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148 lines
7.5 KiB
148 lines
7.5 KiB
'''
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Created on May 8, 2014
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@author: eran
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'''
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from adiencealign.cascade_detection.cascade_face_finder import CascadeFaceFinder
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from adiencealign.affine_alignment.affine_aligner import AffineAligner
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import glob
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import os
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from adiencealign.landmarks_detection.landmarks_detector import detect_landmarks
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from adiencealign.common.landmarks import read_fidu, unwarp_fidu, draw_fidu
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import cv2
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class CascadeFaceAligner(object):
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'''
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classdocs
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'''
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def __init__(self, haar_file = '../resources/haarcascade_frontalface_default.xml',
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lbp_file = '../resources/lbpcascade_frontalface.xml',
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fidu_model_file = '../resources/model_ang_0.txt',
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fidu_exec_dir = '../resources/'):
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'''
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Constructor
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'''
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self.face_finder = CascadeFaceFinder(haar_file = haar_file,
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lbp_file = lbp_file)
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self.aligner = AffineAligner(fidu_model_file = fidu_model_file)
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self.fidu_exec_dir = fidu_exec_dir
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self.valid_angles = [-45,-30,-15,0,15,30,45]
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def detect_faces(self, input_folder, output_folder, mark_dones = True):
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'''
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mark_dones - if True, will create a hidden file, marking this file as done with a hidden file, starting with '.done.'
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'''
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input_files1 = glob.glob(os.path.join(input_folder, '*.jpg'))
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input_files2 = glob.glob(os.path.join(input_folder, '*.png'))
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input_files = input_files1 + input_files2
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N = len(input_files)
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for n_file, input_file in enumerate(input_files):
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a,b = os.path.split(input_file)
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done_file = os.path.join(a, '.done.' + b.rsplit('.',1)[0])
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if os.path.exists(done_file):
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continue
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print "... processing", input_file
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target_faces_file = os.path.join( output_folder, os.path.split(input_file)[1].rsplit('.',1)[0] + '.faces.txt')
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faces_file = self.face_finder.create_faces_file( input_file, is_overwrite = False, target_file = target_faces_file )
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sub_images_files = self.face_finder.create_sub_images_from_file( original_image_file = input_file,
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faces_file = faces_file,
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target_folder = output_folder,
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img_type = 'jpg')
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#touch
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open(done_file,'w').close()
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print "Detected on %d / %d files" %(n_file, N)
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def align_faces(self, input_images, output_path, fidu_max_size = None, fidu_min_size = None, is_align = True, is_draw_fidu = False, delete_no_fidu = False):
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'''
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input_images - can be either a folder (all *.jpgs in it) or a list of filenames
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, fidu_max_size = None, fidu_min_size = None):
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'''
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if type(input_images) == type(''):
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input_images = glob.glob(os.path.join(input_images, '*.jpg'))
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for input_image in input_images:
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detect_landmarks(fname = os.path.abspath(input_image),
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max_size = fidu_max_size,
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min_size = fidu_min_size,
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fidu_exec_dir = self.fidu_exec_dir)
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fidu_file = input_image.rsplit('.',1)[0] + '.cfidu'
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fidu_score, yaw_angle, fidu_points = read_fidu(fidu_file)
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if not (fidu_score is not None and yaw_angle in self.valid_angles):
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# skip face
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if delete_no_fidu:
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os.remove(fidu_file)
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os.remove(input_image)
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continue
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if is_align:
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# save the aligned image
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sub_img = cv2.imread(input_image)
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_, base_fname = os.path.split(input_image)
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aligned_img, R = self.aligner.align(sub_img, fidu_points)
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aligned_img_file = os.path.join(output_path, base_fname.rsplit('.',1)[0] + '.aligned.png')
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cv2.imwrite(aligned_img_file, aligned_img)
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# save a copy of the aligned image, with the landmarks drawn
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if is_draw_fidu:
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aligned_img_file = os.path.join(output_path, base_fname.rsplit('.',1)[0] + '.aligned.withpoints.png')
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fidu_points_in_aligned = unwarp_fidu(orig_fidu_points = fidu_points, unwarp_mat = R)
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draw_fidu(aligned_img, fidu_points_in_aligned, radius = 9, color = (255,0,0), thickness = 3)
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cv2.imwrite(aligned_img_file, aligned_img)
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#
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# def align_faces2(self, input_folder, output_folder, detect_landmarks = True, delete_no_fidu = True, is_align = True, is_draw_fidu = False, fidu_max_size = None, fidu_min_size = None):
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# '''
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# delete_no_fidu - deletes the .cfidu and sub_img if no fidu was found
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# is_draw_fidu - creates a copy of the aligned images with the original fiducial points on it
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# '''
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# input_files = glob.glob(os.path.join(input_folder, '*'))
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# for input_file in input_files:
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# print "... processing", input_file
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# target_faces_file = os.path.join( output_folder, os.path.split(input_file)[1].rsplit('.',1)[0] + '.faces.txt')
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#
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# faces_file = self.face_finder.create_faces_file( input_file, is_overwrite = False, target_file = target_faces_file )
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# sub_images_files = self.face_finder.create_sub_images_from_file( original_image_file = input_file,
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# faces_file = faces_file,
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# target_folder = output_folder,
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# img_type = 'jpg')
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#
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# for sub_image_file in sub_images_files:
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# detect_landmarks(fname = os.path.abspath(sub_image_file),
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# max_size = fidu_max_size,
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# min_size = fidu_min_size,
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# fidu_exec_dir = self.fidu_exec_dir)
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#
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# fidu_file = sub_image_file.rsplit('.',1)[0] + '.cfidu'
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# fidu_score, yaw_angle, fidu_points = read_fidu(fidu_file)
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#
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# if not (fidu_score is not None and yaw_angle in self.valid_angles):
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# # skip face
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# os.remove(fidu_file)
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# os.remove(sub_image_file)
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# continue
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#
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# if is_align:
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# # save the aligned image
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# sub_img = cv2.imread(sub_image_file)
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# aligned_img, R = self.aligner.align(sub_img, fidu_points)
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# aligned_img_file = sub_image_file.rsplit('.',1)[0] + '.aligned.png'
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# cv2.imwrite(aligned_img_file, aligned_img)
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#
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# # save a copy of the aligned image, with the landmarks drawn
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# if is_draw_fidu:
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# aligned_img_file = sub_image_file.rsplit('.',1)[0] + '.aligned.withpoints.png'
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# fidu_points_in_aligned = unwarp_fidu(orig_fidu_points = fidu_points, unwarp_mat = R)
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# draw_fidu(aligned_img, fidu_points_in_aligned, radius = 9, color = (255,0,0), thickness = 3)
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# cv2.imwrite(aligned_img_file, aligned_img)
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