7e1e3ecee5930c527c7f1c89cdd4719d826095e5,chainercv/links/model/mask_rcnn/misc.py,,segm_to_mask,#Any#Any#Any#Any#,54

Before Change

    for i, (bb, sgm) in enumerate(zip(bbox, segm)):
        padded_mask[1:-1, 1:-1] = sgm

        bb_height = np.maximum(bb[2] - bb[0], 1)
        bb_width = np.maximum(bb[3] - bb[1], 1)

        crop_mask = cv2.resize(padded_mask, (bb_width, bb_height))
        crop_mask = crop_mask > 0.5

After Change

        bb_height = bb[2] - bb[0]
        bb_width = bb[3] - bb[1]
        if bb_height == 0 or bb_width == 0:
            continue

        crop_mask = transforms.resize(padded_mask[None], (bb_width, bb_height))[0]
        crop_mask = crop_mask > 0.5

        y_min = max(bb[0], 0)
        x_min = max(bb[1], 0)
        y_max = max(min(bb[2], H), 0)
        x_max = max(min(bb[3], W), 0)
        y_offset = y_min - bb[0]
        x_offset = x_min - bb[1]
        mask[i, y_min:y_max, x_min:x_max] = crop_mask[
            y_offset:y_offset + y_max - y_min,
            x_offset:x_offset + x_max - x_min]

Instances