6701f27afa62712b34a17d4b0ff879156b0c7937,keras_preprocessing/image/utils.py,,load_img,#Any#Any#Any#Any#Any#Any#,75

Before Change

    if pil_image is None:
        raise ImportError("Could not import PIL.Image. "
                          "The use of `load_img` requires PIL.")
    with open(path, "rb") as f:
        img = pil_image.open(io.BytesIO(f.read()))
        if color_mode == "grayscale":
            // if image is not already an 8-bit, 16-bit or 32-bit grayscale image
            // convert it to an 8-bit grayscale image.
            if img.mode not in ("L", "I;16", "I"):
                img = img.convert("L")
        elif color_mode == "rgba":
            if img.mode != "RGBA":
                img = img.convert("RGBA")
        elif color_mode == "rgb":
            if img.mode != "RGB":
                img = img.convert("RGB")
        else:
            raise ValueError("color_mode must be "grayscale", "rgb", or "rgba"")
        if target_size is not None:
            width_height_tuple = (target_size[1], target_size[0])
            if img.size != width_height_tuple:
                if interpolation not in _PIL_INTERPOLATION_METHODS:
                    raise ValueError(
                        "Invalid interpolation method {} specified. Supported "
                        "methods are {}".format(
                            interpolation,
                            ", ".join(_PIL_INTERPOLATION_METHODS.keys())))
                resample = _PIL_INTERPOLATION_METHODS[interpolation]

                if keep_aspect_ratio:
                    width, height = img.size
                    target_width, target_height = width_height_tuple

                    crop_height = (width * target_height) // target_width
                    crop_width = (height * target_width) // target_height

                    // Set back to input height / width
                    // if crop_height / crop_width is not smaller.
                    crop_height = min(height, crop_height)
                    crop_width = min(width, crop_width)

                    crop_box_hstart = (height - crop_height) // 2
                    crop_box_wstart = (width - crop_width) // 2
                    crop_box_wend = crop_box_wstart + crop_width
                    crop_box_hend = crop_box_hstart + crop_height
                    crop_box = [crop_box_wstart, crop_box_hstart,
                                crop_box_wend, crop_box_hend]

                    img = img.resize(width_height_tuple, resample,
                                     box=crop_box)
                else:
                    img = img.resize(width_height_tuple, resample)
        return img


def list_pictures(directory, ext=("jpg", "jpeg", "bmp", "png", "ppm", "tif",
                                  "tiff")):
    Lists all pictures in a directory, including all subdirectories.

After Change

    if pil_image is None:
        raise ImportError("Could not import PIL.Image. "
                          "The use of `load_img` requires PIL.")
    if isinstance(path, io.BytesIO):
        img = pil_image.open(path)
    elif isinstance(path, (Path, bytes, str)):
        if isinstance(path, Path):
            path = str(path.resolve())
        with open(path, "rb") as f:
            img = pil_image.open(io.BytesIO(f.read()))
    else:
        raise TypeError("path should be path-like or io.BytesIO"
                        ", not {}".format(type(path)))

    if color_mode == "grayscale":
        // if image is not already an 8-bit, 16-bit or 32-bit grayscale image
        // convert it to an 8-bit grayscale image.
        if img.mode not in ("L", "I;16", "I"):

Instances