def crop_face_from_image(image):
""" Return a cropped face from a given image. """
# Try to detect faces in the image - if there is None,
# there is nothing to do. Otherwise, keep only the first
# face regardless of how many were detected.
faces = voting_face_detect(image)
if len(faces) == 0:
return None
(x, y, w, h) = faces[0][0]
logger.info("Found face with size %d x %d" % (w, h))
# Take the first detected face and scale the rectangle
# 2 times around its center.
face_rect = (x, y, x + w, y + h)
face_rect = rectangle_scale(*face_rect, factor = 2)
logger.info("Doubling both dimensions to %d x %d" % (face_rect[2] - face_rect[0],
face_rect[3] - face_rect[1]))
# Intersect this with the image rectangle
image_rect = (0, 0, image.size[0], image.size[1])
cropping_rect = rectangle_intersection(face_rect, image_rect)
logger.info("Final cropping rect has dimensions %d x %d" % (cropping_rect[2] - cropping_rect[0],
cropping_rect[3] - cropping_rect[1]))
logger.info("Cropping rect: %.2f %.2f %.2f %.2f" % (cropping_rect[0],
cropping_rect[1],
cropping_rect[2],
cropping_rect[3]))
cropping_rect = (int(cropping_rect[0]), int(cropping_rect[1]),
int(cropping_rect[2]), int(cropping_rect[3]))
cropped_image = image.crop(cropping_rect)
# Save both images and log this so we can debug more easily
temp_path_full_image = random_file_name('jpg')
temp_path_face_image = random_file_name('jpg')
image.save(temp_path_full_image)
cropped_image.save(temp_path_face_image)
logger.info("Saved full image at %s" % temp_path_full_image)
logger.info("Saved full image at %s" % temp_path_face_image)
return cropped_image
def crop_head_using_skeleton(image, skeleton):
""" Given an image taken from the kinect RGB in PIL format, and a set
of skeleton coordinates, crop the head and return the cropped image.
"""
# We will cut off a rectangle with the center in the head
# and the dimension 2 * head-neck distance.
neck_length = dist(skeleton['head']['X'], skeleton['head']['Y'],
skeleton['neck']['X'], skeleton['neck']['Y'])
head_rect = (skeleton['head']['X'] - neck_length,
skeleton['head']['Y'] - neck_length,
skeleton['head']['X'] + neck_length,
skeleton['head']['Y'] + neck_length)
# Intersect our rectangle with the actual image, and crop it
image_rect = (0, 0, image.size[0], image.size[1])
cropping_rect = rectangle_intersection(head_rect, image_rect)
cropping_rect = (int(cropping_rect[0]), int(cropping_rect[1]),
int(cropping_rect[2]), int(cropping_rect[3]))
return image.crop(cropping_rect)
