std::ceil(0.5f * width);
|
||||
int uv_height = std::ceil(0.5f * height);
|
||||
int uv_stride = std::ceil(1.0f * uv_width / kDefaultDataAligment);
|
||||
auto uv_data = std::make_unique<uint8_t[]>(uv_stride * uv_height);
|
||||
auto uv_data = std::make_unique<uint8[]>(uv_stride * uv_height);
|
||||
yuv_image_ = std::make_shared<YUVImage>(
|
||||
fourcc, std::move(y_data), y_stride, std::move(uv_data), uv_stride,
|
||||
nullptr, 0, width, height);
|
||||
@@ -187,8 +187,8 @@ GpuBufferStorageYuvImage::GpuBufferStorageYuvImage(int width, int height,
|
||||
int uv_width = std::ceil(0.5f * width);
|
||||
int uv_height = std::ceil(0.5f * height);
|
||||
int uv_stride = std::ceil(1.0f * uv_width / kDefaultDataAligment);
|
||||
auto u_data = std::make_unique<uint8_t[]>(uv_stride * uv_height);
|
||||
auto v_data = std::make_unique<uint8_t[]>(uv_stride * uv_height);
|
||||
auto u_data = std::make_unique<uint8[]>(uv_stride * uv_height);
|
||||
auto v_data = std::make_unique<uint8[]>(uv_stride * uv_height);
|
||||
yuv_image_ = std::make_shared<YUVImage>(
|
||||
fourcc, std::move(y_data), y_stride, std::move(u_data), uv_stride,
|
||||
std::move(v_data), uv_stride, width, height);
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
/* Copyright 2023 The MediaPipe Authors.
|
||||
/* Copyright 2023 The MediaPipe Authors. All Rights Reserved.
|
||||
|
||||
Licensed under the Apache License, Version 2.0 (the "License");
|
||||
you may not use this file except in compliance with the License.
|
||||
|
||||
@@ -31,8 +31,7 @@
|
||||
namespace mediapipe {
|
||||
namespace {
|
||||
|
||||
void FillImageFrameRGBA(ImageFrame& image, uint8_t r, uint8_t g, uint8_t b,
|
||||
uint8_t a) {
|
||||
void FillImageFrameRGBA(ImageFrame& image, uint8 r, uint8 g, uint8 b, uint8 a) {
|
||||
auto* data = image.MutablePixelData();
|
||||
for (int y = 0; y < image.Height(); ++y) {
|
||||
auto* row = data + image.WidthStep() * y;
|
||||
|
||||
@@ -14,10 +14,8 @@
|
||||
|
||||
package com.google.mediapipe.components;
|
||||
|
||||
import javax.annotation.Nullable;
|
||||
|
||||
/** Lightweight abstraction for an object that can produce audio data. */
|
||||
public interface AudioDataProducer {
|
||||
/** Set the consumer that receives the audio data from this producer. */
|
||||
void setAudioConsumer(@Nullable AudioDataConsumer consumer);
|
||||
void setAudioConsumer(AudioDataConsumer consumer);
|
||||
}
|
||||
|
||||
@@ -71,10 +71,7 @@ android_library(
|
||||
"AudioDataProducer.java",
|
||||
],
|
||||
visibility = ["//visibility:public"],
|
||||
deps = [
|
||||
"@maven//:com_google_code_findbugs_jsr305",
|
||||
"@maven//:com_google_guava_guava",
|
||||
],
|
||||
deps = ["@maven//:com_google_guava_guava"],
|
||||
)
|
||||
|
||||
# MicrophoneHelper that provides access to audio data from a microphone
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user