Open wweiCV opened 4 years ago
您好，我在windows下使用detection_out.cpp推理时，用models\yolov3路径下的模型测试检测正常，但是切换到自己的模型测试时检测层输出一直为[0,-1,-1,-1,-1,-1,-1,-1]，模型是使用您linux版本的环境训练的，训练时map值正常。我将caffemodel转成ncnn，在ncnn下测试也正常。我怀疑可能是deploy文件中layer层与linux环境中的layer不一样导致，但是比对只后未发现异常，这个问题困扰我好多天了，请求您的帮助！这是我的deploy文件。 name: "yolov3" input: "data" layer { name: "data" type: "Input" top: "data" input_param {shape {dim: 1 dim: 3 dim: 800 dim: 800 } } }
layer { name: "conv1" type: "Convolution" bottom: "data" top: "conv1" convolution_param { num_output: 16 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 2 weight_filler { type: "msra" } dilation: 1 } }
layer { name: "bn_scale1" type: "Scale" bottom: "conv1" top: "conv1" scale_param { bias_term: true } } layer { name: "power1" type: "Power" bottom: "conv1" top: "power1" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus1" type: "ReLU6" bottom: "power1" top: "relus1" } layer { name: "power2" type: "Power" bottom: "relus1" top: "power2" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul1" type: "Eltwise" bottom: "conv1" bottom: "power2" top: "mul1" eltwise_param { operation: PROD } } layer { name: "conv2" type: "DepthwiseConvolution" bottom: "mul1" top: "conv2" convolution_param { num_output: 16 bias_term: false pad: 1 kernel_size: 3 group: 16 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale2" type: "Scale" bottom: "conv2" top: "conv2" scale_param { bias_term: true } } layer { name: "relu1" type: "ReLU" bottom: "conv2" top: "relu1" } layer { name: "conv3" type: "Convolution" bottom: "relu1" top: "conv3" convolution_param { num_output: 16 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale3" type: "Scale" bottom: "conv3" top: "conv3" scale_param { bias_term: true } } layer { name: "add1" type: "Eltwise" bottom: "mul1" bottom: "conv3" top: "add1" eltwise_param { operation: SUM } } layer { name: "conv4" type: "Convolution" bottom: "add1" top: "conv4" convolution_param { num_output: 64 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale4" type: "Scale" bottom: "conv4" top: "conv4" scale_param { bias_term: true } } layer { name: "relu2" type: "ReLU" bottom: "conv4" top: "relu2" } layer { name: "conv5" type: "DepthwiseConvolution" bottom: "relu2" top: "conv5" convolution_param { num_output: 64 bias_term: false pad: 1 kernel_size: 3 group: 64 stride: 2 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale5" type: "Scale" bottom: "conv5" top: "conv5" scale_param { bias_term: true } } layer { name: "relu3" type: "ReLU" bottom: "conv5" top: "relu3" } layer { name: "conv6" type: "Convolution" bottom: "relu3" top: "conv6" convolution_param { num_output: 24 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale6" type: "Scale" bottom: "conv6" top: "conv6" scale_param { bias_term: true } } layer { name: "conv7" type: "Convolution" bottom: "conv6" top: "conv7" convolution_param { num_output: 72 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale7" type: "Scale" bottom: "conv7" top: "conv7" scale_param { bias_term: true } } layer { name: "relu4" type: "ReLU" bottom: "conv7" top: "relu4" } layer { name: "conv8" type: "DepthwiseConvolution" bottom: "relu4" top: "conv8" convolution_param { num_output: 72 bias_term: false pad: 1 kernel_size: 3 group: 72 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale8" type: "Scale" bottom: "conv8" top: "conv8" scale_param { bias_term: true } } layer { name: "relu5" type: "ReLU" bottom: "conv8" top: "relu5" } layer { name: "conv9" type: "Convolution" bottom: "relu5" top: "conv9" convolution_param { num_output: 24 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale9" type: "Scale" bottom: "conv9" top: "conv9" scale_param { bias_term: true } } layer { name: "add2" type: "Eltwise" bottom: "conv6" bottom: "conv9" top: "add2" eltwise_param { operation: SUM } } layer { name: "conv10" type: "Convolution" bottom: "add2" top: "conv10" convolution_param { num_output: 72 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale10" type: "Scale" bottom: "conv10" top: "conv10" scale_param { bias_term: true } } layer { name: "relu6" type: "ReLU" bottom: "conv10" top: "relu6" } layer { name: "conv11" type: "DepthwiseConvolution" bottom: "relu6" top: "conv11" convolution_param { num_output: 72 bias_term: false pad: 2 kernel_size: 5 group: 72 stride: 2 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "ave_pool1" type: "Pooling" bottom: "conv11" top: "ave_pool1" pooling_param { pool: AVE global_pooling: true } } layer { name: "route1" type: "Concat" bottom: "ave_pool1" top: "route1" } layer { name: "fc1" type: "InnerProduct" bottom: "route1" top: "fc1" inner_product_param { num_output: 18 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "relu7" type: "ReLU" bottom: "fc1" top: "relu7" } layer { name: "fc2" type: "InnerProduct" bottom: "relu7" top: "fc2" inner_product_param { num_output: 72 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "power3" type: "Power" bottom: "fc2" top: "power3" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus2" type: "ReLU6" bottom: "power3" top: "relus2" } layer { name: "power4" type: "Power" bottom: "relus2" top: "power4" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "route2" type: "Concat" bottom: "power4" top: "route2" } layer { name: "scale1" type: "Scale" bottom: "conv11" bottom: "route2" top: "scale1" scale_param { axis: 0 } } layer { name: "relu8" type: "ReLU" bottom: "scale1" top: "relu8" } layer { name: "conv12" type: "Convolution" bottom: "relu8" top: "conv12" convolution_param { num_output: 40 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale12" type: "Scale" bottom: "conv12" top: "conv12" scale_param { bias_term: true } } layer { name: "conv13" type: "Convolution" bottom: "conv12" top: "conv13" convolution_param { num_output: 120 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale13" type: "Scale" bottom: "conv13" top: "conv13" scale_param { bias_term: true } } layer { name: "relu9" type: "ReLU" bottom: "conv13" top: "relu9" } layer { name: "conv14" type: "DepthwiseConvolution" bottom: "relu9" top: "conv14" convolution_param { num_output: 120 bias_term: false pad: 2 kernel_size: 5 group: 120 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale14" type: "Scale" bottom: "conv14" top: "conv14" scale_param { bias_term: true } } layer { name: "ave_pool2" type: "Pooling" bottom: "conv14" top: "ave_pool2" pooling_param { pool: AVE global_pooling: true } } layer { name: "route3" type: "Concat" bottom: "ave_pool2" top: "route3" } layer { name: "fc3" type: "InnerProduct" bottom: "route3" top: "fc3" inner_product_param { num_output: 30 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "relu10" type: "ReLU" bottom: "fc3" top: "relu10" } layer { name: "fc4" type: "InnerProduct" bottom: "relu10" top: "fc4" inner_product_param { num_output: 120 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "power5" type: "Power" bottom: "fc4" top: "power5" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus3" type: "ReLU6" bottom: "power5" top: "relus3" } layer { name: "power6" type: "Power" bottom: "relus3" top: "power6" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "route4" type: "Concat" bottom: "power6" top: "route4" } layer { name: "scale2" type: "Scale" bottom: "conv14" bottom: "route4" top: "scale2" scale_param { axis: 0 } } layer { name: "relu11" type: "ReLU" bottom: "scale2" top: "relu11" } layer { name: "conv15" type: "Convolution" bottom: "relu11" top: "conv15" convolution_param { num_output: 40 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale15" type: "Scale" bottom: "conv15" top: "conv15" scale_param { bias_term: true } } layer { name: "add3" type: "Eltwise" bottom: "conv12" bottom: "conv15" top: "add3" eltwise_param { operation: SUM } } layer { name: "conv16" type: "Convolution" bottom: "add3" top: "conv16" convolution_param { num_output: 120 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale16" type: "Scale" bottom: "conv16" top: "conv16" scale_param { bias_term: true } } layer { name: "relu12" type: "ReLU" bottom: "conv16" top: "relu12" } layer { name: "conv17" type: "DepthwiseConvolution" bottom: "relu12" top: "conv17" convolution_param { num_output: 120 bias_term: false pad: 2 kernel_size: 5 group: 120 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale17" type: "Scale" bottom: "conv17" top: "conv17" scale_param { bias_term: true } } layer { name: "ave_pool3" type: "Pooling" bottom: "conv17" top: "ave_pool3" pooling_param { pool: AVE global_pooling: true } } layer { name: "route5" type: "Concat" bottom: "ave_pool3" top: "route5" } layer { name: "fc5" type: "InnerProduct" bottom: "route5" top: "fc5" inner_product_param { num_output: 30 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "relu13" type: "ReLU" bottom: "fc5" top: "relu13" } layer { name: "fc6" type: "InnerProduct" bottom: "relu13" top: "fc6" inner_product_param { num_output: 120 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "power7" type: "Power" bottom: "fc6" top: "power7" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus4" type: "ReLU6" bottom: "power7" top: "relus4" } layer { name: "power8" type: "Power" bottom: "relus4" top: "power8" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "route6" type: "Concat" bottom: "power8" top: "route6" } layer { name: "scale3" type: "Scale" bottom: "conv17" bottom: "route6" top: "scale3" scale_param { axis: 0 } } layer { name: "relu14" type: "ReLU" bottom: "scale3" top: "relu14" } layer { name: "conv18" type: "Convolution" bottom: "relu14" top: "conv18" convolution_param { num_output: 40 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale18" type: "Scale" bottom: "conv18" top: "conv18" scale_param { bias_term: true } } layer { name: "add4" type: "Eltwise" bottom: "add3" bottom: "conv18" top: "add4" eltwise_param { operation: SUM } } layer { name: "conv19" type: "Convolution" bottom: "add4" top: "conv19" convolution_param { num_output: 240 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale19" type: "Scale" bottom: "conv19" top: "conv19" scale_param { bias_term: true } } layer { name: "power9" type: "Power" bottom: "conv19" top: "power9" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus5" type: "ReLU6" bottom: "power9" top: "relus5" } layer { name: "power10" type: "Power" bottom: "relus5" top: "power10" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul2" type: "Eltwise" bottom: "conv19" bottom: "power10" top: "mul2" eltwise_param { operation: PROD } } layer { name: "conv20" type: "DepthwiseConvolution" bottom: "mul2" top: "conv20" convolution_param { num_output: 240 bias_term: false pad: 1 kernel_size: 3 group: 240 stride: 2 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale20" type: "Scale" bottom: "conv20" top: "conv20" scale_param { bias_term: true } } layer { name: "power11" type: "Power" bottom: "conv20" top: "power11" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus6" type: "ReLU6" bottom: "power11" top: "relus6" } layer { name: "power12" type: "Power" bottom: "relus6" top: "power12" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul3" type: "Eltwise" bottom: "conv20" bottom: "power12" top: "mul3" eltwise_param { operation: PROD } } layer { name: "conv21" type: "Convolution" bottom: "mul3" top: "conv21" convolution_param { num_output: 80 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale21" type: "Scale" bottom: "conv21" top: "conv21" scale_param { bias_term: true } } layer { name: "conv22" type: "Convolution" bottom: "conv21" top: "conv22" convolution_param { num_output: 200 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale22" type: "Scale" bottom: "conv22" top: "conv22" scale_param { bias_term: true } } layer { name: "power13" type: "Power" bottom: "conv22" top: "power13" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus7" type: "ReLU6" bottom: "power13" top: "relus7" } layer { name: "power14" type: "Power" bottom: "relus7" top: "power14" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul4" type: "Eltwise" bottom: "conv22" bottom: "power14" top: "mul4" eltwise_param { operation: PROD } } layer { name: "conv23" type: "DepthwiseConvolution" bottom: "mul4" top: "conv23" convolution_param { num_output: 200 bias_term: false pad: 1 kernel_size: 3 group: 200 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale23" type: "Scale" bottom: "conv23" top: "conv23" scale_param { bias_term: true } } layer { name: "power15" type: "Power" bottom: "conv23" top: "power15" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus8" type: "ReLU6" bottom: "power15" top: "relus8" } layer { name: "power16" type: "Power" bottom: "relus8" top: "power16" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul5" type: "Eltwise" bottom: "conv23" bottom: "power16" top: "mul5" eltwise_param { operation: PROD } } layer { name: "conv24" type: "Convolution" bottom: "mul5" top: "conv24" convolution_param { num_output: 80 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale24" type: "Scale" bottom: "conv24" top: "conv24" scale_param { bias_term: true } } layer { name: "add5" type: "Eltwise" bottom: "conv21" bottom: "conv24" top: "add5" eltwise_param { operation: SUM } } layer { name: "conv25" type: "Convolution" bottom: "add5" top: "conv25" convolution_param { num_output: 184 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale25" type: "Scale" bottom: "conv25" top: "conv25" scale_param { bias_term: true } } layer { name: "power17" type: "Power" bottom: "conv25" top: "power17" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus9" type: "ReLU6" bottom: "power17" top: "relus9" } layer { name: "power18" type: "Power" bottom: "relus9" top: "power18" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul6" type: "Eltwise" bottom: "conv25" bottom: "power18" top: "mul6" eltwise_param { operation: PROD } } layer { name: "conv26" type: "DepthwiseConvolution" bottom: "mul6" top: "conv26" convolution_param { num_output: 184 bias_term: false pad: 1 kernel_size: 3 group: 184 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale26" type: "Scale" bottom: "conv26" top: "conv26" scale_param { bias_term: true } } layer { name: "power19" type: "Power" bottom: "conv26" top: "power19" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus10" type: "ReLU6" bottom: "power19" top: "relus10" } layer { name: "power20" type: "Power" bottom: "relus10" top: "power20" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul7" type: "Eltwise" bottom: "conv26" bottom: "power20" top: "mul7" eltwise_param { operation: PROD } } layer { name: "conv27" type: "Convolution" bottom: "mul7" top: "conv27" convolution_param { num_output: 80 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale27" type: "Scale" bottom: "conv27" top: "conv27" scale_param { bias_term: true } } layer { name: "add6" type: "Eltwise" bottom: "add5" bottom: "conv27" top: "add6" eltwise_param { operation: SUM } } layer { name: "conv28" type: "Convolution" bottom: "add6" top: "conv28" convolution_param { num_output: 184 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale28" type: "Scale" bottom: "conv28" top: "conv28" scale_param { bias_term: true } } layer { name: "power21" type: "Power" bottom: "conv28" top: "power21" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus11" type: "ReLU6" bottom: "power21" top: "relus11" } layer { name: "power22" type: "Power" bottom: "relus11" top: "power22" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul8" type: "Eltwise" bottom: "conv28" bottom: "power22" top: "mul8" eltwise_param { operation: PROD } } layer { name: "conv29" type: "DepthwiseConvolution" bottom: "mul8" top: "conv29" convolution_param { num_output: 184 bias_term: false pad: 1 kernel_size: 3 group: 184 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale29" type: "Scale" bottom: "conv29" top: "conv29" scale_param { bias_term: true } } layer { name: "power23" type: "Power" bottom: "conv29" top: "power23" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus12" type: "ReLU6" bottom: "power23" top: "relus12" } layer { name: "power24" type: "Power" bottom: "relus12" top: "power24" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul9" type: "Eltwise" bottom: "conv29" bottom: "power24" top: "mul9" eltwise_param { operation: PROD } } layer { name: "conv30" type: "Convolution" bottom: "mul9" top: "conv30" convolution_param { num_output: 80 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale30" type: "Scale" bottom: "conv30" top: "conv30" scale_param { bias_term: true } } layer { name: "add7" type: "Eltwise" bottom: "add6" bottom: "conv30" top: "add7" eltwise_param { operation: SUM } } layer { name: "conv31" type: "Convolution" bottom: "add7" top: "conv31" convolution_param { num_output: 480 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale31" type: "Scale" bottom: "conv31" top: "conv31" scale_param { bias_term: true } } layer { name: "power25" type: "Power" bottom: "conv31" top: "power25" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus13" type: "ReLU6" bottom: "power25" top: "relus13" } layer { name: "power26" type: "Power" bottom: "relus13" top: "power26" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul10" type: "Eltwise" bottom: "conv31" bottom: "power26" top: "mul10" eltwise_param { operation: PROD } } layer { name: "conv32" type: "DepthwiseConvolution" bottom: "mul10" top: "conv32" convolution_param { num_output: 480 bias_term: false pad: 1 kernel_size: 3 group: 480 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale32" type: "Scale" bottom: "conv32" top: "conv32" scale_param { bias_term: true } } layer { name: "ave_pool4" type: "Pooling" bottom: "conv32" top: "ave_pool4" pooling_param { pool: AVE global_pooling: true } } layer { name: "route7" type: "Concat" bottom: "ave_pool4" top: "route7" } layer { name: "fc7" type: "InnerProduct" bottom: "route7" top: "fc7" inner_product_param { num_output: 120 