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)]