hao
e817b94dd8
1. 引入异常机制，捕获opencv抛出的异常并转抛给PHP业务代码 2. 新增confidence可信度要求参数和modelpath模型文件夹路径 3. 修改tests中的测试demo 4. 从Prj-Linux复制model文件到tests文件夹 5. 更新readme说明
123 lines
1.8 KiB
Plaintext
123 lines
1.8 KiB
Plaintext
input: "data"
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input_dim: 1
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input_dim: 1
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input_dim: 30
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input_dim: 14
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layer {
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name: "conv2d_1"
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type: "Convolution"
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bottom: "data"
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top: "conv2d_1"
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convolution_param {
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num_output: 32
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bias_term: true
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pad: 0
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kernel_size: 3
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stride: 1
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}
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}
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layer {
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name: "activation_1"
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type: "ReLU"
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bottom: "conv2d_1"
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top: "activation_1"
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}
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layer {
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name: "max_pooling2d_1"
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type: "Pooling"
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bottom: "activation_1"
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top: "max_pooling2d_1"
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pooling_param {
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pool: MAX
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kernel_size: 2
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stride: 2
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pad: 0
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}
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}
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layer {
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name: "conv2d_2"
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type: "Convolution"
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bottom: "max_pooling2d_1"
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top: "conv2d_2"
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convolution_param {
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num_output: 64
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bias_term: true
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pad: 0
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kernel_size: 3
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stride: 1
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}
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}
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layer {
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name: "activation_2"
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type: "ReLU"
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bottom: "conv2d_2"
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top: "activation_2"
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}
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layer {
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name: "max_pooling2d_2"
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type: "Pooling"
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bottom: "activation_2"
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top: "max_pooling2d_2"
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pooling_param {
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pool: MAX
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kernel_size: 2
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stride: 2
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pad: 0
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}
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}
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layer {
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name: "conv2d_3"
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type: "Convolution"
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bottom: "max_pooling2d_2"
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top: "conv2d_3"
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convolution_param {
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num_output: 128
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bias_term: true
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pad: 0
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kernel_size: 2
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stride: 1
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}
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}
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layer {
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name: "activation_3"
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type: "ReLU"
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bottom: "conv2d_3"
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top: "activation_3"
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}
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layer {
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name: "flatten_1"
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type: "Flatten"
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bottom: "activation_3"
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top: "flatten_1"
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}
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layer {
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name: "dense_1"
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type: "InnerProduct"
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bottom: "flatten_1"
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top: "dense_1"
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inner_product_param {
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num_output: 256
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}
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}
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layer {
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name: "relu2"
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type: "ReLU"
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bottom: "dense_1"
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top: "relu2"
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}
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layer {
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name: "dense2"
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type: "InnerProduct"
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bottom: "relu2"
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top: "dense2"
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inner_product_param {
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num_output: 65
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}
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}
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layer {
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name: "prob"
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type: "Softmax"
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bottom: "dense2"
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top: "prob"
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} |