Python PIL.ImageEnhance.Color() Examples

def adjust_saturation(img, saturation_factor):
    """Adjust color saturation of an image.

    Args:
        img (PIL Image): PIL Image to be adjusted.
        saturation_factor (float):  How much to adjust the saturation. 0 will
            give a black and white image, 1 will give the original image while
            2 will enhance the saturation by a factor of 2.

    Returns:
        PIL Image: Saturation adjusted image.
    """
    if not _is_pil_image(img):
        raise TypeError('img should be PIL Image. Got {}'.format(type(img)))

    enhancer = ImageEnhance.Color(img)
    img = enhancer.enhance(saturation_factor)
    return img 

def adjust_saturation(img, saturation_factor):
    """Adjust color saturation of an image.

    Args:
        img (PIL Image): PIL Image to be adjusted.
        saturation_factor (float):  How much to adjust the saturation. 0 will
            give a black and white image, 1 will give the original image while
            2 will enhance the saturation by a factor of 2.

    Returns:
        PIL Image: Saturation adjusted image.
    """
    if not _is_pil_image(img):
        raise TypeError('img should be PIL Image. Got {}'.format(type(img)))

    enhancer = ImageEnhance.Color(img)
    img = enhancer.enhance(saturation_factor)
    return img 

def resize_and_bitmap(self, fname, size, enhance_color=False):
        """Take filename of an image and resize and center crop it to size."""
        try:
            pil = resize_to_fill(Image.open(fname), size, quality="fast")
        except UnidentifiedImageError:
            msg = ("Opening image '%s' failed with PIL.UnidentifiedImageError."
                   "It could be corrupted or is of foreign type.") % fname
            sp_logging.G_LOGGER.info(msg)
            # show_message_dialog(msg)
            black_bmp = wx.Bitmap.FromRGBA(size[0], size[1], red=0, green=0, blue=0, alpha=255)
            if enhance_color:
                return (black_bmp, black_bmp)
            return black_bmp
        img = wx.Image(pil.size[0], pil.size[1])
        img.SetData(pil.convert("RGB").tobytes())
        if enhance_color:
            converter = ImageEnhance.Color(pil)
            pilenh_bw = converter.enhance(0.25)
            brightns = ImageEnhance.Brightness(pilenh_bw)
            pilenh = brightns.enhance(0.45)
            imgenh = wx.Image(pil.size[0], pil.size[1])
            imgenh.SetData(pilenh.convert("RGB").tobytes())
            return (img.ConvertToBitmap(), imgenh.ConvertToBitmap())
        return img.ConvertToBitmap() 

def adjust_saturation(img, saturation_factor):
    """Adjust color saturation of an image.

    Args:
        img (PIL Image): PIL Image to be adjusted.
        saturation_factor (float):  How much to adjust the saturation. 0 will
            give a black and white image, 1 will give the original image while
            2 will enhance the saturation by a factor of 2.

    Returns:
        PIL Image: Saturation adjusted image.
    """
    if not _is_pil_image(img):
        raise TypeError('img should be PIL Image. Got {}'.format(type(img)))

    enhancer = ImageEnhance.Color(img)
    img = enhancer.enhance(saturation_factor)
    return img 

def adjust_saturation(img, saturation_factor):
    """Adjust color saturation of an image.

    Args:
        img (PIL Image): PIL Image to be adjusted.
        saturation_factor (float):  How much to adjust the saturation. 0 will
            give a black and white image, 1 will give the original image while
            2 will enhance the saturation by a factor of 2.

    Returns:
        PIL Image: Saturation adjusted image.
    """
    if not _is_pil_image(img):
        raise TypeError('img should be PIL Image. Got {}'.format(type(img)))

    enhancer = ImageEnhance.Color(img)
    img = enhancer.enhance(saturation_factor)
    return img 

def adjust_saturation(img, saturation_factor):
    """Adjust color saturation of an image.

    Args:
        img (PIL Image): PIL Image to be adjusted.
        saturation_factor (float):  How much to adjust the saturation. 0 will
            give a black and white image, 1 will give the original image while
            2 will enhance the saturation by a factor of 2.

    Returns:
        PIL Image: Saturation adjusted image.
    """
    if not _is_pil_image(img):
        raise TypeError('img should be PIL Image. Got {}'.format(type(img)))

    enhancer = ImageEnhance.Color(img)
    img = enhancer.enhance(saturation_factor)
    return img 

def image_color(self, factor: int, extension: str = "png"):
        """Change image color
        
        Args:
            factor (int): Factor to increase the color by
            extension (str, optional): File extension of loaded image. Defaults to "png"
        
        Returns:
            Chepy: The Chepy object. 
        """
        image = Image.open(self._load_as_file())
        image = self._force_rgb(image)
        fh = io.BytesIO()
        enhanced = ImageEnhance.Color(image).enhance(factor)
        enhanced.save(fh, extension)
        self.state = fh.getvalue()
        return self 

def adjust_saturation(img, saturation_factor):
    """Adjust color saturation of an image.

