def get_crop_region(mask_image: PIL.Image.Image, width: int, height: int, pad=0):
        r"""
        Finds a rectangular region that contains all masked ares in an image, and expands region to match the aspect
        ratio of the original image; for example, if user drew mask in a 128x32 region, and the dimensions for
        processing are 512x512, the region will be expanded to 128x128.

        Args:
            mask_image (PIL.Image.Image): Mask image.
            width (int): Width of the image to be processed.
            height (int): Height of the image to be processed.
            pad (int, optional): Padding to be added to the crop region. Defaults to 0.

        Returns:
            tuple: (x1, y1, x2, y2) represent a rectangular region that contains all masked ares in an image and
            matches the original aspect ratio.
        """

        mask_image = mask_image.convert("L")
        mask = np.array(mask_image)

        # 1. find a rectangular region that contains all masked ares in an image
        h, w = mask.shape
        crop_left = 0
        for i in range(w):
            if not (mask[:, i] == 0).all():
                break
            crop_left += 1

        crop_right = 0
        for i in reversed(range(w)):
            if not (mask[:, i] == 0).all():
                break
            crop_right += 1

        crop_top = 0
        for i in range(h):
            if not (mask[i] == 0).all():
                break
            crop_top += 1

        crop_bottom = 0
        for i in reversed(range(h)):
            if not (mask[i] == 0).all():
                break
            crop_bottom += 1

        # 2. add padding to the crop region
        x1, y1, x2, y2 = (
            int(max(crop_left - pad, 0)),
            int(max(crop_top - pad, 0)),
            int(min(w - crop_right + pad, w)),
            int(min(h - crop_bottom + pad, h)),
        )

        # 3. expands crop region to match the aspect ratio of the image to be processed
        ratio_crop_region = (x2 - x1) / (y2 - y1)
        ratio_processing = width / height

        if ratio_crop_region > ratio_processing:
            desired_height = (x2 - x1) / ratio_processing
            desired_height_diff = int(desired_height - (y2 - y1))
            y1 -= desired_height_diff // 2
            y2 += desired_height_diff - desired_height_diff // 2
            if y2 >= mask_image.height:
                diff = y2 - mask_image.height
                y2 -= diff
                y1 -= diff
            if y1 < 0:
                y2 -= y1
                y1 -= y1
            if y2 >= mask_image.height:
                y2 = mask_image.height
        else:
            desired_width = (y2 - y1) * ratio_processing
            desired_width_diff = int(desired_width - (x2 - x1))
            x1 -= desired_width_diff // 2
            x2 += desired_width_diff - desired_width_diff // 2
            if x2 >= mask_image.width:
                diff = x2 - mask_image.width
                x2 -= diff
                x1 -= diff
            if x1 < 0:
                x2 -= x1
                x1 -= x1
            if x2 >= mask_image.width:
                x2 = mask_image.width

        return x1, y1, x2, y2

        Finds a rectangular region that contains all masked ares in an image, and expands region to match the aspect
        ratio of the original image; for example, if user drew mask in a 128x32 region, and the dimensions for
        processing are 512x512, the region will be expanded to 128x128.

        Args:
            mask_image (PIL.Image.Image): Mask image.
            width (int): Width of the image to be processed.
            height (int): Height of the image to be processed.
            pad (int, optional): Padding to be added to the crop region. Defaults to 0.

        Returns:
            tuple: (x1, y1, x2, y2) represent a rectangular region that contains all masked ares in an image and
            matches the original aspect ratio.
        
src/diffusers/image_processor.py