def process_video():
# net initialize
net = ailia.Net(MODEL_PATH, WEIGHT_PATH, env_id=args.env_id)
if args.face_recognition:
locator = FaceLocator()
else:
locator = None
capture = webcamera_utils.get_capture(args.video)
if args.savepath != SAVE_IMAGE_PATH:
writer = webcamera_utils.get_writer(args.savepath, args.resolution,
args.resolution)
else:
writer = None
while (True):
ret, frame = capture.read()
if (cv2.waitKey(1) & 0xFF == ord('q')) or not ret:
break
img = process_frame(net, locator, frame)
img = img[..., ::-1]
cv2.imshow('frame', img)
# save results
if writer is not None:
writer.write(img)
capture.release()
cv2.destroyAllWindows()
if writer is not None:
writer.release()
logger.info('Script finished successfully.')
def process_video():
# net initialize
env_id = ailia.get_gpu_environment_id()
print(f'env_id: {env_id}')
net = ailia.Net(MODEL_PATH, WEIGHT_PATH, env_id=env_id)
if args.face_recognition:
locator = FaceLocator()
else:
locator = None
if args.video == '0':
print('[INFO] Webcam mode is activated')
capture = cv2.VideoCapture(0)
if not capture.isOpened():
print("[ERROR] webcamera not found")
sys.exit(1)
else:
if check_file_existance(args.video):
capture = cv2.VideoCapture(args.video)
while (True):
ret, frame = capture.read()
if cv2.waitKey(1) & 0xFF == ord('q'):
break
if not ret:
continue
img = process_frame(net, locator, frame)
cv2.imshow('frame', img[..., ::-1])
capture.release()
cv2.destroyAllWindows()
print('Script finished successfully.')
def transform_image():
"""Full transormation on a single image loaded from filepath in arguments.
"""
net = ailia.Net(MODEL_PATH, WEIGHT_PATH, env_id=args.env_id)
# input image loop
for image_path in args.input:
# prepare input data
logger.info(image_path)
image = cv2.imread(image_path)
if args.face_recognition:
locator = FaceLocator()
else:
locator = None
logger.info('Start inference...')
if args.benchmark:
logger.info('BENCHMARK mode')
for i in range(5):
start = int(round(time.time() * 1000))
out_image = process_frame(net, locator, image)
end = int(round(time.time() * 1000))
logger.info(f'\tailia processing time {end - start} ms')
else:
out_image = process_frame(net, locator, image)
savepath = get_savepath(args.savepath, image_path)
logger.info(f'saved at : {savepath}')
cv2.imwrite(savepath, out_image[..., ::-1])
return True
def transform_image():
"""Full transormation on a single image loaded from filepath in arguments."""
image = cv2.imread(args.input)
env_id = ailia.get_gpu_environment_id()
print(f'env_id: {env_id}')
net = ailia.Net(MODEL_PATH, WEIGHT_PATH, env_id=env_id)
if args.face_recognition:
locator = FaceLocator()
else:
locator = None
if args.benchmark:
print('BENCHMARK mode')
for i in range(5):
start = int(round(time.time() * 1000))
out_image = process_frame(net, locator, image)
end = int(round(time.time() * 1000))
print(f'\tailia processing time {end - start} ms')
else:
out_image = process_frame(net, locator, image)
cv2.imwrite(args.savepath, out_image[..., ::-1])
return True