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Name: w1ll
Type: User
Name: w1ll
Type: User
使用opencv部署yolact实例分割,包含C++和Python两种版本的程序
:zap: Based on yolo's ultra-lightweight universal target detection algorithm, the calculation amount is only 250mflops, the ncnn model size is only 666kb, the Raspberry Pi 3b can run up to 15fps+, and the mobile terminal can run up to 178fps+
YOLO reproduce summary (now based on YOLOv3)
YOLOv3 in PyTorch > ONNX > CoreML > iOS
Complete YOLO v3 TensorFlow implementation. Support training on your own dataset.
YOLOv5 in PyTorch > ONNX > CoreML > iOS
用c++实现了yolov5使用openvino的部署
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