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "relu15" type: "ReLU" bottom: "fc7" top: "relu15" } layer { name: "fc8" type: "InnerProduct" bottom: "relu15" top: "fc8" inner_product_param { num_output: 480 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "power27" type: "Power" bottom: "fc8" top: "power27" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus14" type: "ReLU6" bottom: "power27" top: "relus14" } layer { name: "power28" type: "Power" bottom: "relus14" top: "power28" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "route8" type: "Concat" bottom: "power28" top: "route8" } layer { name: "scale4" type: "Scale" bottom: "conv32" bottom: "route8" top: "scale4" scale_param { axis: 0 } } layer { name: "power29" type: "Power" bottom: "scale4" top: "power29" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus15" type: "ReLU6" bottom: "power29" top: "relus15" } layer { name: "power30" type: "Power" bottom: "relus15" top: "power30" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul11" type: "Eltwise" bottom: "scale4" bottom: "power30" top: "mul11" eltwise_param { operation: PROD } } layer { name: "conv33" type: "Convolution" bottom: "mul11" top: "conv33" convolution_param { num_output: 112 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale33" type: "Scale" bottom: "conv33" top: "conv33" scale_param { bias_term: true } } layer { name: "conv34" type: "Convolution" bottom: "conv33" top: "conv34" convolution_param { num_output: 672 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale34" type: "Scale" bottom: "conv34" top: "conv34" scale_param { bias_term: true } } layer { name: "power31" type: "Power" bottom: "conv34" top: "power31" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus16" type: "ReLU6" bottom: "power31" top: "relus16" } layer { name: "power32" type: "Power" bottom: "relus16" top: "power32" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul12" type: "Eltwise" bottom: "conv34" bottom: "power32" top: "mul12" eltwise_param { operation: PROD } } layer { name: "conv35" type: "DepthwiseConvolution" bottom: "mul12" top: "conv35" convolution_param { num_output: 672 bias_term: false pad: 1 kernel_size: 3 group: 672 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale35" type: "Scale" bottom: "conv35" top: "conv35" scale_param { bias_term: true } } layer { name: "ave_pool5" type: "Pooling" bottom: "conv35" top: "ave_pool5" pooling_param { pool: AVE global_pooling: true } } layer { name: "route9" type: "Concat" bottom: "ave_pool5" top: "route9" } layer { name: "fc9" type: "InnerProduct" bottom: "route9" top: "fc9" inner_product_param { num_output: 168 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "relu16" type: "ReLU" bottom: "fc9" top: "relu16" } layer { name: "fc10" type: "InnerProduct" bottom: "relu16" top: "fc10" inner_product_param { num_output: 672 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "power33" type: "Power" bottom: "fc10" top: "power33" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus17" type: "ReLU6" bottom: "power33" top: "relus17" } layer { name: "power34" type: "Power" bottom: "relus17" top: "power34" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "route10" type: "Concat" bottom: "power34" top: "route10" } layer { name: "scale5" type: "Scale" bottom: "conv35" bottom: "route10" top: "scale5" scale_param { axis: 0 } } layer { name: "power35" type: "Power" bottom: "scale5" top: "power35" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus18" type: "ReLU6" bottom: "power35" top: "relus18" } layer { name: "power36" type: "Power" bottom: "relus18" top: "power36" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul13" type: "Eltwise" bottom: "scale5" bottom: "power36" top: "mul13" eltwise_param { operation: PROD } } layer { name: "conv36" type: "Convolution" bottom: "mul13" top: "conv36" convolution_param { num_output: 112 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale36" type: "Scale" bottom: "conv36" top: "conv36" scale_param { bias_term: true } } layer { name: "add8" type: "Eltwise" bottom: "conv33" bottom: "conv36" top: "add8" eltwise_param { operation: SUM } } layer { name: "conv37" type: "Convolution" bottom: "add8" top: "conv37" convolution_param { num_output: 672 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale37" type: "Scale" bottom: "conv37" top: "conv37" scale_param { bias_term: true } } layer { name: "power37" type: "Power" bottom: "conv37" top: "power37" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus19" type: "ReLU6" bottom: "power37" top: "relus19" } layer { name: "power38" type: "Power" bottom: "relus19" top: "power38" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul14" type: "Eltwise" bottom: "conv37" bottom: "power38" top: "mul14" eltwise_param { operation: PROD } } layer { name: "conv38" type: "DepthwiseConvolution" bottom: "mul14" top: "conv38" convolution_param { num_output: 672 bias_term: false pad: 2 kernel_size: 5 group: 672 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale38" type: "Scale" bottom: "conv38" top: "conv38" scale_param { bias_term: true } } layer { name: "ave_pool6" type: "Pooling" bottom: "conv38" top: "ave_pool6" pooling_param { pool: AVE global_pooling: true } } layer { name: "route11" type: "Concat" bottom: "ave_pool6" top: "route11" } layer { name: "fc11" type: "InnerProduct" bottom: "route11" top: "fc11" inner_product_param { num_output: 168 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "relu17" type: "ReLU" bottom: "fc11" top: "relu17" } layer { name: "fc12" type: "InnerProduct" bottom: "relu17" top: "fc12" inner_product_param { num_output: 672 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "power39" type: "Power" bottom: "fc12" top: "power39" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus20" type: "ReLU6" bottom: "power39" top: "relus20" } layer { name: "power40" type: "Power" bottom: "relus20" top: "power40" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "route12" type: "Concat" bottom: "power40" top: "route12" } layer { name: "scale6" type: "Scale" bottom: "conv38" bottom: "route12" top: "scale6" scale_param { axis: 0 } } layer { name: "power41" type: "Power" bottom: "scale6" top: "power41" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus21" type: "ReLU6" bottom: "power41" top: "relus21" } layer { name: "power42" type: "Power" bottom: "relus21" top: "power42" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul15" type: "Eltwise" bottom: "scale6" bottom: "power42" top: "mul15" eltwise_param { operation: PROD } } layer { name: "conv39" type: "Convolution" bottom: "mul15" top: "conv39" convolution_param { num_output: 160 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale39" type: "Scale" bottom: "conv39" top: "conv39" scale_param { bias_term: true } } layer { name: "conv40" type: "Convolution" bottom: "conv39" top: "conv40" convolution_param { num_output: 672 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale40" type: "Scale" bottom: "conv40" top: "conv40" scale_param { bias_term: true } } layer { name: "power43" type: "Power" bottom: "conv40" top: "power43" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus22" type: "ReLU6" bottom: "power43" top: "relus22" } layer { name: "power44" type: "Power" bottom: "relus22" top: "power44" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul16" type: "Eltwise" bottom: "conv40" bottom: "power44" top: "mul16" eltwise_param { operation: PROD } } layer { name: "conv41" type: "DepthwiseConvolution" bottom: "mul16" top: "conv41" convolution_param { num_output: 672 bias_term: false pad: 2 kernel_size: 5 group: 672 stride: 2 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale41" type: "Scale" bottom: "conv41" top: "conv41" scale_param { bias_term: true } } layer { name: "ave_pool7" type: "Pooling" bottom: "conv41" top: "ave_pool7" pooling_param { pool: AVE global_pooling: true } } layer { name: "route13" type: "Concat" bottom: "ave_pool7" top: "route13" } layer { name: "fc13" type: "InnerProduct" bottom: "route13" top: "fc13" inner_product_param { num_output: 168 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "relu18" type: "ReLU" bottom: "fc13" top: "relu18" } layer { name: "fc14" type: "InnerProduct" bottom: "relu18" top: "fc14" inner_product_param { num_output: 672 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "power45" type: "Power" bottom: "fc14" top: "power45" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus23" type: "ReLU6" bottom: "power45" top: "relus23" } layer { name: "power46" type: "Power" bottom: "relus23" top: "power46" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "route14" type: "Concat" bottom: "power46" top: "route14" } layer { name: "scale7" type: "Scale" bottom: "conv41" bottom: "route14" top: "scale7" scale_param { axis: 0 } } layer { name: "power47" type: "Power" bottom: "scale7" top: "power47" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus24" type: "ReLU6" bottom: "power47" top: "relus24" } layer { name: "power48" type: "Power" bottom: "relus24" top: "power48" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul17" type: "Eltwise" bottom: "scale7" bottom: "power48" top: "mul17" eltwise_param { operation: PROD } } layer { name: "conv42" type: "Convolution" bottom: "mul17" top: "conv42" convolution_param { num_output: 160 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale42" type: "Scale" bottom: "conv42" top: "conv42" scale_param { bias_term: true } } layer { name: "conv43" type: "Convolution" bottom: "conv42" top: "conv43" convolution_param { num_output: 960 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale43" type: "Scale" bottom: "conv43" top: "conv43" scale_param { bias_term: true } } layer { name: "power49" type: "Power" bottom: "conv43" top: "power49" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus25" type: "ReLU6" bottom: "power49" top: "relus25" } layer { name: "power50" type: "Power" bottom: "relus25" top: "power50" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul18" type: "Eltwise" bottom: "conv43" bottom: "power50" top: "mul18" eltwise_param { operation: PROD } } layer { name: "conv44" type: "DepthwiseConvolution" bottom: "mul18" top: "conv44" convolution_param { num_output: 960 bias_term: false pad: 2 kernel_size: 5 group: 960 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale44" type: "Scale" bottom: "conv44" top: "conv44" scale_param { bias_term: true } } layer { name: "ave_pool8" type: "Pooling" bottom: "conv44" top: "ave_pool8" pooling_param { pool: AVE global_pooling: true } } layer { name: "route15" type: "Concat" bottom: "ave_pool8" top: "route15" } layer { name: "fc15" type: "InnerProduct" bottom: "route15" top: "fc15" inner_product_param { num_output: 240 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "relu19" type: "ReLU" bottom: "fc15" top: "relu19" } layer { name: "fc16" type: "InnerProduct" bottom: "relu19" top: "fc16" inner_product_param { num_output: 960 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "power51" type: "Power" bottom: "fc16" top: "power51" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus26" type: "ReLU6" bottom: "power51" top: "relus26" } layer { name: "power52" type: "Power" bottom: "relus26" top: "power52" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "route16" type: "Concat" bottom: "power52" top: "route16" } layer { name: "scale8" type: "Scale" bottom: "conv44" bottom: "route16" top: "scale8" scale_param { axis: 0 } } layer { name: "power53" type: "Power" bottom: "scale8" top: "power53" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus27" type: "ReLU6" bottom: "power53" top: "relus27" } layer { name: "power54" type: "Power" bottom: "relus27" top: "power54" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul19" type: "Eltwise" bottom: "scale8" bottom: "power54" top: "mul19" eltwise_param { operation: PROD } } layer { name: "conv45" type: "Convolution" bottom: "mul19" top: "conv45" convolution_param { num_output: 160 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale45" type: "Scale" bottom: "conv45" top: "conv45" scale_param { bias_term: true } } layer { name: "add9" type: "Eltwise" bottom: "conv42" bottom: "conv45" top: "add9" eltwise_param { operation: SUM } } layer { name: "conv46" type: "Convolution" bottom: "add9" top: "conv46" convolution_param { num_output: 960 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale46" type: "Scale" bottom: "conv46" top: "conv46" scale_param { bias_term: true } } layer { name: "power55" type: "Power" bottom: "conv46" top: "power55" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus28" type: "ReLU6" bottom: "power55" top: "relus28" } layer { name: "power56" type: "Power" bottom: "relus28" top: "power56" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul20" type: "Eltwise" bottom: "conv46" bottom: "power56" top: "mul20" eltwise_param { operation: PROD } }
layer { name: "yolo/conv1/dw" type: "DepthwiseConvolution" bottom: "mul20" top: "yolo/conv1/dw" param { lr_mult: 1 decay_mult: 1 } convolution_param { num_output: 960 bias_term: false pad: 1 kernel_size: 3 group: 960 engine: CAFFE weight_filler { type: "msra" } } }
layer { name: "yolo/conv1/dw/scale" type: "Scale" bottom: "yolo/conv1/dw" top: "yolo/conv1/dw" param { lr_mult: 1 decay_mult: 0.0 } param { lr_mult: 2 decay_mult: 0.0 } scale_param { filler { value: 1 } bias_term: true bias_filler { value: 0 } } } layer { name: "yolo/conv1/dw/relu" type: "ReLU" bottom: "yolo/conv1/dw" top: "yolo/conv1/dw" } layer { name: "yolo/conv1" type: "Convolution" bottom: "yolo/conv1/dw" top: "yolo/conv1" param { lr_mult: 1 decay_mult: 1 } convolution_param { num_output: 672 bias_term: false kernel_size: 1 weight_filler { type: "msra" } } } layer { name: "yolo/conv1/scale" type: "Scale" bottom: "yolo/conv1" top: "yolo/conv1" param { lr_mult: 1 decay_mult: 0.0 } param { lr_mult: 2 decay_mult: 0.0 } scale_param { filler { value: 1 } bias_term: true bias_filler { value: 0 } } } layer { name: "yolo/conv1/relu" type: "ReLU" bottom: "yolo/conv1" top: "yolo/conv1" } layer { name: "upsample" type: "Deconvolution" bottom: "yolo/conv1" top: "upsample" param { lr_mult: 0 decay_mult: 0 } convolution_param { num_output: 672 group: 672 kernel_size: 1 stride: 2 pad: 0 weight_filler: { type: "constant" value : 1 } bias_term: false } }
layer { top: "maxpool" name: "maxpool" bottom: "upsample" type: "Pooling" pooling_param { kernel_size: 2 stride: 1 pool: MAX pad: 1 } } layer { name: "yolo/conv2/dw" type: "DepthwiseConvolution" bottom: "mul16" top: "yolo/conv2/dw" param { lr_mult: 1 decay_mult: 1 } convolution_param { num_output: 672 bias_term: false pad: 1 kernel_size: 3 group: 672 engine: CAFFE weight_filler { type: "msra" } } } layer { name: "yolo/conv2/dw/scale" type: "Scale" bottom: "yolo/conv2/dw" top: "yolo/conv2/dw" param { lr_mult: 1 decay_mult: 0.0 } param { lr_mult: 2 decay_mult: 0.0 } scale_param { filler { value: 1 } bias_term: true bias_filler { value: 0 } } } layer { name: "yolo/conv2/dw/relu" type: "ReLU" bottom: "yolo/conv2/dw" top: "yolo/conv2/dw" } layer { name: "yolo/conv2" type: "Convolution" bottom: "yolo/conv2/dw" top: "yolo/conv2" param { lr_mult: 1 decay_mult: 1 } convolution_param { num_output: 672 bias_term: false kernel_size: 1 weight_filler { type: "msra" } } } layer { name: "yolo/conv2/scale" type: "Scale" bottom: "yolo/conv2" top: "yolo/conv2" param { lr_mult: 1 decay_mult: 0.0 } param { lr_mult: 2 decay_mult: 0.0 } scale_param { filler { value: 1 } bias_term: true bias_filler { value: 0 } } } layer { name: "yolo/conv2/relu" type: "ReLU" bottom: "yolo/conv2" top: "yolo/conv2" } layer { name: "yolo/conv2/sum" type: "Eltwise" bottom: "maxpool" bottom: "yolo/conv2" top: "yolo/conv2/sum" }
layer { name: "yolo/conv3/dw" type: "DepthwiseConvolution" bottom: "yolo/conv2/sum" top: "yolo/conv3/dw" param { lr_mult: 1 decay_mult: 1 } convolution_param { num_output: 672 bias_term: false pad: 1 kernel_size: 3 group: 672 engine: CAFFE weight_filler { type: "msra" } } } layer { name: "yolo/conv3/dw/scale" type: "Scale" bottom: "yolo/conv3/dw" top: "yolo/conv3/dw" param { lr_mult: 1 decay_mult: 0.0 } param { lr_mult: 2 decay_mult: 0.0 } scale_param { filler { value: 1 } bias_term: true bias_filler { value: 0 } } } layer { name: "yolo/conv3/dw/relu" type: "ReLU" bottom: "yolo/conv3/dw" top: "yolo/conv3/dw" } layer { name: "yolo/conv3" type: "Convolution" bottom: "yolo/conv3/dw" top: "yolo/conv3" param { lr_mult: 1 decay_mult: 1 } convolution_param { num_output: 672 bias_term: false kernel_size: 1 weight_filler { type: "msra" } } } layer { name: "yolo/conv3/scale" type: "Scale" bottom: "yolo/conv3" top: "yolo/conv3" param { lr_mult: 1 decay_mult: 0.0 } param { lr_mult: 2 decay_mult: 0.0 } scale_param { filler { value: 1 } bias_term: true bias_filler { value: 0 } } } layer { name: "yolo/conv3/relu" type: "ReLU" bottom: "yolo/conv3" top: "yolo/conv3" } layer { name: "yolo/conv4" type: "Convolution" bottom: "yolo/conv1" top: "yolo/conv4" param { lr_mult: 1 decay_mult: 1 } param { lr_mult: 2 decay_mult: 0 } convolution_param { num_output: 18 kernel_size: 1 pad: 0 stride: 1 weight_filler { type: "msra" } bias_filler { value: 0 } } }
layer { name: "yolo/conv5" type: "Convolution" bottom: "yolo/conv3" top: "yolo/conv5" param { lr_mult: 1 decay_mult: 1 } param { lr_mult: 2 decay_mult: 0 } convolution_param { num_output: 18 kernel_size: 1 pad: 0 stride: 1 weight_filler { type: "msra" } bias_filler { value: 0 } } } layer { name: "detection_out" type: "Yolov3DetectionOutput" bottom: "yolo/conv4" bottom: "yolo/conv5" top: "detection_out" yolov3_detection_output_param { confidence_threshold: 0.01 nms_threshold: 0.45 num_classes: 1
#10,14, 23,27, 37,58, 81,82, 135,169, 344,319 biases: 18 biases: 34 biases: 45 biases: 84 biases: 65 biases: 181 biases: 141 biases: 111 biases: 129 biases: 241 biases: 254 biases: 254 mask:3 mask:4 mask:5 mask:0 mask:1 mask:2 anchors_scale:32 anchors_scale:16 mask_group_num:2
