This project forked from imuncle/yoloface-50k
yoloface-50k的可部署模型
本仓库包含已量化的yoloface tflite模型以及未量化的onnx模型，h5模型和pb模型，另外还有使用pytorch解析运行yolo cfg和weight的小工具
本仓库所使用的网络模型来自dog-qiuqiu/MobileNet-Yolo，感谢这位大佬
ncnn: yoloface使用ncnn推理后的工程，可以在CPU上实时运行。其中libncnn.a是在Ubuntu 20.04上编译的，如是不同的操作系统，请下载ncnn自行编译替换
tensorflow: 内含yolo转h5、h5转pb的代码
tflite: pb转tflite并量化的代码
firmware: 单片机部分代码。因为硬件不同所以没有上传整个工程，摘取了核心代码，另附STM32CUBEMX工程文件参考。
注意：代码中的
nms是虚假的nms，并没有进行非极大值抑制，只是提取出了置信度较高的目标，使用时可自己添加
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