name: "DL_FR" input: "data" input_dim:1 input_dim:3 input_dim:61 input_dim:61 ################# laye-1 layers { bottom: "data" top: "conv1/3x3_s2_1" name: "conv1/3x3_s2_1" type: CONVOLUTION convolution_param { num_output: 64 kernel_size: 3 stride: 2 } } layers { bottom: "conv1/3x3_s2_1" top: "conv1/3x3_s2_1" name: "conv1/relu_3x3" type: PRELU prelu_param { channel_shared: false } } layers { name: "conv1/norm1" type: LRN bottom: "conv1/3x3_s2_1" top: "conv1/norm1" lrn_param { local_size: 3 alpha: 0.0001 beta: 0.75 } } #####################layer-2 layers { bottom: "conv1/norm1" top: "conv2/3x3_s2_1" name: "conv2/3x3_s2_1" type: CONVOLUTION convolution_param { num_output: 128 kernel_size: 3 stride: 2 } } layers { bottom: "conv2/3x3_s2_1" top: "conv2/3x3_s2_1" name: "conv2/relu_3x3" type: PRELU prelu_param { channel_shared: false } } layers { name: "conv2/norm1" type: LRN bottom: "conv2/3x3_s2_1" top: "conv2/norm1" lrn_param { local_size: 3 alpha: 0.0001 beta: 0.75 } } ##################################### layer-3 layers { bottom: "conv2/norm1" top: "conv3/2x2_s2_1" name: "conv3/2x2_s2_1" type: CONVOLUTION convolution_param { num_output: 256 kernel_size: 2 stride: 2 } } layers { bottom: "conv3/2x2_s2_1" top: "conv3/2x2_s2_1" name: "conv3/relu_2x2_1" type: PRELU prelu_param { channel_shared: false } } layers { bottom: "conv3/2x2_s2_1" top: "conv3/2x2_s1_2" name: "conv3/2x2_s1_2" type: CONVOLUTION convolution_param { num_output: 384 kernel_size: 2 pad: 1 stride: 1 } } layers { bottom: "conv3/2x2_s1_2" top: "conv3/2x2_s1_2" name: "conv3/relu_2x2_2" type: PRELU prelu_param { channel_shared: false } } #####################layer-4 layers { bottom: "conv3/2x2_s1_2" top: "conv4/2x2_s1_1" name: "conv4/2x2_s1_1" type: CONVOLUTION convolution_param { num_output: 256 kernel_size: 2 stride: 1 } } layers { bottom: "conv4/2x2_s1_1" top: "conv4/2x2_s1_1" name: "conv4/relu_2x2_1" type: PRELU prelu_param { channel_shared: false } } layers { bottom: "conv4/2x2_s1_1" top: "conv4/2x2_s1_2" name: "conv4/2x2_s1_2" type: CONVOLUTION convolution_param { num_output: 128 kernel_size: 2 pad: 1 stride: 1 } } layers { bottom: "conv4/2x2_s1_2" top: "conv4/2x2_s1_2" name: "conv4/relu_2x2_2" type: PRELU prelu_param { channel_shared: false } } ##############4x4 bin layers { name: "pool4_1" type: POOLING bottom: "conv4/2x2_s1_2" top: "pool4_1" pooling_param { pool: MAX kernel_size: 2 stride: 2 } } layers { name: "pool4_1_flatten" type: FLATTEN bottom: "pool4_1" top: "pool4_1_flatten" } ###############2*2 bin layers { name: "pool4_2" type: POOLING bottom: "conv4/2x2_s1_2" top: "pool4_2" pooling_param { pool: MAX kernel_size: 4 stride: 4 } } layers { name: "pool4_2_flatten" type: FLATTEN bottom: "pool4_2" top: "pool4_2_flatten" } #############1*1 bin layers { name: "pool4_3" type: POOLING bottom: "conv4/2x2_s1_2" top: "pool4_3" pooling_param { pool: MAX kernel_size: 8 stride: 8 } } layers { name: "pool4_3_flatten" type: FLATTEN bottom: "pool4_3" top: "pool4_3_flatten" } layers { bottom: "pool4_1_flatten" bottom: "pool4_2_flatten" bottom: "pool4_3_flatten" top: "pool4_spp" name: "pool4_spp" type: CONCAT } ##########################fc-5 layers { name: "fc5" type: INNER_PRODUCT bottom: "pool4_spp" top: "fc5" inner_product_param { num_output: 512 } } layers { name: "relu5" type: PRELU bottom: "fc5" top: "fc5" prelu_param { channel_shared: false } } #layers { # name: "drop5" # type: DROPOUT # bottom: "fc5" # top: "fc5" # dropout_param { # dropout_ratio: 0.2 # } #} ##############fc-6 layers { name: "fc6" type: INNER_PRODUCT bottom: "fc5" top: "fc6" inner_product_param { num_output: 256 } } layers { name: "relu6" type: PRELU bottom: "fc6" top: "fc6" prelu_param { channel_shared: false } } #layers { # name: "drop6" # type: DROPOUT # bottom: "fc6" # top: "fc6" # dropout_param { # dropout_ratio: 0.1 # } #} #layers { # name: "fc7_face64" # type: INNER_PRODUCT # bottom: "fc6" # top: "fc7_face64" # inner_product_param { # num_output: 2193 # } #} #layers { # name: "accuracy_top1" # type: ACCURACY # bottom: "fc7_face64" # bottom: "label" # top: "accuracy_top1" # accuracy_param { # top_k: 1 # } # include: { phase: TEST } #} #layers { # name: "loss" # type: SOFTMAX_LOSS # bottom: "fc7_face64" # bottom: "label" # top: "loss" #}