train => disk +lg

[vampire1204]

Thanks for your impressive work!
I find something maybe wrong while I train mine custom datasets

in disk_kornia.py -> _forward -> for .... ->
image[: min(image.shape[0], i + chunk)] (here)

'''
for i in range(0, image.shape[0], chunk):
if self.conf.dense_outputs:
features, d_descriptors = self._get_dense_outputs(
image[: min(image.shape[0], i + chunk)]
)
dense_descriptors.append(d_descriptors)
else:
features = self.model(
image[: min(image.shape[0], i + chunk)],
n=self.conf.max_num_keypoints,
window_size=self.conf.nms_window_size,
score_threshold=self.conf.detection_threshold,
pad_if_not_divisible=self.conf.pad_if_not_divisible,
)
keypoints += [f.keypoints for f in features]
scores += [f.detection_scores for f in features]
descriptors += [f.descriptors for f in features]
del features
'''

I think it's range maybe wrong. I don't know if you agree? Thanks again

[vampire1204]

I used image[i: min(image.shape[0], i + chunk)]