} }
您好，我在windows下使用detection_out.cpp推理时，用models\yolov3路径下的模型测试检测正常，但是切换到自己的模型测试时检测层输出一直为[0,-1,-1,-1,-1,-1,-1,-1]，模型是使用您linux版本的环境训练的，训练时map值正常。我将caffemodel转成ncnn，在ncnn下测试也正常。我怀疑可能是deploy文件中layer层与linux环境中的layer不一样导致，但是比对只后未发现异常，这个问题困扰我好多天了，请求您的帮助！这是我的deploy文件。 name: "yolov3" input: "data" layer { name: "data" type: "Input" top: "data" input_param {shape {dim: 1 dim: 3 dim: 800 dim: 800 } } }
layer { name: "conv1" type: "Convolution" bottom: "data" top: "conv1" convolution_param { num_output: 16 bias_term: false pad: 1 kernel_size: 3 group: 1 stride: 2 weight_filler { type: "msra" } dilation: 1 } }
layer { name: "bn_scale1" type: "Scale" bottom: "conv1" top: "conv1" scale_param { bias_term: true } } layer { name: "power1" type: "Power" bottom: "conv1" top: "power1" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus1" type: "ReLU6" bottom: "power1" top: "relus1" } layer { name: "power2" type: "Power" bottom: "relus1" top: "power2" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul1" type: "Eltwise" bottom: "conv1" bottom: "power2" top: "mul1" eltwise_param { operation: PROD } } layer { name: "conv2" type: "DepthwiseConvolution" bottom: "mul1" top: "conv2" convolution_param { num_output: 16 bias_term: false pad: 1 kernel_size: 3 group: 16 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale2" type: "Scale" bottom: "conv2" top: "conv2" scale_param { bias_term: true } } layer { name: "relu1" type: "ReLU" bottom: "conv2" top: "relu1" } layer { name: "conv3" type: "Convolution" bottom: "relu1" top: "conv3" convolution_param { num_output: 16 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale3" type: "Scale" bottom: "conv3" top: "conv3" scale_param { bias_term: true } } layer { name: "add1" type: "Eltwise" bottom: "mul1" bottom: "conv3" top: "add1" eltwise_param { operation: SUM } } layer { name: "conv4" type: "Convolution" bottom: "add1" top: "conv4" convolution_param { num_output: 64 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale4" type: "Scale" bottom: "conv4" top: "conv4" scale_param { bias_term: true } } layer { name: "relu2" type: "ReLU" bottom: "conv4" top: "relu2" } layer { name: "conv5" type: "DepthwiseConvolution" bottom: "relu2" top: "conv5" convolution_param { num_output: 64 bias_term: false pad: 1 kernel_size: 3 group: 64 stride: 2 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale5" type: "Scale" bottom: "conv5" top: "conv5" scale_param { bias_term: true } } layer { name: "relu3" type: "ReLU" bottom: "conv5" top: "relu3" } layer { name: "conv6" type: "Convolution" bottom: "relu3" top: "conv6" convolution_param { num_output: 24 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale6" type: "Scale" bottom: "conv6" top: "conv6" scale_param { bias_term: true } } layer { name: "conv7" type: "Convolution" bottom: "conv6" top: "conv7" convolution_param { num_output: 72 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale7" type: "Scale" bottom: "conv7" top: "conv7" scale_param { bias_term: true } } layer { name: "relu4" type: "ReLU" bottom: "conv7" top: "relu4" } layer { name: "conv8" type: "DepthwiseConvolution" bottom: "relu4" top: "conv8" convolution_param { num_output: 72 bias_term: false pad: 1 kernel_size: 3 group: 72 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale8" type: "Scale" bottom: "conv8" top: "conv8" scale_param { bias_term: true } } layer { name: "relu5" type: "ReLU" bottom: "conv8" top: "relu5" } layer { name: "conv9" type: "Convolution" bottom: "relu5" top: "conv9" convolution_param { num_output: 24 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale9" type: "Scale" bottom: "conv9" top: "conv9" scale_param { bias_term: true } } layer { name: "add2" type: "Eltwise" bottom: "conv6" bottom: "conv9" top: "add2" eltwise_param { operation: SUM } } layer { name: "conv10" type: "Convolution" bottom: "add2" top: "conv10" convolution_param { num_output: 72 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale10" type: "Scale" bottom: "conv10" top: "conv10" scale_param { bias_term: true } } layer { name: "relu6" type: "ReLU" bottom: "conv10" top: "relu6" } layer { name: "conv11" type: "DepthwiseConvolution" bottom: "relu6" top: "conv11" convolution_param { num_output: 72 bias_term: false pad: 2 kernel_size: 5 group: 72 stride: 2 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "ave_pool1" type: "Pooling" bottom: "conv11" top: "ave_pool1" pooling_param { pool: AVE global_pooling: true } } layer { name: "route1" type: "Concat" bottom: "ave_pool1" top: "route1" } layer { name: "fc1" type: "InnerProduct" bottom: "route1" top: "fc1" inner_product_param { num_output: 18 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "relu7" type: "ReLU" bottom: "fc1" top: "relu7" } layer { name: "fc2" type: "InnerProduct" bottom: "relu7" top: "fc2" inner_product_param { num_output: 72 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "power3" type: "Power" bottom: "fc2" top: "power3" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus2" type: "ReLU6" bottom: "power3" top: "relus2" } layer { name: "power4" type: "Power" bottom: "relus2" top: "power4" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "route2" type: "Concat" bottom: "power4" top: "route2" } layer { name: "scale1" type: "Scale" bottom: "conv11" bottom: "route2" top: "scale1" scale_param { axis: 0 } } layer { name: "relu8" type: "ReLU" bottom: "scale1" top: "relu8" } layer { name: "conv12" type: "Convolution" bottom: "relu8" top: "conv12" convolution_param { num_output: 40 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale12" type: "Scale" bottom: "conv12" top: "conv12" scale_param { bias_term: true } } layer { name: "conv13" type: "Convolution" bottom: "conv12" top: "conv13" convolution_param { num_output: 120 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale13" type: "Scale" bottom: "conv13" top: "conv13" scale_param { bias_term: true } } layer { name: "relu9" type: "ReLU" bottom: "conv13" top: "relu9" } layer { name: "conv14" type: "DepthwiseConvolution" bottom: "relu9" top: "conv14" convolution_param { num_output: 120 bias_term: false pad: 2 kernel_size: 5 group: 120 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale14" type: "Scale" bottom: "conv14" top: "conv14" scale_param { bias_term: true } } layer { name: "ave_pool2" type: "Pooling" bottom: "conv14" top: "ave_pool2" pooling_param { pool: AVE global_pooling: true } } layer { name: "route3" type: "Concat" bottom: "ave_pool2" top: "route3" } layer { name: "fc3" type: "InnerProduct" bottom: "route3" top: "fc3" inner_product_param { num_output: 30 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "relu10" type: "ReLU" bottom: "fc3" top: "relu10" } layer { name: "fc4" type: "InnerProduct" bottom: "relu10" top: "fc4" inner_product_param { num_output: 120 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "power5" type: "Power" bottom: "fc4" top: "power5" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus3" type: "ReLU6" bottom: "power5" top: "relus3" } layer { name: "power6" type: "Power" bottom: "relus3" top: "power6" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "route4" type: "Concat" bottom: "power6" top: "route4" } layer { name: "scale2" type: "Scale" bottom: "conv14" bottom: "route4" top: "scale2" scale_param { axis: 0 } } layer { name: "relu11" type: "ReLU" bottom: "scale2" top: "relu11" } layer { name: "conv15" type: "Convolution" bottom: "relu11" top: "conv15" convolution_param { num_output: 40 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale15" type: "Scale" bottom: "conv15" top: "conv15" scale_param { bias_term: true } } layer { name: "add3" type: "Eltwise" bottom: "conv12" bottom: "conv15" top: "add3" eltwise_param { operation: SUM } } layer { name: "conv16" type: "Convolution" bottom: "add3" top: "conv16" convolution_param { num_output: 120 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale16" type: "Scale" bottom: "conv16" top: "conv16" scale_param { bias_term: true } } layer { name: "relu12" type: "ReLU" bottom: "conv16" top: "relu12" } layer { name: "conv17" type: "DepthwiseConvolution" bottom: "relu12" top: "conv17" convolution_param { num_output: 120 bias_term: false pad: 2 kernel_size: 5 group: 120 stride: 1 weight_filler { type: "xavier" } dilation: 1 } }
