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Palm Detection

2022 Spring Tongji Computer Vision Course Project

Method

  1. Extract ROI —— Yolov5n (Run on Android Client)
  2. Detect ROI —— MobileFaceNet (Run on Flask Server)

Paper: Towards Palmprint Verification On Smartphones (arxiv.org)

Flask Backend: LinzhouLi/PalmDetection-backend (github.com)

Deploy Yolov5

模型转换:

  1. 训练好的pytorch模型导出为torchscript
  2. 使用pnnx将torchscript格式转换为NCNN格式

图片预处理:

  1. Resize (转换宽高至 $320\times 32k$$32k\times320$, $k\in \mathbb{Z}$)
  2. Padding (以114填充添加的部分)
  3. Normalize (除以255)

数据后处理:

Anchor & NMS

参考 nihui/ncnn-android-yolov5: The YOLOv5 object detection android example (github.com)

UI

homepage

detect

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Deploy yolov5n on android with ncnn

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  • C++ 85.6%
  • C 11.1%
  • CMake 2.4%
  • Other 0.9%