class MRFaceTaskSimulation(object):
def __init__(self, file_list, **kwargs):
self.file_list = file_list
gpu_or_cpu = kwargs['hardware_type']
resources_dir = kwargs['resources_dir']
colorferet_tar = os.path.join(resources_dir, kwargs['colorferet'])
cascade_cpu = os.path.join(resources_dir, kwargs['cascade_cpu'])
cascade_gpu = os.path.join(resources_dir, kwargs['cascade_gpu'])
tar_stem = kwargs['colorferet'].split('.')[0]
colorferet_dir = os.path.join(resources_dir, tar_stem)
with tarfile.open(colorferet_tar) as tar:
tar.extractall(path=colorferet_dir)
self.detector = create_detector(gpu_or_cpu, cascade_cpu, cascade_gpu)
self.recognizer = create_recognizer(colorferet_dir)
shutil.rmtree(colorferet_dir, ignore_errors=True)
self.timer = Timer()
def run(self):
race_count = {
'Black-or-African-American': 0,
'Asian': 0,
'Asian-Middle-Eastern': 0,
'Hispanic': 0,
'Native-American': 0,
'Other': 0,
'Pacific-Islander': 0,
'White': 0
}
for file_path in self.file_list:
frame = cv2.imread(file_path)
frame_bgr = None
print file_path
if len(frame.shape) == 3:
if frame.shape[2] > 1:
frame_bgr = frame
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
for (x, y, w, h) in self.detector.detect(file_path):
cutout = cv2.resize(frame[y:y+h, x:x+w], (256, 256))
race_predicted_num, conf = self.recognizer.predict(cutout)
race_predicted_str = labels_int[int(race_predicted_num)]
race_count[race_predicted_str] += 1
results = []
for race in race_count:
count = race_count[race]
results.append((race, count))
self.timer.end()
return results
def __init__(self, file_list, **kwargs):
self.file_list = file_list
gpu_or_cpu = kwargs['hardware_type']
resources_dir = kwargs['resources_dir']
colorferet_tar = os.path.join(resources_dir, kwargs['colorferet'])
cascade_cpu = os.path.join(resources_dir, kwargs['cascade_cpu'])
cascade_gpu = os.path.join(resources_dir, kwargs['cascade_gpu'])
tar_stem = kwargs['colorferet'].split('.')[0]
colorferet_dir = os.path.join(resources_dir, tar_stem)
with tarfile.open(colorferet_tar) as tar:
tar.extractall(path=colorferet_dir)
self.detector = create_detector(gpu_or_cpu, cascade_cpu, cascade_gpu)
self.recognizer = create_recognizer(colorferet_dir)
shutil.rmtree(colorferet_dir, ignore_errors=True)
self.timer = Timer()