layer { name: "bn_scale17" type: "Scale" bottom: "conv17" top: "conv17" scale_param { bias_term: true } } layer { name: "ave_pool3" type: "Pooling" bottom: "conv17" top: "ave_pool3" pooling_param { pool: AVE global_pooling: true } } layer { name: "route5" type: "Concat" bottom: "ave_pool3" top: "route5" } layer { name: "fc5" type: "InnerProduct" bottom: "route5" top: "fc5" inner_product_param { num_output: 30 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "relu13" type: "ReLU" bottom: "fc5" top: "relu13" } layer { name: "fc6" type: "InnerProduct" bottom: "relu13" top: "fc6" inner_product_param { num_output: 120 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "power7" type: "Power" bottom: "fc6" top: "power7" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus4" type: "ReLU6" bottom: "power7" top: "relus4" } layer { name: "power8" type: "Power" bottom: "relus4" top: "power8" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "route6" type: "Concat" bottom: "power8" top: "route6" } layer { name: "scale3" type: "Scale" bottom: "conv17" bottom: "route6" top: "scale3" scale_param { axis: 0 } } layer { name: "relu14" type: "ReLU" bottom: "scale3" top: "relu14" } layer { name: "conv18" type: "Convolution" bottom: "relu14" top: "conv18" convolution_param { num_output: 40 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale18" type: "Scale" bottom: "conv18" top: "conv18" scale_param { bias_term: true } } layer { name: "add4" type: "Eltwise" bottom: "add3" bottom: "conv18" top: "add4" eltwise_param { operation: SUM } } layer { name: "conv19" type: "Convolution" bottom: "add4" top: "conv19" convolution_param { num_output: 240 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale19" type: "Scale" bottom: "conv19" top: "conv19" scale_param { bias_term: true } } layer { name: "power9" type: "Power" bottom: "conv19" top: "power9" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus5" type: "ReLU6" bottom: "power9" top: "relus5" } layer { name: "power10" type: "Power" bottom: "relus5" top: "power10" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul2" type: "Eltwise" bottom: "conv19" bottom: "power10" top: "mul2" eltwise_param { operation: PROD } } layer { name: "conv20" type: "DepthwiseConvolution" bottom: "mul2" top: "conv20" convolution_param { num_output: 240 bias_term: false pad: 1 kernel_size: 3 group: 240 stride: 2 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale20" type: "Scale" bottom: "conv20" top: "conv20" scale_param { bias_term: true } } layer { name: "power11" type: "Power" bottom: "conv20" top: "power11" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus6" type: "ReLU6" bottom: "power11" top: "relus6" } layer { name: "power12" type: "Power" bottom: "relus6" top: "power12" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul3" type: "Eltwise" bottom: "conv20" bottom: "power12" top: "mul3" eltwise_param { operation: PROD } } layer { name: "conv21" type: "Convolution" bottom: "mul3" top: "conv21" convolution_param { num_output: 80 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale21" type: "Scale" bottom: "conv21" top: "conv21" scale_param { bias_term: true } } layer { name: "conv22" type: "Convolution" bottom: "conv21" top: "conv22" convolution_param { num_output: 200 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale22" type: "Scale" bottom: "conv22" top: "conv22" scale_param { bias_term: true } } layer { name: "power13" type: "Power" bottom: "conv22" top: "power13" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus7" type: "ReLU6" bottom: "power13" top: "relus7" } layer { name: "power14" type: "Power" bottom: "relus7" top: "power14" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul4" type: "Eltwise" bottom: "conv22" bottom: "power14" top: "mul4" eltwise_param { operation: PROD } } layer { name: "conv23" type: "DepthwiseConvolution" bottom: "mul4" top: "conv23" convolution_param { num_output: 200 bias_term: false pad: 1 kernel_size: 3 group: 200 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale23" type: "Scale" bottom: "conv23" top: "conv23" scale_param { bias_term: true } } layer { name: "power15" type: "Power" bottom: "conv23" top: "power15" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus8" type: "ReLU6" bottom: "power15" top: "relus8" } layer { name: "power16" type: "Power" bottom: "relus8" top: "power16" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul5" type: "Eltwise" bottom: "conv23" bottom: "power16" top: "mul5" eltwise_param { operation: PROD } } layer { name: "conv24" type: "Convolution" bottom: "mul5" top: "conv24" convolution_param { num_output: 80 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale24" type: "Scale" bottom: "conv24" top: "conv24" scale_param { bias_term: true } } layer { name: "add5" type: "Eltwise" bottom: "conv21" bottom: "conv24" top: "add5" eltwise_param { operation: SUM } } layer { name: "conv25" type: "Convolution" bottom: "add5" top: "conv25" convolution_param { num_output: 184 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale25" type: "Scale" bottom: "conv25" top: "conv25" scale_param { bias_term: true } } layer { name: "power17" type: "Power" bottom: "conv25" top: "power17" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus9" type: "ReLU6" bottom: "power17" top: "relus9" } layer { name: "power18" type: "Power" bottom: "relus9" top: "power18" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul6" type: "Eltwise" bottom: "conv25" bottom: "power18" top: "mul6" eltwise_param { operation: PROD } } layer { name: "conv26" type: "DepthwiseConvolution" bottom: "mul6" top: "conv26" convolution_param { num_output: 184 bias_term: false pad: 1 kernel_size: 3 group: 184 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale26" type: "Scale" bottom: "conv26" top: "conv26" scale_param { bias_term: true } } layer { name: "power19" type: "Power" bottom: "conv26" top: "power19" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus10" type: "ReLU6" bottom: "power19" top: "relus10" } layer { name: "power20" type: "Power" bottom: "relus10" top: "power20" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul7" type: "Eltwise" bottom: "conv26" bottom: "power20" top: "mul7" eltwise_param { operation: PROD } } layer { name: "conv27" type: "Convolution" bottom: "mul7" top: "conv27" convolution_param { num_output: 80 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale27" type: "Scale" bottom: "conv27" top: "conv27" scale_param { bias_term: true } } layer { name: "add6" type: "Eltwise" bottom: "add5" bottom: "conv27" top: "add6" eltwise_param { operation: SUM } } layer { name: "conv28" type: "Convolution" bottom: "add6" top: "conv28" convolution_param { num_output: 184 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale28" type: "Scale" bottom: "conv28" top: "conv28" scale_param { bias_term: true } } layer { name: "power21" type: "Power" bottom: "conv28" top: "power21" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus11" type: "ReLU6" bottom: "power21" top: "relus11" } layer { name: "power22" type: "Power" bottom: "relus11" top: "power22" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul8" type: "Eltwise" bottom: "conv28" bottom: "power22" top: "mul8" eltwise_param { operation: PROD } } layer { name: "conv29" type: "DepthwiseConvolution" bottom: "mul8" top: "conv29" convolution_param { num_output: 184 bias_term: false pad: 1 kernel_size: 3 group: 184 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale29" type: "Scale" bottom: "conv29" top: "conv29" scale_param { bias_term: true } } layer { name: "power23" type: "Power" bottom: "conv29" top: "power23" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus12" type: "ReLU6" bottom: "power23" top: "relus12" } layer { name: "power24" type: "Power" bottom: "relus12" top: "power24" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul9" type: "Eltwise" bottom: "conv29" bottom: "power24" top: "mul9" eltwise_param { operation: PROD } } layer { name: "conv30" type: "Convolution" bottom: "mul9" top: "conv30" convolution_param { num_output: 80 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale30" type: "Scale" bottom: "conv30" top: "conv30" scale_param { bias_term: true } } layer { name: "add7" type: "Eltwise" bottom: "add6" bottom: "conv30" top: "add7" eltwise_param { operation: SUM } } layer { name: "conv31" type: "Convolution" bottom: "add7" top: "conv31" convolution_param { num_output: 480 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale31" type: "Scale" bottom: "conv31" top: "conv31" scale_param { bias_term: true } } layer { name: "power25" type: "Power" bottom: "conv31" top: "power25" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus13" type: "ReLU6" bottom: "power25" top: "relus13" } layer { name: "power26" type: "Power" bottom: "relus13" top: "power26" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul10" type: "Eltwise" bottom: "conv31" bottom: "power26" top: "mul10" eltwise_param { operation: PROD } } layer { name: "conv32" type: "DepthwiseConvolution" bottom: "mul10" top: "conv32" convolution_param { num_output: 480 bias_term: false pad: 1 kernel_size: 3 group: 480 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale32" type: "Scale" bottom: "conv32" top: "conv32" scale_param { bias_term: true } } layer { name: "ave_pool4" type: "Pooling" bottom: "conv32" top: "ave_pool4" pooling_param { pool: AVE global_pooling: true } } layer { name: "route7" type: "Concat" bottom: "ave_pool4" top: "route7" } layer { name: "fc7" type: "InnerProduct" bottom: "route7" top: "fc7" inner_product_param { num_output: 120 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "relu15" type: "ReLU" bottom: "fc7" top: "relu15" } layer { name: "fc8" type: "InnerProduct" bottom: "relu15" top: "fc8" inner_product_param { num_output: 480 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "power27" type: "Power" bottom: "fc8" top: "power27" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus14" type: "ReLU6" bottom: "power27" top: "relus14" } layer { name: "power28" type: "Power" bottom: "relus14" top: "power28" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "route8" type: "Concat" bottom: "power28" top: "route8" } layer { name: "scale4" type: "Scale" bottom: "conv32" bottom: "route8" top: "scale4" scale_param { axis: 0 } } layer { name: "power29" type: "Power" bottom: "scale4" top: "power29" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus15" type: "ReLU6" bottom: "power29" top: "relus15" } layer { name: "power30" type: "Power" bottom: "relus15" top: "power30" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul11" type: "Eltwise" bottom: "scale4" bottom: "power30" top: "mul11" eltwise_param { operation: PROD } } layer { name: "conv33" type: "Convolution" bottom: "mul11" top: "conv33" convolution_param { num_output: 112 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale33" type: "Scale" bottom: "conv33" top: "conv33" scale_param { bias_term: true } } layer { name: "conv34" type: "Convolution" bottom: "conv33" top: "conv34" convolution_param { num_output: 672 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale34" type: "Scale" bottom: "conv34" top: "conv34" scale_param { bias_term: true } } layer { name: "power31" type: "Power" bottom: "conv34" top: "power31" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus16" type: "ReLU6" bottom: "power31" top: "relus16" } layer { name: "power32" type: "Power" bottom: "relus16" top: "power32" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul12" type: "Eltwise" bottom: "conv34" bottom: "power32" top: "mul12" eltwise_param { operation: PROD } } layer { name: "conv35" type: "DepthwiseConvolution" bottom: "mul12" top: "conv35" convolution_param { num_output: 672 bias_term: false pad: 1 kernel_size: 3 group: 672 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale35" type: "Scale" bottom: "conv35" top: "conv35" scale_param { bias_term: true } } layer { name: "ave_pool5" type: "Pooling" bottom: "conv35" top: "ave_pool5" pooling_param { pool: AVE global_pooling: true } } layer { name: "route9" type: "Concat" bottom: "ave_pool5" top: "route9" } layer { name: "fc9" type: "InnerProduct" bottom: "route9" top: "fc9" inner_product_param { num_output: 168 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "relu16" type: "ReLU" bottom: "fc9" top: "relu16" } layer { name: "fc10" type: "InnerProduct" bottom: "relu16" top: "fc10" inner_product_param { num_output: 672 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "power33" type: "Power" bottom: "fc10" top: "power33" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus17" type: "ReLU6" bottom: "power33" top: "relus17" } layer { name: "power34" type: "Power" bottom: "relus17" top: "power34" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "route10" type: "Concat" bottom: "power34" top: "route10" } layer { name: "scale5" type: "Scale" bottom: "conv35" bottom: "route10" top: "scale5" scale_param { axis: 0 } } layer { name: "power35" type: "Power" bottom: "scale5" top: "power35" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus18" type: "ReLU6" bottom: "power35" top: "relus18" } layer { name: "power36" type: "Power" bottom: "relus18" top: "power36" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul13" type: "Eltwise" bottom: "scale5" bottom: "power36" top: "mul13" eltwise_param { operation: PROD } } layer { name: "conv36" type: "Convolution" bottom: "mul13" top: "conv36" convolution_param { num_output: 112 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale36" type: "Scale" bottom: "conv36" top: "conv36" scale_param { bias_term: true } } layer { name: "add8" type: "Eltwise" bottom: "conv33" bottom: "conv36" top: "add8" eltwise_param { operation: SUM } } layer { name: "conv37" type: "Convolution" bottom: "add8" top: "conv37" convolution_param { num_output: 672 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale37" type: "Scale" bottom: "conv37" top: "conv37" scale_param { bias_term: true } } layer { name: "power37" type: "Power" bottom: "conv37" top: "power37" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus19" type: "ReLU6" bottom: "power37" top: "relus19" } layer { name: "power38" type: "Power" bottom: "relus19" top: "power38" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul14" type: "Eltwise" bottom: "conv37" bottom: "power38" top: "mul14" eltwise_param { operation: PROD } } layer { name: "conv38" type: "DepthwiseConvolution" bottom: "mul14" top: "conv38" convolution_param { num_output: 672 bias_term: false pad: 2 kernel_size: 5 group: 672 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale38" type: "Scale" bottom: "conv38" top: "conv38" scale_param { bias_term: true } } layer { name: "ave_pool6" type: "Pooling" bottom: "conv38" top: "ave_pool6" pooling_param { pool: AVE global_pooling: true } } layer { name: "route11" type: "Concat" bottom: "ave_pool6" top: "route11" } layer { name: "fc11" type: "InnerProduct" bottom: "route11" top: "fc11" inner_product_param { num_output: 168 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "relu17" type: "ReLU" bottom: "fc11" top: "relu17" } layer { name: "fc12" type: "InnerProduct" bottom: "relu17" top: "fc12" inner_product_param { num_output: 672 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "power39" type: "Power" bottom: "fc12" top: "power39" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus20" type: "ReLU6" bottom: "power39" top: "relus20" } layer { name: "power40" type: "Power" bottom: "relus20" top: "power40" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "route12" type: "Concat" bottom: "power40" top: "route12" } layer { name: "scale6" type: "Scale" bottom: "conv38" bottom: "route12" top: "scale6" scale_param { axis: 0 } } layer { name: "power41" type: "Power" bottom: "scale6" top: "power41" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus21" type: "ReLU6" bottom: "power41" top: "relus21" } layer { name: "power42" type: "Power" bottom: "relus21" top: "power42" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul15" type: "Eltwise" bottom: "scale6" bottom: "power42" top: "mul15" eltwise_param { operation: PROD } } layer { name: "conv39" type: "Convolution" bottom: "mul15" top: "conv39" convolution_param { num_output: 160 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale39" type: "Scale" bottom: "conv39" top: "conv39" scale_param { bias_term: true } } layer { name: "conv40" type: "Convolution" bottom: "conv39" top: "conv40" convolution_param { num_output: 672 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale40" type: "Scale" bottom: "conv40" top: "conv40" scale_param { bias_term: true } } layer { name: "power43" type: "Power" bottom: "conv40" top: "power43" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus22" type: "ReLU6" bottom: "power43" top: "relus22" } layer { name: "power44" type: "Power" bottom: "relus22" top: "power44" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul16" type: "Eltwise" bottom: "conv40" bottom: "power44" top: "mul16" eltwise_param { operation: PROD } } layer { name: "conv41" type: "DepthwiseConvolution" bottom: "mul16" top: "conv41" convolution_param { num_output: 672 bias_term: false pad: 2 kernel_size: 5 group: 672 stride: 2 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale41" type: "Scale" bottom: "conv41" top: "conv41" scale_param { bias_term: true } } layer { name: "ave_pool7" type: "Pooling" bottom: "conv41" top: "ave_pool7" pooling_param { pool: AVE global_pooling: true } } layer { name: "route13" type: "Concat" bottom: "ave_pool7" top: "route13" } layer { name: "fc13" type: "InnerProduct" bottom: "route13" top: "fc13" inner_product_param { num_output: 168 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "relu18" type: "ReLU" bottom: "fc13" top: "relu18" } layer { name: "fc14" type: "InnerProduct" bottom: "relu18" top: "fc14" inner_product_param { num_output: 672 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "power45" type: "Power" bottom: "fc14" top: "power45" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus23" type: "ReLU6" bottom: "power45" top: "relus23" } layer { name: "power46" type: "Power" bottom: "relus23" top: "power46" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "route14" type: "Concat" bottom: "power46" top: "route14" } layer { name: "scale7" type: "Scale" bottom: "conv41" bottom: "route14" top: "scale7" scale_param { axis: 0 } } layer { name: "power47" type: "Power" bottom: "scale7" top: "power47" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus24" type: "ReLU6" bottom: "power47" top: "relus24" } layer { name: "power48" type: "Power" bottom: "relus24" top: "power48" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul17" type: "Eltwise" bottom: "scale7" bottom: "power48" top: "mul17" eltwise_param { operation: PROD } } layer { name: "conv42" type: "Convolution" bottom: "mul17" top: "conv42" convolution_param { num_output: 160 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale42" type: "Scale" bottom: "conv42" top: "conv42" scale_param { bias_term: true } } layer { name: "conv43" type: "Convolution" bottom: "conv42" top: "conv43" convolution_param { num_output: 960 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale43" type: "Scale" bottom: "conv43" top: "conv43" scale_param { bias_term: true } } layer { name: "power49" type: "Power" bottom: "conv43" top: "power49" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus25" type: "ReLU6" bottom: "power49" top: "relus25" } layer { name: "power50" type: "Power" bottom: "relus25" top: "power50" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul18" type: "Eltwise" bottom: "conv43" bottom: "power50" top: "mul18" eltwise_param { operation: PROD } } layer { name: "conv44" type: "DepthwiseConvolution" bottom: "mul18" top: "conv44" convolution_param { num_output: 960 bias_term: false pad: 2 kernel_size: 5 group: 960 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale44" type: "Scale" bottom: "conv44" top: "conv44" scale_param { bias_term: true } } layer { name: "ave_pool8" type: "Pooling" bottom: "conv44" top: "ave_pool8" pooling_param { pool: AVE global_pooling: true } } layer { name: "route15" type: "Concat" bottom: "ave_pool8" top: "route15" } layer { name: "fc15" type: "InnerProduct" bottom: "route15" top: "fc15" inner_product_param { num_output: 240 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "relu19" type: "ReLU" bottom: "fc15" top: "relu19" } layer { name: "fc16" type: "InnerProduct" bottom: "relu19" top: "fc16" inner_product_param { num_output: 960 bias_term: true weight_filler { type: "xavier" } bias_filler { type: "constant" } } } layer { name: "power51" type: "Power" bottom: "fc16" top: "power51" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus26" type: "ReLU6" bottom: "power51" top: "relus26" } layer { name: "power52" type: "Power" bottom: "relus26" top: "power52" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "route16" type: "Concat" bottom: "power52" top: "route16" } layer { name: "scale8" type: "Scale" bottom: "conv44" bottom: "route16" top: "scale8" scale_param { axis: 0 } } layer { name: "power53" type: "Power" bottom: "scale8" top: "power53" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus27" type: "ReLU6" bottom: "power53" top: "relus27" } layer { name: "power54" type: "Power" bottom: "relus27" top: "power54" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul19" type: "Eltwise" bottom: "scale8" bottom: "power54" top: "mul19" eltwise_param { operation: PROD } } layer { name: "conv45" type: "Convolution" bottom: "mul19" top: "conv45" convolution_param { num_output: 160 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale45" type: "Scale" bottom: "conv45" top: "conv45" scale_param { bias_term: true } } layer { name: "add9" type: "Eltwise" bottom: "conv42" bottom: "conv45" top: "add9" eltwise_param { operation: SUM } } layer { name: "conv46" type: "Convolution" bottom: "add9" top: "conv46" convolution_param { num_output: 960 bias_term: false pad: 0 kernel_size: 1 group: 1 stride: 1 weight_filler { type: "xavier" } dilation: 1 } } layer { name: "bn_scale46" type: "Scale" bottom: "conv46" top: "conv46" scale_param { bias_term: true } } layer { name: "power55" type: "Power" bottom: "conv46" top: "power55" power_param { power: 1.0 scale: 1.0 shift: 3.0 } } layer { name: "relus28" type: "ReLU6" bottom: "power55" top: "relus28" } layer { name: "power56" type: "Power" bottom: "relus28" top: "power56" power_param { power: 1.0 scale: 0.1666666716337204 shift: 0.0 } } layer { name: "mul20" type: "Eltwise" bottom: "conv46" bottom: "power56" top: "mul20" eltwise_param { operation: PROD } }
layer { name: "yolo/conv1/dw" type: "DepthwiseConvolution" bottom: "mul20" top: "yolo/conv1/dw" param { lr_mult: 1 decay_mult: 1 } convolution_param { num_output: 960 bias_term: false pad: 1 kernel_size: 3 group: 960 engine: CAFFE weight_filler { type: "msra" } } }
layer { name: "yolo/conv1/dw/scale" type: "Scale" bottom: "yolo/conv1/dw" top: "yolo/conv1/dw" param { lr_mult: 1 decay_mult: 0.0 } param { lr_mult: 2 decay_mult: 0.0 } scale_param { filler { value: 1 } bias_term: true bias_filler { value: 0 } } } layer { name: "yolo/conv1/dw/relu" type: "ReLU" bottom: "yolo/conv1/dw" top: "yolo/conv1/dw" } layer { name: "yolo/conv1" type: "Convolution" bottom: "yolo/conv1/dw" top: "yolo/conv1" param { lr_mult: 1 decay_mult: 1 } convolution_param { num_output: 672 bias_term: false kernel_size: 1 weight_filler { type: "msra" } } } layer { name: "yolo/conv1/scale" type: "Scale" bottom: "yolo/conv1" top: "yolo/conv1" param { lr_mult: 1 decay_mult: 0.0 } param { lr_mult: 2 decay_mult: 0.0 } scale_param { filler { value: 1 } bias_term: true bias_filler { value: 0 } } } layer { name: "yolo/conv1/relu" type: "ReLU" bottom: "yolo/conv1" top: "yolo/conv1" } layer { name: "upsample" type: "Deconvolution" bottom: "yolo/conv1" top: "upsample" param { lr_mult: 0 decay_mult: 0 } convolution_param { num_output: 672 group: 672 kernel_size: 1 stride: 2 pad: 0 weight_filler: { type: "constant" value : 1 } bias_term: false } }
layer {
top: "maxpool" name: "maxpool" bottom: "upsample" type: "Pooling" pooling_param { kernel_size: 2 stride: 1 pool: MAX pad: 1 } } layer { name: "yolo/conv2/dw" type: "DepthwiseConvolution" bottom: "mul16" top: "yolo/conv2/dw" param { lr_mult: 1 decay_mult: 1 } convolution_param { num_output: 672 bias_term: false pad: 1 kernel_size: 3 group: 672 engine: CAFFE weight_filler { type: "msra" } } } layer { name: "yolo/conv2/dw/scale" type: "Scale" bottom: "yolo/conv2/dw" top: "yolo/conv2/dw" param { lr_mult: 1 decay_mult: 0.0 } param { lr_mult: 2 decay_mult: 0.0 } scale_param { filler { value: 1 } bias_term: true bias_filler { value: 0 } } } layer { name: "yolo/conv2/dw/relu" type: "ReLU" bottom: "yolo/conv2/dw" top: "yolo/conv2/dw" } layer { name: "yolo/conv2" type: "Convolution" bottom: "yolo/conv2/dw" top: "yolo/conv2" param { lr_mult: 1 decay_mult: 1 } convolution_param { num_output: 672 bias_term: false kernel_size: 1 weight_filler { type: "msra" } } } layer { name: "yolo/conv2/scale" type: "Scale" bottom: "yolo/conv2" top: "yolo/conv2" param { lr_mult: 1 decay_mult: 0.0 } param { lr_mult: 2 decay_mult: 0.0 } scale_param { filler { value: 1 } bias_term: true bias_filler { value: 0 } } } layer { name: "yolo/conv2/relu" type: "ReLU" bottom: "yolo/conv2" top: "yolo/conv2" } layer { name: "yolo/conv2/sum" type: "Eltwise" bottom: "maxpool" bottom: "yolo/conv2" top: "yolo/conv2/sum" }
layer { name: "yolo/conv3/dw" type: "DepthwiseConvolution" bottom: "yolo/conv2/sum" top: "yolo/conv3/dw" param { lr_mult: 1 decay_mult: 1 } convolution_param { num_output: 672 bias_term: false pad: 1 kernel_size: 3 group: 672 engine: CAFFE weight_filler { type: "msra" } } } layer { name: "yolo/conv3/dw/scale" type: "Scale" bottom: "yolo/conv3/dw" top: "yolo/conv3/dw" param { lr_mult: 1 decay_mult: 0.0 } param { lr_mult: 2 decay_mult: 0.0 } scale_param { filler { value: 1 } bias_term: true bias_filler { value: 0 } } } layer { name: "yolo/conv3/dw/relu" type: "ReLU" bottom: "yolo/conv3/dw" top: "yolo/conv3/dw" } layer { name: "yolo/conv3" type: "Convolution" bottom: "yolo/conv3/dw" top: "yolo/conv3" param { lr_mult: 1 decay_mult: 1 } convolution_param { num_output: 672 bias_term: false kernel_size: 1 weight_filler { type: "msra" } } } layer { name: "yolo/conv3/scale" type: "Scale" bottom: "yolo/conv3" top: "yolo/conv3" param { lr_mult: 1 decay_mult: 0.0 } param { lr_mult: 2 decay_mult: 0.0 } scale_param { filler { value: 1 } bias_term: true bias_filler { value: 0 } } } layer { name: "yolo/conv3/relu" type: "ReLU" bottom: "yolo/conv3" top: "yolo/conv3" } layer { name: "yolo/conv4" type: "Convolution" bottom: "yolo/conv1" top: "yolo/conv4" param { lr_mult: 1 decay_mult: 1 } param { lr_mult: 2 decay_mult: 0 } convolution_param { num_output: 18 kernel_size: 1 pad: 0 stride: 1 weight_filler { type: "msra" } bias_filler { value: 0 } } }
layer { name: "yolo/conv5" type: "Convolution" bottom: "yolo/conv3" top: "yolo/conv5" param { lr_mult: 1 decay_mult: 1 } param { lr_mult: 2 decay_mult: 0 } convolution_param { num_output: 18 kernel_size: 1 pad: 0 stride: 1 weight_filler { type: "msra" } bias_filler { value: 0 } } } layer { name: "detection_out" type: "Yolov3DetectionOutput" bottom: "yolo/conv4" bottom: "yolo/conv5" top: "detection_out" yolov3_detection_output_param { confidence_threshold: 0.01 nms_threshold: 0.45 num_classes: 1
} }