def draw_pix3d_dict()

in meshrcnn/utils/vis.py [0:0]

• 38 lines of code
• 11 McCabe index (conditional complexity)

def draw_pix3d_dict(dataset_dict, class_names=None):
    """
    Draw the instance annotations for an image.

    Args:
        dataset_dict (dict): a dict in Detectron2 Dataset format. See DATASETS.md
        class_names (list[str] or None): `class_names[cateogory_id]` is the
            name for this category. If not provided, the visualization will
            not contain class names.
    """
    img = dataset_dict.get("image", None)
    if img is None:
        img = cv2.imread(dataset_dict["file_name"])
    annos = dataset_dict["annotations"]
    if not len(annos):
        return img
    boxes = np.asarray(
        [BoxMode.convert(k["bbox"], k["bbox_mode"], BoxMode.XYXY_ABS) for k in annos]
    )

    # Display in largest to smallest order to reduce occlusion
    areas = (boxes[:, 2] - boxes[:, 0]) * (boxes[:, 3] - boxes[:, 1])
    sorted_inds = np.argsort(-areas)
    sorted_boxes = copy.deepcopy(boxes[sorted_inds])

    img = draw_boxes(img, sorted_boxes)

    cmap = colormap()

    for num, i in enumerate(sorted_inds):
        anno = annos[i]
        bbox = anno["bbox"]
        assert anno["bbox_mode"] in [
            BoxMode.XYXY_ABS,
            BoxMode.XYWH_ABS,
        ], "Relative coordinates not yet supported in visualization."
        iscrowd = anno.get("iscrowd", 0)
        clsid = anno["category_id"]
        text = class_names[clsid] if class_names is not None else str(clsid)
        if iscrowd:
            text = text + "_crowd"
        img = draw_text(img, (bbox[0], bbox[1] - 2), text)

        segs = anno.get("segmentation", None)
        if segs is not None and not iscrowd:
            segs_color = cmap[num % len(cmap)]
            mask = cv2.imread(segs)
            img = draw_mask(img, mask, segs_color, draw_contours=False)

        kpts = anno.get("keypoints", None)
        if kpts is not None and not iscrowd:
            kpts = np.asarray(kpts).reshape(-1, 3)[:, :2]
            img = draw_keypoints(img, kpts)
    return img