Function _make_transform_sample

test/test_transforms_v2.py:286–351

(transform, *, image_or_video, adapter)

def _make_transform_sample(transform, *, image_or_video, adapter):
    device = image_or_video.device if isinstance(image_or_video, torch.Tensor) else "cpu"
    size = F.get_size(image_or_video)
    input = dict(
        image_or_video=image_or_video,
        image_tv_tensor=make_image(size, device=device),
        video_tv_tensor=make_video(size, device=device),
        image_pil=make_image_pil(size),
        bounding_boxes_xyxy=make_bounding_boxes(size, format=tv_tensors.BoundingBoxFormat.XYXY, device=device),
        bounding_boxes_xywh=make_bounding_boxes(size, format=tv_tensors.BoundingBoxFormat.XYWH, device=device),
        bounding_boxes_cxcywh=make_bounding_boxes(size, format=tv_tensors.BoundingBoxFormat.CXCYWH, device=device),
        bounding_boxes_degenerate_xyxy=tv_tensors.BoundingBoxes(
            [
                [0, 0, 0, 0],  # no height or width
                [0, 0, 0, 1],  # no height
                [0, 0, 1, 0],  # no width
                [2, 0, 1, 1],  # x1 > x2, y1 < y2
                [0, 2, 1, 1],  # x1 < x2, y1 > y2
                [2, 2, 1, 1],  # x1 > x2, y1 > y2
            ],
            format=tv_tensors.BoundingBoxFormat.XYXY,
            canvas_size=size,
            device=device,
        ),
        bounding_boxes_degenerate_xywh=tv_tensors.BoundingBoxes(
            [
                [0, 0, 0, 0],  # no height or width
                [0, 0, 0, 1],  # no height
                [0, 0, 1, 0],  # no width
                [0, 0, 1, -1],  # negative height
                [0, 0, -1, 1],  # negative width
                [0, 0, -1, -1],  # negative height and width
            ],
            format=tv_tensors.BoundingBoxFormat.XYWH,
            canvas_size=size,
            device=device,
        ),
        bounding_boxes_degenerate_cxcywh=tv_tensors.BoundingBoxes(
            [
                [0, 0, 0, 0],  # no height or width
                [0, 0, 0, 1],  # no height
                [0, 0, 1, 0],  # no width
                [0, 0, 1, -1],  # negative height
                [0, 0, -1, 1],  # negative width
                [0, 0, -1, -1],  # negative height and width
            ],
            format=tv_tensors.BoundingBoxFormat.CXCYWH,
            canvas_size=size,
            device=device,
        ),
        keypoints=make_keypoints(canvas_size=size),
        detection_mask=make_detection_masks(size, device=device),
        segmentation_mask=make_segmentation_mask(size, device=device),
        int=0,
        float=0.0,
        bool=True,
        none=None,
        str="str",