/Mediapipe-android-pose-tracking

This is an Android Studio project for Mediapipe pose tracking.

Primary LanguageJava

This is an example of using MediaPipe AAR in Android Studio with Gradle.

The steps to build and use MediaPipe AAR is documented in MediaPipe's android_archive_library.md.

To build aar file. bazel build -c opt --strip=ALWAYS --host_crosstool_top=@bazel_tools//tools/cpp:toolchain --fat_apk_cpu=arm64-v8a,armeabi-v7a mediapipe/examples/android/src/java/com/google/mediapipe/apps/aar_example:mediapipe_pose_tracking --verbose_failures

To build binarypb: bazel build -c opt --strip=ALWAYS --host_crosstool_top=@bazel_tools//tools/cpp:toolchain --fat_apk_cpu=arm64-v8a,armeabi-v7a mediapipe/graphs/pose_tracking:pose_tracking_gpu_binary_graph

The binarypb is in the folder /bazel-bin/mediapipe/graphs/pose_tracking

  1. To control the output stream, you can modify https://github.com/google/mediapipe/blob/master/mediapipe/graphs/pose_tracking/pose_tracking_gpu.pbtxt to generate your own pose_tracking_gpu.binarypb, then overwrite it in the folder app/src/main/assets/

  2. Google ML Kit Pose detection.

    https://developers.google.com/ml-kit/vision/pose-detection

  3. After my testing, the current Mediapipe pose detection model is more accurate than ML Kit even if Google said ML Kit also uses BlazePose.