10 examples of 'scale and convert images using pil help' in Python

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def scale_image(image, scale_ratio):
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    # type: (Image.Image, float) -> Image.Image
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    if scale_ratio == 1:
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        return image
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    image_ratio = float(image.height) / float(image.width)
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    scale_width = int(math.ceil(image.width * scale_ratio))
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    scale_height = int(math.ceil(scale_width * image_ratio))
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    image = image.convert('RGBA')
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    scaled_image = image.resize((scale_width, scale_height), resample=Image.BICUBIC)
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    return scaled_image

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def scale_image(self, image, scale):
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    if self.settings.opencv_or_pil == 'PIL':
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        ow, oh = image.size
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        nw = ow * scale
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        nh = oh * scale
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        return image.resize((int(nw), int(nh)), Image.ANTIALIAS)
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    else:
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        oh, ow, channels = image.shape
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        nw = ow * scale
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        nh = oh * scale
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        # PERF return cv2.resize(image, (int(nw), int(nh)), interpolation=cv2.INTER_NEAREST)
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        return cv2.resize(image, (int(nw), int(nh)), interpolation=cv2.INTER_CUBIC)

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def _pil_convert_(self, image, mode="L"):
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    """ Convert image. Actually calls ``image.convert(mode)``.
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    Parameters
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    ----------
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    mode : str
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        Pass 'L' to convert to grayscale
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    src : str
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        Component to get images from. Default is 'images'.
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    dst : str
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        Component to write images to. Default is 'images'.
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    p : float
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        Probability of applying the transform. Default is 1.
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    """
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    return image.convert(mode)

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@staticmethod
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def scale_image(img, max_width=0, max_height=0, keep_ratio=True, ratio=1):
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    """
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    缩放图像
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    :param numpy.ndarray img:
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    :param int max_width:
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    :param int max_height:
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    :param bool keep_ratio:
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    :param int ratio:
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    :return int:
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    """
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    if ratio != 1:
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        height, width, _ = img.shape
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        return ratio, cv2.resize(img, (int(width / ratio), int(height / ratio)))
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    elif keep_ratio and max_width > 0 and max_height > 0:
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        height, width, _ = img.shape
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        width_ratio = width / max_width
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        height_ratio = height / max_height
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        ratio = max(width_ratio, height_ratio)
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        return ratio, cv2.resize(img, (int(width / ratio), int(height / ratio)))
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    else:
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        return 0, cv2.resize(img, (max_width, max_height))

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def Quick_Scale_To_im(path=None, im=None, source_dpi=600, target_dpi=150,
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                      scale=None):
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    if im is None:
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        try:
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            im = load_image_to_numpy(path, dtype=np.uint8)
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        except:
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            _logger.error("Could not open source")
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            return -1
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    if scale is None:
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        scale = target_dpi / float(source_dpi)
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    small_im = zoom(im, scale, order=1)
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    return small_im

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def rescale_images(images, scale=8):
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    num_iter = len(images)
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    dim = np.array(list(images[0].shape[:2]))
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    new_dims = tuple(dim*scale + [3])
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    resized_images = []
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    for i in range(num_iter):
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        resized = cv2.resize(images[i], new_dims, interpolation = cv2.INTER_AREA)
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        resized_images.append(resized)
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    return resized_images

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def cli_convert_image (self, img_bgr, img_landmarks, debug):
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    #img_landmarks not None, if input image is png with embedded data
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    #return float32 image
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    #if debug , return tuple ( images of any size and channels, ...)
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    return image

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def _colorspace(self, im, bw=False, replace_alpha=False):
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    """
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    A utility method taken from SmileyChris' easy-thumbnails that a lot of
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    processors will probably want to use.
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    Convert images to the correct color space.
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    bw
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        Make the thumbnail grayscale (not really just black & white).
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    replace_alpha
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        Replace any transparency layer with a solid color. For example,
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        ``replace_alpha='#fff'`` would replace the transparency layer with
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        white.
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    """
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    if bw and im.mode != 'L':
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        return im.convert('L')
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    if im.mode in ('L', 'RGB'):
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        return im
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    if im.mode == 'RGBA' or (im.mode == 'P' and 'transparency' in im.info):
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        if im.mode != 'RGBA':
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            im = im.convert('RGBA')
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        if not replace_alpha:
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            return im
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        base = Image.new('RGBA', im.size, replace_alpha)
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        base.paste(im)
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        im = base
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    return im.convert('RGB')

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def _resize_pil(img, size, interpolation):
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    C = img.shape[0]
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    H, W = size
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    out = np.empty((C, H, W), dtype=img.dtype)
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    for ch, out_ch in zip(img, out):
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        ch = PIL.Image.fromarray(ch, mode='F')
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        out_ch[:] = ch.resize((W, H), resample=interpolation)
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    return out

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def engine_scale(self, image, width, height):
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    image.resize(width, height)
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    return image