vis4d.vis.functional.image

Function interface for image visualization functions.

Functions

draw_bbox3d(image, boxes3d, intrinsics[, ...])

Draw 3D box onto image.

draw_bboxes(image, boxes[, scores, ...])

Draws the predicted bounding boxes into the given image.

draw_masks(image, masks, class_ids[, ...])

Draws semantic masks into the given image.

imsave(image, file_path[, image_mode, ...])

Shows a single image.

imshow(image[, image_mode, image_viewer])

Shows a single image.

imshow_bboxes(image, boxes[, scores, ...])

Shows the bounding boxes overlayed on the given image.

imshow_bboxes3d(image, boxes3d, intrinsics)

Show image with bounding boxes.

imshow_masks(image, masks, class_ids[, ...])

Shows semantic masks overlayed over the given image.

imshow_topk_bboxes(image, boxes, scores[, ...])

Visualize the 'topk' bounding boxes with highest score.

imshow_track_matches(key_imgs, ref_imgs, ...)

Visualize paired bounding boxes successively for batched frame pairs.
draw_bbox3d(image, boxes3d, intrinsics, extrinsics=None, scores=None, class_ids=None, track_ids=None, class_id_mapping=None, n_colors=50, image_mode='RGB', canvas=<vis4d.vis.image.canvas.pillow_backend.PillowCanvasBackend object>, width=4, camera_near_clip=0.15)[source]

Draw 3D box onto image.

Return type:

NDArrayUI8

draw_bboxes(image, boxes, scores=None, class_ids=None, track_ids=None, class_id_mapping=None, n_colors=50, image_mode='RGB', box_width=1, canvas=<vis4d.vis.image.canvas.pillow_backend.PillowCanvasBackend object>)[source]

Draws the predicted bounding boxes into the given image.

Parameters:

  • image (ArrayLike) – The image to draw the bboxes into.

  • boxes (ArrayLikeFloat) – Predicted bounding boxes.

  • scores (None | ArrayLikeFloat, optional) – Predicted scores. Defaults to None.

  • class_ids (ArrayLikeInt, optional) – Predicted class ids. Defaults to None.

  • track_ids (ArrayLikeInt, optional) – Predicted track ids. Defaults to None.

  • class_id_mapping (dict[int, str], optional) – Mapping from class id to name. Defaults to None.

  • n_colors (int, optional) – Number of colors to use for color palette. Defaults to 50.

  • image_mode (str, optional) – Image Mode. Defaults to “RGB”.

  • box_width (int, optional) – Width of the box border. Defaults to 1.

  • canvas (CanvasBackend, optional) – Canvas backend to use. Defaults to PillowCanvasBackend().

Returns:

The image with boxes drawn into it,

Return type:

NDArrayUI8

draw_masks(image, masks, class_ids, n_colors=50, image_mode='RGB', canvas=<vis4d.vis.image.canvas.pillow_backend.PillowCanvasBackend object>)[source]

Draws semantic masks into the given image.

Parameters:

  • image (ArrayLike) – The image to draw the bboxes into.

  • masks (ArrayLikeBool) – The semantic masks with the same shape as the image.

  • class_ids (ArrayLikeInt, optional) – Predicted class ids. Defaults to None.

  • n_colors (int, optional) – Number of colors to use for color palette. Defaults to 50.

  • image_mode (str, optional) – Image Mode. Defaults to “RGB”.

  • canvas (CanvasBackend, optional) – Canvas backend to use. Defaults to PillowCanvasBackend().

Returns:

The image with semantic masks drawn into it,

Return type:

NDArrayUI8

imsave(image, file_path, image_mode='RGB', image_viewer=<vis4d.vis.image.viewer.matplotlib_viewer.MatplotlibImageViewer object>)[source]

Shows a single image.

Parameters:

  • image (NDArrayNumber) – The image to show.

  • file_path (str) – The path to save the image to.

  • image_mode (str, optional) – Image Mode. Defaults to “RGB”.

  • image_viewer (ImageViewerBackend, optional) – The Image viewer backend to use. Defaults to MatplotlibImageViewer().

Return type:

None

imshow(image, image_mode='RGB', image_viewer=<vis4d.vis.image.viewer.matplotlib_viewer.MatplotlibImageViewer object>)[source]

Shows a single image.

Parameters:

  • image (NDArrayNumber) – The image to show.

  • image_mode (str, optional) – Image Mode. Defaults to “RGB”.

  • image_viewer (ImageViewerBackend, optional) – The Image viewer backend to use. Defaults to MatplotlibImageViewer().

Return type:

None

imshow_bboxes(image, boxes, scores=None, class_ids=None, track_ids=None, class_id_mapping=None, n_colors=50, image_mode='RGB', box_width=1, image_viewer=<vis4d.vis.image.viewer.matplotlib_viewer.MatplotlibImageViewer object>)[source]

Shows the bounding boxes overlayed on the given image.

