├── LAB.cpp
├── Makefile.config
├── README.md
└── compile.sh


/LAB.cpp:
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 1 | #include <string>
 2 | #include <vector>
 3 | #include "opencv2/opencv.hpp"
 4 | #include "caffe/caffe.hpp"
 5 | using namespace std;
 6 | using namespace cv;
 7 | using namespace caffe;
 8 | inline void Copy(const cv::Mat& cv_mat, caffe::Blob<float>& blob) {
 9 | 	blob.Reshape(1, cv_mat.channels(), cv_mat.rows, cv_mat.cols);
10 | 	if(cv_mat.channels()==1) {
11 | 		memcpy(blob.mutable_cpu_data(), cv_mat.data, blob.count()*sizeof(float));
12 | 	}
13 | 	else {
14 | 		std::vector<cv::Mat> splited_img;
15 | 		cv::split(cv_mat, splited_img);
16 | 		for(size_t i=0; i<splited_img.size(); i++)
17 | 			memcpy(blob.mutable_cpu_data()+blob.count(2)*i, splited_img[i].data, blob.count(2)*sizeof(float));
18 | 	}
19 | }
20 | template <typename T>
21 | inline std::vector<T> ToVector(const caffe::Blob<T>& blob) {
22 | 	std::vector<T> vec(blob.count());
23 | 	memcpy(vec.data(), blob.cpu_data(), vec.size()*sizeof(T));
24 | 	return vec;
25 | }
26 | 
27 | inline std::vector<cv::Point2f> ToPoints(const std::vector<float>& labels) {
28 | 	std::vector<cv::Point2f> points(labels.size()/2);
29 | 	for(size_t i=0; i<points.size(); i++) {
30 | 		points[i].x=labels[2*i];
31 | 		points[i].y=labels[2*i+1];
32 | 	}
33 | 	return points;
34 | }
35 | void ConvertImageToGray(Mat &image) {
36 | 	if(image.channels()==1)
37 | 		return;
38 | 	else if(image.channels()==3) {
39 | 		cvtColor(image, image, CV_BGR2GRAY);
40 | 		return;
41 | 	}
42 | }
43 | void NormalizeImage(Mat &img) {
44 | 	Mat mean;
45 | 	Mat std;
46 | 	meanStdDev(img, mean, std);
47 | 	for(int i=0;i<img.channels();i++) {
48 | 		if(std.at<double>(i, 0)<1E-6)
49 | 			std.at<double>(i, 0)=1;
50 | 	}
51 | 	vector<Mat> split_img(img.channels());
52 | 	split(img, &(split_img[0]));
53 | 	for(int i=0;i<img.channels();i++)
54 | 		split_img[i].convertTo(split_img[i], CV_32F, 1.0/std.at<double>(i, 0), -1*mean.at<double>(i, 0)/std.at<double>(i, 0));
55 | 	merge(&(split_img[0]), img.channels(), img);
56 | }
57 | int main(void) {
58 |     string FLAGS_model_path="./models/";
59 |     caffe::Caffe::set_mode(caffe::Caffe::CPU);
60 |     string imgPath = "./faceImg.jpg";
61 |     caffe::shared_ptr<Net<float>> deep_align;
62 |     caffe::shared_ptr<Blob<float>> input_blob;
63 |     caffe::shared_ptr<Blob<float>> output_blob;
64 |     deep_align.reset(new Net<float>(FLAGS_model_path+"rel.prototxt", TEST));
65 |     deep_align->CopyTrainedLayersFrom(FLAGS_model_path+"model.bin");
66 |     input_blob=deep_align->blob_by_name("data");
67 |     output_blob=deep_align->blob_by_name("result");
68 |     Mat image=imread(imgPath);
69 |     cv::resize(image,image,cv::Size(256,256));
70 |     Mat show = image.clone();
71 |     ConvertImageToGray(image);
72 |     image.convertTo(image, CV_32F);
73 |     NormalizeImage(image);
74 |     Copy(image, *(input_blob));
75 |     deep_align->Forward();
76 |     vector<Point2f> landmark_98pt=ToPoints(ToVector(*(output_blob)));
77 |     for(uint i=0; i<landmark_98pt.size(); i++){
78 |         cv::circle(show,cv::Point(int(landmark_98pt[i].x),int(landmark_98pt[i].y)),0.1,cv::Scalar(0,255,0), 4, 8, 0);
79 |     }
80 |     imshow("tracking", show);
81 |     waitKey(0);
82 |     return 0;
83 | }
84 | 


