def resize_short_within()

in components/artifacts/aws.sagemaker.edgeManagerPythonClient/0.1.0/edge_manager_python_client.py [0:0]

• 13 lines of code
• 3 McCabe index (conditional complexity)

def resize_short_within(img, short=512, max_size=1024, mult_base=32, interp=2):
    """
    resizes the short side of the image so the aspect ratio remains the same AND the short
    side matches the convolutional layer for the network
​
    Args:
    -----
    img: np.array
        image you want to resize
    short: int
        the size to reshape the image to
    max_size: int
        the max size of the short side
    mult_base: int
        the size scale to readjust the resizer
    interp: int
        see '_get_interp_method'
    Returns:
    --------
    img: np.array
        the resized array
    """
    h, w, _ = img.shape
    im_size_min, im_size_max = (h, w) if w > h else (w, h)
    scale = float(short) / float(im_size_min)
    if np.round(scale * im_size_max / mult_base) * mult_base > max_size:
        # fit in max_size
        scale = float(np.floor(max_size / mult_base) * mult_base) / float(im_size_max)
    new_w, new_h = (
        int(np.round(w * scale / mult_base) * mult_base),
        int(np.round(h * scale / mult_base) * mult_base)
    )
    img = cv2.resize(img, (new_w, new_h),
                     interpolation=_get_interp_method(interp, (h, w, new_h, new_w)))
    return img