talksik/mediapipe
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Project import generated by Copybara.

Browse Source 
PiperOrigin-RevId: 263982686
This commit is contained in:
MediaPipe Team
2019-08-17 20:08:42 -07:00
committed by chuoling
parent 7d4ec1e24d
commit c27a7c1e10
71 changed files with 2066 additions and 153 deletions
Download Patch File Download Diff File Expand all files Collapse all files
mediapipe/docs/face_detection_mobile_gpu.md
+13 -11
View File
@@ -4,22 +4,22 @@ This doc focuses on the
[example graph](https://github.com/google/mediapipe/tree/master/mediapipe/graphs/face_detection/face_detection_mobile_gpu.pbtxt)
that performs face detection with TensorFlow Lite on GPU.
![face_detection_android_gpu_gif](images/mobile/face_detection_android_gpu.gif){width="300"}
![face_detection_android_gpu_gif](images/mobile/face_detection_android_gpu.gif)
## Android
Please see [Hello World! in MediaPipe on Android](hello_world_android.md) for
general instructions to develop an Android application that uses MediaPipe.
The graph is used in the
[Face Detection GPU](https://github.com/google/mediapipe/tree/master/mediapipe/examples/android/src/java/com/google/mediapipe/apps/facedetectiongpu)
example app. To build the app, run:
The graph below is used in the
[Face Detection GPU Android example app](https://github.com/google/mediapipe/tree/master/mediapipe/examples/android/src/java/com/google/mediapipe/apps/facedetectiongpu).
To build the app, run:
```bash
bazel build -c opt --config=android_arm64 mediapipe/examples/android/src/java/com/google/mediapipe/apps/facedetectiongpu
```
To further install the app on android device, run:
To further install the app on an Android device, run:
```bash
adb install bazel-bin/mediapipe/examples/android/src/java/com/google/mediapipe/apps/facedetectiongpu/facedetectiongpu.apk
@@ -28,13 +28,13 @@ adb install bazel-bin/mediapipe/examples/android/src/java/com/google/mediapipe/a
## iOS
Please see [Hello World! in MediaPipe on iOS](hello_world_ios.md) for general
instructions to develop an iOS application that uses MediaPipe. The graph below
is used in the
[Face Detection GPU iOS example app](https://github.com/google/mediapipe/tree/master/mediapipe/examples/ios/facedetectiongpu).
instructions to develop an iOS application that uses MediaPipe.
To build the iOS app, please see the general
The graph below is used in the
[Face Detection GPU iOS example app](https://github.com/google/mediapipe/tree/master/mediapipe/examples/ios/facedetectiongpu).
To build the app, please see the general
[MediaPipe iOS app building and setup instructions](./mediapipe_ios_setup.md).
Specifically, run:
Specific to this example, run:
```bash
bazel build -c opt --config=ios_arm64 mediapipe/examples/ios/facedetectiongpu:FaceDetectionGpuApp
@@ -42,11 +42,13 @@ bazel build -c opt --config=ios_arm64 mediapipe/examples/ios/facedetectiongpu:Fa
## Graph
![face_detection_mobile_gpu_graph](images/mobile/face_detection_mobile_gpu.png){width="400"}
![face_detection_mobile_gpu_graph](images/mobile/face_detection_mobile_gpu.png)
To visualize the graph as shown above, copy the text specification of the graph
below and paste it into [MediaPipe Visualizer](https://viz.mediapipe.dev/).
[Source pbtxt file](https://github.com/google/mediapipe/tree/master/mediapipe/graphs/face_detection/face_detection_mobile_gpu.pbtxt)
```bash
# MediaPipe graph that performs face detection with TensorFlow Lite on GPU.
# Used in the example in