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/Makefile.config:
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  1 | ## Refer to http://caffe.berkeleyvision.org/installation.html
  2 | # Contributions simplifying and improving our build system are welcome!
  3 | 
  4 | # cuDNN acceleration switch (uncomment to build with cuDNN).
  5 | # USE_CUDNN := 1
  6 | 
  7 | # CPU-only switch (uncomment to build without GPU support).
  8 | # CPU_ONLY := 0
  9 | 
 10 | # uncomment to disable IO dependencies and corresponding data layers
 11 | # USE_OPENCV := 0
 12 | # USE_LEVELDB := 1
 13 | # USE_LMDB := 1
 14 | 
 15 | # uncomment to allow MDB_NOLOCK when reading LMDB files (only if necessary)
 16 | #	You should not set this flag if you will be reading LMDBs with any
 17 | #	possibility of simultaneous read and write
 18 | # ALLOW_LMDB_NOLOCK := 1
 19 | 
 20 | # Uncomment if you're using OpenCV 3
 21 | # OPENCV_VERSION := 3
 22 | 
 23 | # To customize your choice of compiler, uncomment and set the following.
 24 | # N.B. the default for Linux is g++ and the default for OSX is clang++
 25 | # CUSTOM_CXX := g++
 26 | CXXFLAGS := -std=c++11 -O3 -Wno-reorder -fopenmp
 27 | LDFLAGS := -fopenmp
 28 | NVCCFLAGS := -std=c++11
 29 | 
 30 | # CUDA directory contains bin/ and lib/ directories that we need.
 31 | CUDA_DIR := /usr/local/cuda
 32 | # On Ubuntu 14.04, if cuda tools are installed via
 33 | # "sudo apt-get install nvidia-cuda-toolkit" then use this instead:
 34 | # CUDA_DIR := /usr
 35 | 
 36 | # CUDA architecture setting: going with all of them.
 37 | # For CUDA < 6.0, comment the *_50 through *_61 lines for compatibility.
 38 | # For CUDA < 8.0, comment the *_60 and *_61 lines for compatibility.
 39 | # For CUDA >= 9.0, comment the *_20 and *_21 lines for compatibility.
 40 | CUDA_ARCH := -gencode arch=compute_30,code=sm_30 \
 41 | 		-gencode arch=compute_35,code=sm_35 \
 42 | 		-gencode arch=compute_50,code=sm_50 \
 43 | 		-gencode arch=compute_52,code=sm_52 \
 44 | 		-gencode arch=compute_60,code=sm_60 \
 45 | 		-gencode arch=compute_61,code=sm_61 \
 46 | 		-gencode arch=compute_61,code=compute_61
 47 | 
 48 | # BLAS choice:
 49 | # atlas for ATLAS (default)
 50 | # mkl for MKL
 51 | # open for OpenBlas
 52 | BLAS := atlas
 53 | # Custom (MKL/ATLAS/OpenBLAS) include and lib directories.
 54 | # Leave commented to accept the defaults for your choice of BLAS
 55 | # (which should work)!
 56 | # BLAS_INCLUDE := /media/hans/4ddb33c4-42d9-4544-b7b4-796994f061ce/enviroments/OpenBLAS/include
 57 | # BLAS_LIB := /media/hans/4ddb33c4-42d9-4544-b7b4-796994f061ce/enviroments/OpenBLAS/lib
 58 | 
 59 | # Homebrew puts openblas in a directory that is not on the standard search path
 60 | # BLAS_INCLUDE := $(shell brew --prefix openblas)/include
 61 | # BLAS_LIB := $(shell brew --prefix openblas)/lib
 62 | 
 63 | # This is required only if you will compile the matlab interface.
 64 | # MATLAB directory should contain the mex binary in /bin.
 65 | # MATLAB_DIR := /usr/local
 66 | # MATLAB_DIR := /Applications/MATLAB_R2012b.app
 67 | 
 68 | # NOTE: this is required only if you will compile the python interface.
 69 | # We need to be able to find Python.h and numpy/arrayobject.h.
 70 | PYTHON_INCLUDE := /usr/include/python2.7 \
 71 | 		/usr/local/lib/python2.7/dist-packages/numpy/core/include
 72 | # Anaconda Python distribution is quite popular. Include path:
 73 | # Verify anaconda location, sometimes it's in root.
 74 | # ANACONDA_HOME := $(HOME)/anaconda
 75 | # PYTHON_INCLUDE := $(ANACONDA_HOME)/include \
 76 | 		# $(ANACONDA_HOME)/include/python2.7 \
 77 | 		# $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include
 78 | 
 79 | # Uncomment to use Python 3 (default is Python 2)
 80 | # PYTHON_LIBRARIES := boost_python3 python3.5m
 81 | # PYTHON_INCLUDE := /usr/include/python3.5m \
 82 | #                 /usr/lib/python3.5/dist-packages/numpy/core/include
 83 | 
 84 | # We need to be able to find libpythonX.X.so or .dylib.
 85 | PYTHON_LIB := /usr/lib
 86 | # PYTHON_LIB := $(ANACONDA_HOME)/lib
 87 | 
 88 | # Homebrew installs numpy in a non standard path (keg only)
 89 | # PYTHON_INCLUDE += $(dir $(shell python -c 'import numpy.core; print(numpy.core.__file__)'))/include
 90 | # PYTHON_LIB += $(shell brew --prefix numpy)/lib
 91 | 
 92 | # Uncomment to support layers written in Python (will link against Python libs)
 93 | WITH_PYTHON_LAYER := 1
 94 | 
 95 | # Whatever else you find you need goes here.
 96 | INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial
 97 | LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu /usr/lib/x86_64-linux-gnu/hdf5/serial
 98 | 
 99 | # If Homebrew is installed at a non standard location (for example your home directory) and you use it for general dependencies
100 | # INCLUDE_DIRS += $(shell brew --prefix)/include
101 | # LIBRARY_DIRS += $(shell brew --prefix)/lib
102 | 
103 | # NCCL acceleration switch (uncomment to build with NCCL)
104 | # https://github.com/NVIDIA/nccl (last tested version: v1.2.3-1+cuda8.0)
105 | USE_NCCL := 1
106 | 
107 | # Uncomment to use `pkg-config` to specify OpenCV library paths.
108 | # (Usually not necessary -- OpenCV libraries are normally installed in one of the above $LIBRARY_DIRS.)
109 | # USE_PKG_CONFIG := 1
110 | 
111 | # N.B. both build and distribute dirs are cleared on `make clean`
112 | BUILD_DIR := build
113 | DISTRIBUTE_DIR := distribute
114 | 
115 | # Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171
116 | # DEBUG := 1
117 | 
118 | # The ID of the GPU that 'make runtest' will use to run unit tests.
119 | TEST_GPUID := 3
120 | 
121 | # enable pretty build (comment to see full commands)
122 | Q ?= @
123 | 


