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Hsintao
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Description

106点人脸关键点检测的PFLD算法实现

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pfld106face_landmarks

106点人脸关键点检测的PFLD算法实现

  • [x] 😊ncnn cpp推理代码

  • [x] 转换后的ONNX模型

  • [x] 预训练权重

  • [x] 性能测试

  • [x] update GhostNet

  • [x] update MobileNetV3

| Backbone | param | MACC | nme | Link | ONNX | | :---------------: | :---: | :----: | :---: | :----------------------------: | :--: | | MobileNetV2 | 1.26M | 393M | 4.96% | v2 | v2.onnx | | MobileNetV3 | 1.44M | 201.8M | 4.40% | v3 | v3.onnx | | MobileNetV3_Small | 0.22M | 13M | 6.22% | lite | lite.onnx |

测试电脑MacBook 2017 13-Inch CPU i5-3.1GHz (single core) | backbone | FPS(onnxruntime cpu) | Time(single face) | | :-----------: | :------------------: | :----: | | v2.onnx | 60.9 | 16ms | | V3.onnx | 62.7 | 15.9ms | | lite.onnx | 255 | 3.9ms |

  • Requirements
    torch=1.2.0
    torchvision
    opencv-python
    tqdm
    onnxruntime==1.2.2
    numpy
  • 数据集准备
  # 下载数据集到data/imgs下
  cd data
  python prepare.py
  # data 文件夹结构
  data/
    imgs/
    train_data/
      imgs/
      list.txt
    test_data/
      imgs/
      list.txt
  • 训练
  CUDA_VISIBLE_DEVICES=0 python train.py --backbone=v3
  # 可选backbone为v2 v3 lite
  • 结果 (MobileNetV2)

  • Thanks

https://github.com/polarisZhao/PFLD-pytorch

https://github.com/microsoft/onnxruntime

https://github.com/kuan-wang/pytorch-mobilenet-v3

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