b591a7aecce5b8de42a0dd7bba62780675d34fce,utils/datasets.py,ListDataset,collate_fn,#,141

Before Change

        paths, imgs, labels = list(zip(*batch))
        for i, boxes in enumerate(labels):
            boxes[:, 0] = i
        imgs = torch.stack(imgs, 0)
        labels = torch.cat(labels, 0)
        return paths, imgs, labels

    def __len__(self):

After Change

        if self.multiscale:
            img_size = random.sample(list(range(self.min_size, self.max_size + 1, 32)), 1)[0]
        else:
            img_size = self.img_size
        imgs = torch.stack([resize(img, img_size) for img in imgs])
        return paths, imgs, labels

    def __len__(self):
        return len(self.img_files)

Instances