def __getitem__()

in maskrcnn_benchmark/data/datasets/coco.py [0:0]

• 22 lines of code
• 13 McCabe index (conditional complexity)

    def __getitem__(self, idx):
        img, anno = super(COCODataset, self).__getitem__(idx)

        # filter crowd annotations
        # TODO might be better to add an extra field
        anno = [obj for obj in anno if obj["iscrowd"] == 0]

        boxes = [obj["bbox"] for obj in anno]
        boxes = torch.as_tensor(boxes).reshape(-1, 4)  # guard against no boxes
        target = BoxList(boxes, img.size, mode="xywh").convert("xyxy")

        classes = [obj["category_id"] for obj in anno]
        classes = [self.json_category_id_to_contiguous_id[c] for c in classes]
        classes = torch.tensor(classes)
        target.add_field("labels", classes)

        if anno and "segmentation" in anno[0]:
            masks = [obj["segmentation"] for obj in anno]
            masks = SegmentationMask(masks, img.size, mode='poly')
            target.add_field("masks", masks)

        if anno and "keypoints" in anno[0]:
            keypoints = [obj["keypoints"] for obj in anno]
            keypoints = PersonKeypoints(keypoints, img.size)
            target.add_field("keypoints", keypoints)

        target = target.clip_to_image(remove_empty=True)

        if self._transforms is not None:
            img, target = self._transforms(img, target)

        return img, target, idx