def betaface_recognition(image_dict):
""" Given a message contained a cropped head, send it to BetaFace
API for face recognition. This can take anywhere from 1 to 10 seconds.
"""
try:
api = BetaFaceAPI()
# Get image from message, save it to disk and
# pass it on to BetaFace API
image = base64_to_image(image_dict['head_image']['image'],
int(image_dict['head_image']['width']),
int(image_dict['head_image']['height']))
temp_path = random_file_name('jpg', "FR_")
logger.info("Generated random path to save image: %s" % temp_path)
image = image.rotate(180)
image.save(temp_path)
logger.info("Saved image to disk at path %s" % temp_path)
matches = api.recognize_faces(temp_path, 'amilab.ro')
logger.info("Received recognized faces from BetaFace API %r" % matches)
#os.remove(str(temp_path))
#logger.info("Removed image from disk (%s)" % str(temp_path))
return matches
except:
logger.exception("Failed to recognize faces via BetaFace API")
return {}
def _crop_head_using_face_detection(last_image):
""" Given the last image, try to detect any faces in it
and crop the first one of them, if any. """
image = base64_to_image(last_image['image'],
int(last_image['width']),
int(last_image['height']),
last_image['encoder_name'])
return crop_face_from_image(image)
def _crop_head_using_skeleton(last_image, last_skeleton):
""" Given the last image and last skeleton which are
'close enough' apart, crop off an image of the head. """
image = base64_to_image(last_image['image'],
int(last_image['width']),
int(last_image['height']),
last_image['encoder_name'])
skeleton = last_skeleton
return crop_head_using_skeleton(image, skeleton)