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align_dataset.m
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align_dataset.m
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# MIT License
#
# Copyright (c) 2016 David Sandberg
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
% LFW
% source_path = '/home/david/datasets/lfw/raw';
% target_path = '/home/david/datasets/lfw/lfw_mtcnnalign_160';
% image_size = 160 + 0;
% margin = round(image_size*0.2) + 0;
% FaceScrub
% source_path = '/home/david/datasets/facescrub/facescrub/';
% target_path = '/home/david/datasets/facescrub/facescrub_mtcnnalign_182_160';
% failed_images_list = '/home/david/datasets/facescrub/facescrub_mtcnnalign_182_160/failed_images.txt';
% image_size = 160 + 12;
% margin = round(image_size*0.2) + 12;
source_path = '/home/david/datasets/casia/CASIA-maxpy-clean/';
target_path = '/home/david/datasets/casia/casia_maxpy_mtcnnalign_182_160';
failed_images_list = '/home/david/datasets/casia/casia_maxpy_mtcnnalign_182_160/failed_images.txt';
image_size = 160 + 12;
margin = round(image_size*0.2) + 12;
image_extension = 'png';
minsize=20; %minimum size of face
use_new = 0;
caffe_path='/home/david/repo2/caffe/matlab';
pdollar_toolbox_path='/home/david/repo2/toolbox';
if use_new
caffe_model_path='/home/david/repo2/MTCNN_face_detection_alignment/code/codes/MTCNNv2/model';
else
caffe_model_path='/home/david/repo2/MTCNN_face_detection_alignment/code/codes/MTCNNv1/model';
end;
addpath(genpath(caffe_path));
addpath(genpath(pdollar_toolbox_path));
caffe.set_mode_gpu();
caffe.set_device(0);
%three steps's threshold
threshold=[0.6 0.7 0.7];
%scale factor
factor=0.709;
%load caffe models
if use_new
prototxt_dir = strcat(caffe_model_path,'/det4.prototxt');
model_dir = strcat(caffe_model_path,'/det4.caffemodel');
end;
%faces=cell(0);
k = 0;
classes = dir(source_path);
%classes = classes(randperm(length(classes)));
for i=1:length(classes),
if classes(i).name(1)~='.'
source_class_path = sprintf('%s/%s', source_path, classes(i).name);
target_class_path = sprintf('%s/%s', target_path, classes(i).name);
imgs = dir(source_class_path);
%imgs = imgs(randperm(length(imgs)));
if ~exist(target_class_path, 'dir'),
mkdir(target_class_path);
end;
for j=1:length(imgs),
if imgs(j).isdir==0
[pathstr,name,ext] = fileparts(imgs(j).name);
target_img_path = sprintf('%s/%s.%s', target_class_path, name, image_extension);
if ~exist(target_img_path,'file') && any([ strcmpi(ext,'.jpg') strcmpi(ext,'.jpeg') strcmpi(ext,'.png') strcmpi(ext,'.gif') ])
if mod(k,1000)==0
fprintf('Resetting GPU\n');
caffe.reset_all();
caffe.set_mode_gpu();
caffe.set_device(0);
prototxt_dir = strcat(caffe_model_path,'/det1.prototxt');
model_dir = strcat(caffe_model_path,'/det1.caffemodel');
PNet=caffe.Net(prototxt_dir,model_dir,'test');
prototxt_dir = strcat(caffe_model_path,'/det2.prototxt');
model_dir = strcat(caffe_model_path,'/det2.caffemodel');
RNet=caffe.Net(prototxt_dir,model_dir,'test');
prototxt_dir = strcat(caffe_model_path,'/det3.prototxt');
model_dir = strcat(caffe_model_path,'/det3.caffemodel');
ONet=caffe.Net(prototxt_dir,model_dir,'test');
if use_new
prototxt_dir = strcat(caffe_model_path,'/det4.prototxt');
model_dir = strcat(caffe_model_path,'/det4.caffemodel');
LNet=caffe.Net(prototxt_dir,model_dir,'test');
end;
end;
source_img_path = sprintf('%s/%s', source_class_path, imgs(j).name);
% source_img_path = '/home/david/datasets/facescrub/facescrub//Billy_Zane/095f83fefdf1dc493c013edb1ef860001193e8d9.jpg'
try
img = imread(source_img_path);
catch exception
fprintf('Unexpected error (%s): %s\n', exception.identifier, exception.message);
continue;
end;
fprintf('%6d: %s\n', k, source_img_path);
if length(size(img))<3
img = repmat(img,[1,1,3]);
end;
img_size = size(img); % [height, width, channels]
img_size = fliplr(img_size(1:2)); % [x,y]
if use_new
[boundingboxes, points]=detect_face_v2(img,minsize,PNet,RNet,ONet,LNet,threshold,false,factor);
else
[boundingboxes, points]=detect_face_v1(img,minsize,PNet,RNet,ONet,threshold,false,factor);
end;
nrof_faces = size(boundingboxes,1);
det = boundingboxes;
if nrof_faces>0
if nrof_faces>1
% select the faces with the largest bounding box
% closest to the image center
bounding_box_size = (det(:,3)-det(:,1)).*(det(:,4)-det(:,2));
img_center = img_size / 2;
offsets = [ (det(:,1)+det(:,3))/2 (det(:,2)+det(:,4))/2 ] - ones(nrof_faces,1)*img_center;
offset_dist_squared = sum(offsets.^2,2);
[a, index] = max(bounding_box_size-offset_dist_squared*2.0); % some extra weight on the centering
det = det(index,:);
points = points(:,index);
end;
% if nrof_faces>0
% figure(1); clf;
% imshow(img);
% hold on;
% plot(points(1:5,1),points(6:10,1),'g.','MarkerSize',10);
% bb = round(det(1:4));
% rectangle('Position',[bb(1) bb(2) bb(3)-bb(1) bb(4)-bb(2)],'LineWidth',2,'LineStyle','-')
% xxx = 1;
% end;
det(1) = max(det(1)-margin/2, 1);
det(2) = max(det(2)-margin/2, 1);
det(3) = min(det(3)+margin/2, img_size(1));
det(4) = min(det(4)+margin/2, img_size(2));
det(1:4) = round(det(1:4));
img = img(det(2):det(4),det(1):det(3),:);
img = imresize(img, [image_size, image_size]);
imwrite(img, target_img_path);
k = k + 1;
else
fprintf('Detection failed: %s\n', source_img_path);
fid = fopen(failed_images_list,'at');
if fid>=0
fprintf(fid, '%s\n', source_img_path);
fclose(fid);
end;
end;
if mod(k,100)==0
xxx = 1;
end;
end;
end;
end;
end;
end;