Parameters:

  • image (ArrayLike) – Background Image

  • boxes (ArrayLikeFloat) – Boxes to show. Shape [N, 4] with (x1,y1,x2,y2) as corner convention

  • scores (ArrayLikeFloat, optional) – Score for each box shape [N]

  • class_ids (ArrayLikeInt, optional) – Class id for each box shape [N]

  • track_ids (ArrayLikeInt, optional) – Track id for each box shape [N]

  • class_id_mapping (dict[int, str], optional) – Mapping to convert class id to class name

  • n_colors (int, optional) – Number of distinct colors used to color the boxes. Defaults to 50.

  • image_mode (str, optional) – Image channel mode (RGB or BGR).

  • box_width (int, optional) – Width of the box border. Defaults to 1.

  • image_viewer (ImageViewerBackend, optional) – The Image viewer backend to use. Defaults to MatplotlibImageViewer().

Return type:

None

imshow_bboxes3d(image, boxes3d, intrinsics, extrinsics=None, scores=None, class_ids=None, track_ids=None, class_id_mapping=None, n_colors=50, image_mode='RGB', image_viewer=<vis4d.vis.image.viewer.matplotlib_viewer.MatplotlibImageViewer object>)[source]

Show image with bounding boxes.

Return type:

None

imshow_masks(image, masks, class_ids, n_colors=50, image_mode='RGB', canvas=<vis4d.vis.image.canvas.pillow_backend.PillowCanvasBackend object>, image_viewer=<vis4d.vis.image.viewer.matplotlib_viewer.MatplotlibImageViewer object>)[source]

Shows semantic masks overlayed over the given image.

Parameters:

  • image (ArrayLike) – The image to draw the bboxes into.

  • masks (ArrayLikeBool) – The semantic masks with the same shape as the image.

  • class_ids (ArrayLikeInt, optional) – Predicted class ids. Defaults to None.

  • n_colors (int, optional) – Number of colors to use for color palette. Defaults to 50.

  • image_mode (str, optional) – Image Mode.. Defaults to “RGB”.

  • canvas (CanvasBackend, optional) – Canvas backend to use. Defaults to PillowCanvasBackend().

  • image_viewer (ImageViewerBackend, optional) – The Image viewer backend to use. Defaults to MatplotlibImageViewer().

Return type:

None

imshow_topk_bboxes(image, boxes, scores, topk=100, class_ids=None, track_ids=None, class_id_mapping=None, n_colors=50, image_mode='RGB', box_width=1, image_viewer=<vis4d.vis.image.viewer.matplotlib_viewer.MatplotlibImageViewer object>)[source]

Visualize the ‘topk’ bounding boxes with highest score.

Parameters:

  • image (ArrayLike) – Background Image

  • boxes (ArrayLikeFloat) – Boxes to show. Shape [N, 4] with (x1,y1,x2,y2) as corner convention

  • scores (ArrayLikeFloat) – Score for each box shape [N]

  • topk (int) – Number of boxes to visualize

  • class_ids (ArrayLikeInt, optional) – Class id for each box shape [N]

  • track_ids (ArrayLikeInt, optional) – Track id for each box shape [N]

  • class_id_mapping (dict[int, str], optional) – Mapping to convert class id to class name

  • n_colors (int, optional) – Number of distinct colors used to color the boxes. Defaults to 50.

  • image_mode (str, optional) – Image channel mode (RGB or BGR).

  • box_width (int, optional) – Width of the box border. Defaults to 1.

  • image_viewer (ImageViewerBackend, optional) – The Image viewer backend to use. Defaults to MatplotlibImageViewer().

Return type:

None

imshow_track_matches(key_imgs, ref_imgs, key_boxes, ref_boxes, key_track_ids, ref_track_ids, image_mode='RGB', image_viewer=<vis4d.vis.image.viewer.matplotlib_viewer.MatplotlibImageViewer object>)[source]

Visualize paired bounding boxes successively for batched frame pairs.

Parameters:

  • key_imgs (list[ArrayLike]) – Key Images.

  • ref_imgs (list[ArrayLike]) – Reference Images.

  • key_boxes (list[ArrayLikeFloat]) – Predicted Boxes for the key image. Shape [N, 4]

  • ref_boxes (list[ArrayLikeFloat]) – Predicted Boxes for the key image. Shape [N, 4]

  • key_track_ids (list[ArrayLikeInt]) – Predicted ids for the key images.

  • ref_track_ids (list[ArrayLikeInt]) – Predicted ids for the reference images.

  • image_mode (str, optional) – Color mode if the image. Defaults to “RGB”.

  • image_viewer (ImageViewerBackend, optional) – The Image viewer backend to use. Defaults to MatplotlibImageViewer().

Return type:

None