File size: 1,528 Bytes
cca075c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 |
import cv2 as cv
import argparse
# Check OpenCV version
opencv_python_version = lambda str_version: tuple(map(int, [p.split('-')[0] for p in str_version.split('.')]))
assert opencv_python_version(cv.__version__) >= opencv_python_version("5.0.0"), \
"Please install latest opencv-python for benchmark: python3 -m pip install --upgrade opencv-python"
from nafnet import Nafnet
def get_args_parser(func_args):
parser = argparse.ArgumentParser(add_help=False)
parser.add_argument('--input', help='Path to input image.', default='example_outputs/licenseplate_motion.jpg', required=False)
parser.add_argument('--model', help='Path to nafnet deblurring onnx model', default='deblurring_nafnet_2025may.onnx', required=False)
args, _ = parser.parse_known_args()
parser = argparse.ArgumentParser(parents=[parser],
description='', formatter_class=argparse.RawTextHelpFormatter)
return parser.parse_args(func_args)
def main(func_args=None):
args = get_args_parser(func_args)
nafnet = Nafnet(modelPath=args.model)
input_image = cv.imread(args.input)
tm = cv.TickMeter()
tm.start()
result = nafnet.infer(input_image)
tm.stop()
label = 'Inference time: {:.2f} ms'.format(tm.getTimeMilli())
cv.putText(result, label, (0, 15), cv.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 0))
cv.imshow("Input image", input_image)
cv.imshow("Output image", result)
cv.waitKey(0)
cv.destroyAllWindows()
if __name__ == '__main__':
main()
|