def validate(n_img, o_img):
# Return value 1: No image found in given path
if not os.path.exists(n_img) or not os.path.exists(o_img):
log_error('No image found in given path')
return False, 1, None, None
# Return value 2: Image is unreadable (size: 0 bytes)
if not os.path.getsize(n_img) > 0 or not os.path.getsize(o_img) > 0:
log_error('Image is unreadable (size: 0 bytes)')
return False, 2, None, None
# Read input images
new_im = Image.open(new_img_path)
old_im = Image.open(old_img_path)
# Return value 3: Image is below minimum dimension (500x500)
new_file_width, new_file_height = new_im.size
old_file_width, old_file_height = old_im.size
if new_file_width + new_file_height < MIN_HEIGHT + MIN_WIDTH or \
old_file_width + old_file_height < MIN_HEIGHT + MIN_WIDTH:
log_error('Image is below minimum dimension')
return False, 3, new_im, old_im
# Return value 4: Face not detected
# Return value 5: Multiple face detected
new_im_cv2 = cv2.imread(n_img)
old_im_cv2 = cv2.imread(o_img)
new_img_points = face_points(new_im_cv2)
old_img_points = face_points(old_im_cv2)
if len(new_img_points) == 0:
log_error('Face not detected')
return False, 4, new_im, old_im
if len(old_img_points) == 0:
log_error('Face not detected')
return False, 4, new_im, old_im
# if len(new_img_points) > 1:
# log_error('Multiple face detected')
# return False, 5, new_im, old_im
# Return value 6: Face too small
face_detector = dlib.get_frontal_face_detector()
gray_image = cv2.cvtColor(new_im_cv2, cv2.COLOR_BGR2GRAY)
detected_faces = face_detector(gray_image, 0)
x = detected_faces[0]
x1, y1, x2, y2 = x.left(), x.top(), x.right(), x.bottom()
ratio_of_height = (x2 - x1) / OUTPUT_HEIGHT
ratio_of_weight = (y2 - y1) / OUTPUT_WIDTH
if (ratio_of_height + ratio_of_weight) / 2.0 < 0.30:
log_error('Face too small')
return False, 6, new_im, old_im
return True, 0, new_im, old_im
def load_image_points(path, size):
print 'in load image points'
img = scipy.ndimage.imread(path)[..., :3]
points = locator.face_points(path)
if len(points) == 0:
print 'No face in %s' % path
return None, None
else:
# print 'Face landmark points : ',points
# for i in range (0,71):
# cv2.line(img, (points[i][0],points[i][1]), (points[i][0],points[i][1]), (0,255,0),5)
# cv2.imshow('original points',img)
# cv2.waitKey(0)
cv2.line(img, (points[18][0],points[18][1]), (points[18][0],points[18][1]), (255,224,0),5)
cv2.line(img, (points[21][0],points[21][1]), (points[21][0],points[21][1]), (255,224,0),5)
cv2.line(img, (points[22][0],points[22][1]), (points[22][0],points[22][1]), (255,224,0),5)
cv2.line(img, (points[25][0],points[25][1]), (points[25][0],points[25][1]), (255,224,0),5)
cv2.line(img, (points[30][0],points[30][1]), (points[30][0],points[30][1]), (255,0,0),5)
cv2.line(img, (points[40][0],points[40][1]), (points[40][0],points[40][1]), (255,0,0),5)
cv2.line(img, (points[54][0],points[54][1]), (points[54][0],points[54][1]), (0,255,0),5)
cv2.line(img, (points[56][0],points[56][1]), (points[56][0],points[56][1]), (0,255,0),5)
cv2.line(img, (points[58][0],points[58][1]), (points[58][0],points[58][1]), (0,255,0),5)
cv2.line(img, (points[59][0],points[59][1]), (points[59][0],points[59][1]), (0,0,255),5)
cv2.line(img, (points[65][0],points[65][1]), (points[65][0],points[65][1]), (0,0,255),5)
cv2.imshow("img",img)
cv2.waitKey(0)
return aligner.resize_align(img, points, size)
def load_image_points(path, size):
