config = {
'superpoint': {
'nms_radius': opt.nms_radius,
'keypoint_threshold': opt.keypoint_threshold,
'max_keypoints': opt.max_keypoints
},
'superglue': {
'weights': opt.superglue,
'sinkhorn_iterations': opt.sinkhorn_iterations,
'match_threshold': opt.match_threshold,
}
}
matching = Matching(config).eval().to(device)
keys = ['keypoints', 'scores', 'descriptors']
vs = VideoStreamer(opt.input, opt.resize, opt.skip, opt.image_glob,
opt.max_length)
frame, ret = vs.next_frame()
assert ret, 'Error when reading the first frame (try different --input?)'
frame_tensor = frame2tensor(frame, device)
last_data = matching.superpoint({'image': frame_tensor})
last_data = {k + '0': last_data[k] for k in keys}
last_data['image0'] = frame_tensor
last_frame = frame
last_image_id = 0
if opt.output_dir is not None:
print('==> Will write outputs to {}'.format(opt.output_dir))
Path(opt.output_dir).mkdir(exist_ok=True)
# Create a window to display the demo.
config = {
'superpoint': {
'nms_radius': opt.nms_radius,
'detection_threshold': opt.keypoint_thresh,
'max_keypoints': opt.max_keypoints
},
'superglue': {
'weights': opt.superglue,
'num_sinkhorn_iterations': opt.sinkhorn_iterations,
'filter_threshold': opt.match_thresh,
}
}
matching = Matching(config).eval().to(device)
keys = ['keypoints', 'scores', 'descriptors']
vs = VideoStreamer(opt.input, opt.resize, opt.skip, opt.img_glob,
opt.maxlen)
frame, ret = vs.next_frame()
assert ret, 'Error when reading the first frame (try different --input?)'
frame_tensor = frame2tensor(frame, device)
last_data = matching.superpoint({'image': frame_tensor})
last_data = {k + '0': last_data[k] for k in keys}
last_data['image0'] = frame_tensor
last_frame = frame
last_image_id = 0
if opt.write:
print('==> Will write outputs to {}'.format(opt.write_dir))
Path(opt.write_dir).mkdir(exist_ok=True)
# Create a window to display the demo.