def test_face_cropped_ok(self):
"""Detect faces from a folder of Kinect images.
If this test fails it means that:
- our face detection algorithm has improved and we detect faces in
much more images than the beginning.
Uncomment line 119, run test again and check output images!
Update face_images array! :)
or
- our face detection algorithm is buggy and it does not recognize
the same images as the beginning.
"""
from lib.opencv import crop_face_from_image
from os import listdir
image_folder = "%s/headcrop_dataset/" % PROJECT_PATH
images = [image for image in listdir(image_folder)
if not image.endswith('_result.jpg')]
face_images = ['2.jpg', '3.jpg', '11.jpg', '12.jpg', '14.jpg',
'18.jpg', '20.jpg', '21.jpg']
for image_file in images:
image = Image.open("%s/%s" % (image_folder, image_file))
cropped_head = crop_face_from_image(image)
if cropped_head is not None:
#cropped_head.save("%s/%s_result.jpg" % (image_folder, image_file))
self.assertIn(image_file, face_images)
else:
self.assertNotIn(image_file, face_images)
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 test_face_cropped_ok(self):
from lib.opencv import crop_face_from_image
from os import listdir
image_folder = "/home/ami/AmI-Platform/headcrop_dataset"
images = [ image for image in listdir(image_folder) if not image.endswith('_result.jpg')]
for image_file in images:
image = Image.open("%s/%s" % (image_folder,image_file))
logging.debug("processing image %s" % image_file)
cropped_head = crop_face_from_image(image)
if cropped_head is not None:
cropped_head.save("%s/%s_result.jpg" % (image_folder, image_file))
print '.'