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/README.md:
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 1 | # Easy-LAB
 2 | 
 3 | Look at Boundary: A Boundary-Aware Face Alignment Algorithm
 4 | 
 5 | # Installing
 6 | 
 7 | 1.Download the **repo** below, as well as pretrained models
 8 | 
 9 | 2.Replace **Makefile.config**
10 | 
11 | 3.make all -j8
12 | 
13 | 4.run **compile.sh**
14 | 
15 | # Reference
16 | 
17 | https://github.com/wywu/LAB
18 | 


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/compile.sh:
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1 | #!/usr/bin/env bash
2 | export LD_LIBRARY_PATH=/home/hans/LAB-master/build/lib/:$LD_LIBRARY_PATH
3 | g++ -I/home/hans/LAB-master/include -I/home/hans/LAB-master/build/src -O0 -g3 -Wall -c -fmessage-length=0 -std=c++11 -O3 -D CPU_ONLY -MMD -MP -MF"LAB.d" -MT"LAB.o" -o "LAB.o" "./LAB.cpp"
4 | g++ -L/home/hans/LAB-master/build/lib -o "caffe_LAB"  ./LAB.o   -lcaffe -lglog -lopencv_core -lopencv_contrib -lprotobuf -lboost_system -lopencv_imgproc -lopencv_highgui
5 | 


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