YuNetのPythonでのONNX、TensorFlow-Lite推論サンプル

Related tags

Deep Learning opencv onnx tensorflow-lite opencv-zoo yunet
Overview

YuNet-ONNX-TFLite-Sample

YuNetのPythonでのONNX、TensorFlow-Lite推論サンプルです。
TensorFlow-LiteモデルはPINTO0309/PINTO_model_zoo/144_YuNetのものを使用しています。

Requirement

  • OpenCV 3.4.2 or later
  • onnxruntime 1.5.2 or later
  • tensorflow 2.6.0 or later

Demo

デモの実行方法は以下です。

python sample_onnx.py
  • --device
    カメラデバイス番号の指定
    デフォルト：0
  • --movie
    動画ファイルの指定 ※指定時はカメラデバイスより優先
    デフォルト：指定なし
  • --image
    画像ファイルの指定 ※指定時はカメラデバイスや動画より優先
    デフォルト：指定なし
  • --width
    カメラキャプチャ時の横幅
    デフォルト：960
  • --height
    カメラキャプチャ時の縦幅
    デフォルト：540
  • --model
    ロードするモデルの格納パス
    デフォルト：model/face_detection_yunet_120x160.onnx
  • --input_shape
    モデルの入力サイズ
    デフォルト：160,120
  • --score_th
    クラス判別の閾値
    デフォルト：0.6
  • --nms_th
    NMSの閾値
    デフォルト：0.3
  • --topk
    topk指定値
    デフォルト：5000
  • --keep_topk
    keep_topk指定値
    デフォルト：750
python sample_tlite.py
  • --device
    カメラデバイス番号の指定
    デフォルト：0
  • --movie
    動画ファイルの指定 ※指定時はカメラデバイスより優先
    デフォルト：指定なし
  • --image
    画像ファイルの指定 ※指定時はカメラデバイスや動画より優先
    デフォルト：指定なし
  • --width
    カメラキャプチャ時の横幅
    デフォルト：960
  • --height
    カメラキャプチャ時の縦幅
    デフォルト：540
  • --model
    ロードするモデルの格納パス
    デフォルト：model/model_float16_quant.tflite
  • --input_shape
    モデルの入力サイズ
    デフォルト：160,120
  • --score_th
    クラス判別の閾値
    デフォルト：0.6
  • --nms_th
    NMSの閾値
    デフォルト：0.3
  • --topk
    topk指定値
    デフォルト：5000
  • --keep_topk
    keep_topk指定値
    デフォルト：750

Reference

Author

高橋かずひと(https://twitter.com/KzhtTkhs)

License

YuNet-ONNX-TFLite-Sample is under Apache-2.0 License.

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Comments
  • ONNX Demo example not working with Jetson Xavier NX

    ONNX Demo example not working with Jetson Xavier NX

    Hi. First things first, thank you for you repo !! I'm just testing the ONNX demo code and I encountered the following error.

    python3 sample_onnx.py --width 640 --height 480 Traceback (most recent call last): File "sample_onnx.py", line 179, in main() File "sample_onnx.py", line 101, in main bboxes, landmarks, scores = yunet.inference(frame) File "/workspace/YuNet-ONNX-TFLite-Sample/yunet/yunet_onnx.py", line 59, in inference bboxes, landmarks, scores = self._postprocess(result) File "/workspace/YuNet-ONNX-TFLite-Sample/yunet/yunet_onnx.py", line 143, in _postprocess dets = np.squeeze(dets, axis=1) File "<array_function internals>", line 6, in squeeze File "/usr/local/lib/python3.6/dist-packages/numpy/core/fromnumeric.py", line 1495, in squeeze return squeeze(axis=axis) ValueError: cannot select an axis to squeeze out which has size not equal to one

    I'm using the default tensorflow docker from nvdia (other onnx models works such as yours of movenet multipose) with these packages installed

    onnxruntime-gpu 1.8.0 opencv-python 4.5.4.58 tensorflow 2.5.0+nv

    opened by isra60 5
Owner
KazuhitoTakahashi
KazuhitoTakahashi
GitHub
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