Open alicexiao123 opened 6 years ago
hi, ChenYingPeng 我从你的百度盘里面下载了里面的yolov3.prototxt,但是看起来里面好像82、83层没有,这样是对的吗?还是漏了?
不管怎样,还是谢谢你的分享。
layer { bottom: "layer81-conv" top: "layer82-conv" name: "layer82-conv" type: "Convolution" convolution_param { num_output: 255 kernel_size: 1 pad: 0 stride: 1 bias_term: true } } layer { bottom: "layer80-conv" top: "layer84-route" name: "layer84-route" type: "Concat" } layer { bottom: "layer84-route" top: "layer85-conv" name: "layer85-conv" type: "Convolution" convolution_param { num_output: 256 kernel_size: 1 pad: 0 stride: 1 bias_term: false } }
yolov3从82,94,106层输出三个特征图,之后通过yolo层进行特征融合,这里没有写的83层是yolo层,作者把这部分放到主函数里做了~
The comment from zbw4034 is correct.
hi, ChenYingPeng 我从你的百度盘里面下载了里面的yolov3.prototxt,但是看起来里面好像82、83层没有,这样是对的吗?还是漏了?
不管怎样,还是谢谢你的分享。
layer { bottom: "layer81-conv" top: "layer82-conv" name: "layer82-conv" type: "Convolution" convolution_param { num_output: 255 kernel_size: 1 pad: 0 stride: 1 bias_term: true } } layer { bottom: "layer80-conv" top: "layer84-route" name: "layer84-route" type: "Concat" } layer { bottom: "layer84-route" top: "layer85-conv" name: "layer85-conv" type: "Convolution" convolution_param { num_output: 256 kernel_size: 1 pad: 0 stride: 1 bias_term: false } }