90b78b1379b3423aa3b4b5d0de7313f88bda23ab,chainercv/utils/mask/mask_to_bbox.py,,mask_to_bbox,#,5

Before Change

    bbox = []
    for msk in mask:
        where = np.argwhere(msk)
        if len(where) > 0:
            y_min, x_min = where.min(0)
            y_max, x_max = where.max(0) + 1
        else:
            y_min, x_min, y_max, x_max = 0, 0, 0, 0
        bbox.append((y_min, x_min, y_max, x_max))
    if len(bbox) == 0:
        return xp.empty((0, 4), dtype=np.float32)
    return xp.array(bbox, dtype=np.float32)

After Change

    R, H, W = mask.shape
    xp = cuda.get_array_module(mask)

    instance_index, ys, xs = xp.nonzero(mask)
    bbox = xp.zeros((R, 4), dtype=np.float32)
    for i in range(R):
        ys_i = ys[instance_index == i]
        xs_i = xs[instance_index == i]

Instances