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‎.gitignore

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.vs/MTCNN/v14/.suo
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bin/
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train/
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x64/

‎CMakeLists.txt

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cmake_minimum_required(VERSION 2.8)
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project(MTCNN)
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set(CMAKE_CXX_STANDARD 11)
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find_package(OpenCV REQUIRED)
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option(BUILD_CAFFE "build with caffe" ON)
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option(BUILD_NCNN "build with ncnn" ON)
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#default build light, only depend on openblas
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add_subdirectory(MTCNN-light)
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#need opencv version >= 3.4.* or recompile opencv with conrtib module
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#add_subdirectory(Fast-MTCNN)
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if(BUILD_CAFFE)
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find_package(Caffe REQUIRED)
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include_directories(${Caffe_INCLUDE_DIRS})
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add_subdirectory(cpp)
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endif()
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if(BUILD_NCNN)
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add_subdirectory(ncnn)
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endif()

‎Fast-MTCNN/CMakeLists.txt

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AUX_SOURCE_DIRECTORY(./ SRC_FILES)
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set(DEMO_NAME Fast-MTCNN)
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add_executable(${DEMO_NAME} ${SRC_FILES})
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target_link_libraries(${DEMO_NAME} ${OpenCV_LIBS})

‎Fast-MTCNN/Fast-MTCNN.vcxproj

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<Configuration>Release</Configuration>
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<Configuration>Debug</Configuration>
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<Configuration>Release</Configuration>
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<Keyword>Win32Proj</Keyword>
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<RootNamespace>FastMTCNN</RootNamespace>
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<WindowsTargetPlatformVersion>8.1</WindowsTargetPlatformVersion>
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‎Fast-MTCNN/model/det1.prototxt

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name: "PNet"
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input: "data"
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input_dim: 1
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input_dim: 3
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input_dim: 12
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input_dim: 12
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layer {
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name: "conv1"
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type: "Convolution"
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bottom: "data"
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top: "conv1"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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param {
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lr_mult: 2
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decay_mult: 0
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}
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convolution_param {
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num_output: 10
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kernel_size: 3
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stride: 1
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weight_filler {
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type: "xavier"
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}
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bias_filler {
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type: "constant"
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value: 0
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}
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}
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}
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layer {
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name: "PReLU1"
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type: "PReLU"
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bottom: "conv1"
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top: "conv1"
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}
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layer {
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name: "pool1"
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type: "Pooling"
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bottom: "conv1"
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top: "pool1"
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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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}
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}
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layer {
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name: "conv2"
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type: "Convolution"
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bottom: "pool1"
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top: "conv2"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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param {
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lr_mult: 2
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decay_mult: 0
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}
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convolution_param {
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num_output: 16
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kernel_size: 3
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stride: 1
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weight_filler {
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type: "xavier"
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}
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bias_filler {
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type: "constant"
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value: 0
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}
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}
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}
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layer {
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name: "PReLU2"
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type: "PReLU"
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bottom: "conv2"
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top: "conv2"
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}
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layer {
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name: "conv3"
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type: "Convolution"
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bottom: "conv2"
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top: "conv3"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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param {
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lr_mult: 2
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decay_mult: 0
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}
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convolution_param {
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num_output: 32
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kernel_size: 3
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stride: 1
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weight_filler {
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type: "xavier"
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}
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bias_filler {
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type: "constant"
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value: 0
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}
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}
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}
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layer {
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name: "PReLU3"
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type: "PReLU"
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bottom: "conv3"
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top: "conv3"
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}
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layer {
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name: "conv4-1"
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type: "Convolution"
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bottom: "conv3"
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top: "conv4-1"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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param {
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lr_mult: 2
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decay_mult: 0
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}
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convolution_param {
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num_output: 2
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kernel_size: 1
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stride: 1
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weight_filler {
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type: "xavier"
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}
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bias_filler {
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type: "constant"
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value: 0
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}
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}
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}
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layer {
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name: "conv4-2"
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type: "Convolution"
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bottom: "conv3"
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top: "conv4-2"
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param {
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lr_mult: 1
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decay_mult: 1
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}
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param {
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lr_mult: 2
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decay_mult: 0
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}
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convolution_param {
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num_output: 4
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kernel_size: 1
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stride: 1
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weight_filler {
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type: "xavier"
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}
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bias_filler {
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type: "constant"
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value: 0
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}
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}
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}
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layer {
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name: "prob1"
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type: "Softmax"
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bottom: "conv4-1"
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top: "prob1"
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}

‎Fast-MTCNN/model/det1_.caffemodel

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