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74 lines
3.1 KiB
74 lines
3.1 KiB
# TensorFlow Lite Pose Estimation Android Demo
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### Overview
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This is an app that continuously detects the body parts in the frames seen by
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your device's camera. These instructions walk you through building and running
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the demo on an Android device. Camera captures are discarded immediately after
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use, nothing is stored or saved.
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The app demonstrates how to use 4 models:
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* Single pose models: The model can estimate the pose of only one person in the
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input image. If the input image contains multiple persons, the detection result
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can be largely incorrect.
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* PoseNet
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* MoveNet Lightning
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* MoveNet Thunder
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* Multi pose models: The model can estimate pose of multiple persons in the
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input image.
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* MoveNet MultiPose: Support up to 6 persons.
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See this [blog post](https://blog.tensorflow.org/2021/05/next-generation-pose-detection-with-movenet-and-tensorflowjs.html)
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for a comparison between these models.
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## Build the demo using Android Studio
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### Prerequisites
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* If you don't have it already, install **[Android Studio](
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https://developer.android.com/studio/index.html)** 4.2 or
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above, following the instructions on the website.
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* Android device and Android development environment with minimum API 21.
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### Building
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* Open Android Studio, and from the `Welcome` screen, select
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`Open an existing Android Studio project`.
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* From the `Open File or Project` window that appears, navigate to and select
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the `lite/examples/pose_estimation/android` directory from wherever you
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cloned the `tensorflow/examples` GitHub repo. Click `OK`.
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* If it asks you to do a `Gradle Sync`, click `OK`.
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* You may also need to install various platforms and tools, if you get errors
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like `Failed to find target with hash string 'android-21'` and similar. Click
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the `Run` button (the green arrow) or select `Run` > `Run 'android'` from the
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top menu. You may need to rebuild the project using `Build` > `Rebuild Project`.
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* If it asks you to use `Instant Run`, click `Proceed Without Instant Run`.
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* Also, you need to have an Android device plugged in with developer options
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enabled at this point. See **[here](
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https://developer.android.com/studio/run/device)** for more details
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on setting up developer devices.
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### Model used
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Downloading, extraction and placement in assets folder has been managed
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automatically by `download.gradle`.
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If you explicitly want to download the model, you can download it from here:
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* [Posenet](https://storage.googleapis.com/download.tensorflow.org/models/tflite/posenet_mobilenet_v1_100_257x257_multi_kpt_stripped.tflite)
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* [Movenet Lightning](https://kaggle.com/models/google/movenet/frameworks/tfLite/variations/singlepose-lightning)
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* [Movenet Thunder](https://www.kaggle.com/models/google/movenet/frameworks/tfLite/variations/singlepose-thunder)
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* [Movenet MultiPose](https://www.kaggle.com/models/google/movenet/frameworks/tfLite/variations/multipose-lightning-tflite-float16)
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### Additional Note
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_Please do not delete the assets folder content_. If you explicitly deleted the
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files, then please choose `Build` > `Rebuild` from menu to re-download the
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deleted model files into assets folder.
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