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dog-qiuqiu / Yolo-Fastest

: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+
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darknet2ncnn output #55

Closed wxkkk closed 3 years ago

wxkkk commented 3 years ago

修改voc类别为五类，训练后将cfg和weights转为ncnn模型，但是输出层有两个Yolov3DetectionOutput，转换的时候已经选了合并yolo层，这里是我漏掉什么操作吗？ 直接转换你的模型是没问题的，如下图输出层已经合并 微信截图_20210512110447 但是我训练出来的模型转换就是两个输出 微信截图_20210512110428

期待解答，谢谢

wxkkk commented 3 years ago

手动修改.param文件把两层输出合并了，可能是转换工具的问题没有自动合并，我关闭问题啦