# print 'in load image points'
# img = scipy.ndimage.imread(path)[..., :3]
img = cv2.imread(path)[..., :3]
# print 'in load image points'
# img = scipy.ndimage.imread(path)[..., :3]
points = locator.face_points(path)
if len(points) == 0:
print 'No face in %s' % path
return None, None
else:
# print 'Face landmark points : ',points
# for i in range (0,71):
# cv2.line(img, (points[i][0],points[i][1]), (points[i][0],points[i][1]), (0,255,0),5)
# cv2.imshow('original points',img)
# cv2.waitKey(0)
# cv2.line(img, (points[18][0],points[18][1]), (points[18][0],points[18][1]), (255,224,0),5)
# cv2.line(img, (points[21][0],points[21][1]), (points[21][0],points[21][1]), (255,224,0),5)
# cv2.line(img, (points[22][0],points[22][1]), (points[22][0],points[22][1]), (255,224,0),5)
# cv2.line(img, (points[25][0],points[25][1]), (points[25][0],points[25][1]), (255,224,0),5)
#
# cv2.line(img, (points[30][0],points[30][1]), (points[30][0],points[30][1]), (255,0,0),5)
# cv2.line(img, (points[40][0],points[40][1]), (points[40][0],points[40][1]), (255,0,0),5)
#
# cv2.line(img, (points[54][0],points[54][1]), (points[54][0],points[54][1]), (0,255,0),5)
# cv2.line(img, (points[56][0],points[56][1]), (points[56][0],points[56][1]), (0,255,0),5)
# cv2.line(img, (points[58][0],points[58][1]), (points[58][0],points[58][1]), (0,255,0),5)
#
# cv2.line(img, (points[59][0],points[59][1]), (points[59][0],points[59][1]), (0,0,255),5)
# cv2.line(img, (points[65][0],points[65][1]), (points[65][0],points[65][1]), (0,0,255),5)
# cv2.imshow("img",img)
# cv2.waitKey(0)
# return aligner.resize_align(img, points, size)
return aligner.resize_align(img, points, size)
def load_image_points(path, size):
img = scipy.ndimage.imread(path)[..., :3]
points = locator.face_points(path)
if len(points) == 0:
return None, None
else:
return aligner.resize_align(img, points, size)
def load_image_points(path, size):
img = scipy.ndimage.imread(path)[..., :3]
points = locator.face_points(path)
if len(points) == 0:
return None, None
else:
return aligner.resize_align(img, points, size)
def load_image_points(img):
# img = cv2.imread(path)
points = locator.face_points(img)
if len(points) == 0:
# print('No face in the image')
return (None, None)
else:
return (img, points)
def load_image_points(path, size):
img = cv2.imread(path)
points = locator.face_points(img)
if len(points) == 0:
print('No face in %s' % path)
return None, None
else:
return aligner.resize_align(img, points, size)
def load_image_points(path):
img = cv2.imread(path)
points = locator.face_points(path)
if len(points) == 0:
print('No face in %s' % path)
return (None, None)
else:
return (img, points)
def load_image_points(path, size):
img = scipy.ndimage.imread(path)[..., :3]
points = locator.face_points(path)
## Add image boundary points
#x,y = np.meshgrid([0,size[0]/2,size[0]],[0,size[1]/2,size[1]])
#im_edge_points = np.vstack((y.flatten(),x.flatten())).T
#points = np.vstack((points,im_edge_points))
if len(points) == 0:
print('No face in %s' % path)
return None, None
else:
return aligner.resize_align(img, points, size)
def load_image_points(path, size, fromDb=False):
img = scipy.ndimage.imread(path)[..., :3]
if fromDb:
with con:
cur = con.cursor()
data = cur.execute("SELECT points FROM entries WHERE name=?", ([os.path.basename(path)]))
points = convert_array(cur.fetchone()[0])
else:
points = locator.face_points(path)
if len(points) == 0:
return None, None
else:
return aligner.resize_align(img, points, size)