    Args:
        img (PIL Image): PIL Image to be adjusted.
        saturation_factor (float):  How much to adjust the saturation. 0 will
            give a black and white image, 1 will give the original image while
            2 will enhance the saturation by a factor of 2.

    Returns:
        PIL Image: Saturation adjusted image.
    """
    if not _is_pil_image(img):
        raise TypeError('img should be PIL Image. Got {}'.format(type(img)))

    enhancer = ImageEnhance.Color(img)
    img = enhancer.enhance(saturation_factor)
    return img 

def adjust_saturation(img, saturation_factor):
    """Adjust color saturation of an image.
    Args:
    img (PIL Image): PIL Image to be adjusted.
    saturation_factor (float):  How much to adjust the saturation. 0 will
    give a black and white image, 1 will give the original image while
    2 will enhance the saturation by a factor of 2.
    Returns:
    PIL Image: Saturation adjusted image.
    """
    if not is_pil_image(img):
        raise TypeError('img should be PIL Image. Got {}'.format(type(img)))

    enhancer = ImageEnhance.Color(img)
    img = enhancer.enhance(saturation_factor)
    return img 

def adjust_saturation(img, saturation_factor):
    """Adjust color saturation of an image.

    Args:
        img (PIL Image): PIL Image to be adjusted.
        saturation_factor (float):  How much to adjust the saturation. 0 will
            give a black and white image, 1 will give the original image while
            2 will enhance the saturation by a factor of 2.

    Returns:
        PIL Image: Saturation adjusted image.
    """
    if not _is_pil_image(img):
        raise TypeError('img should be PIL Image. Got {}'.format(type(img)))

    enhancer = ImageEnhance.Color(img)
    img = enhancer.enhance(saturation_factor)
    return img 

def adjust_saturation(img, saturation_factor):
    """Adjust color saturation of an image.

    Args:
        img (PIL Image): PIL Image to be adjusted.
        saturation_factor (float):  How much to adjust the saturation. 0 will
            give a black and white image, 1 will give the original image while
            2 will enhance the saturation by a factor of 2.

    Returns:
        PIL Image: Saturation adjusted image.
    """
    if not _is_pil_image(img):
        raise TypeError('img should be PIL Image. Got {}'.format(type(img)))

    enhancer = ImageEnhance.Color(img)
    img = enhancer.enhance(saturation_factor)
    return img 

def save_img(fname, image, image_enhance=False):  # 图像可以增强
    image = Image.fromarray(image)
    if image_enhance:
        # 亮度增强
        enh_bri = ImageEnhance.Brightness(image)
        brightness = 1.2
        image = enh_bri.enhance(brightness)

        # 色度增强
        enh_col = ImageEnhance.Color(image)
        color = 1.2
        image = enh_col.enhance(color)

        # 锐度增强
        enh_sha = ImageEnhance.Sharpness(image)
        sharpness = 1.2
        image = enh_sha.enhance(sharpness)
    imsave(fname, image)
    return 

def adjust_saturation(img, saturation_factor):
    """Adjust color saturation of an image.

    Args:
        img (PIL Image): PIL Image to be adjusted.
        saturation_factor (float):  How much to adjust the saturation. 0 will
            give a black and white image, 1 will give the original image while
            2 will enhance the saturation by a factor of 2.

    Returns:
        PIL Image: Saturation adjusted image.
    """
    if not _is_pil_image(img):
        raise TypeError('img should be PIL Image. Got {}'.format(type(img)))

    enhancer = ImageEnhance.Color(img)
    img = enhancer.enhance(saturation_factor)
    return img 

def __getitem__(self, index):
        im, xpatch, ypatch, rotation, flip, enhance = np.unravel_index(index, self.shape)

        with Image.open(self.names[im]) as img:
            extractor = PatchExtractor(img=img, patch_size=PATCH_SIZE, stride=self.stride)
            patch = extractor.extract_patch((xpatch, ypatch))

            if rotation != 0:
                patch = patch.rotate(rotation * 90)

            if flip != 0:
                patch = patch.transpose(Image.FLIP_LEFT_RIGHT)

            if enhance != 0:
                factors = np.random.uniform(.5, 1.5, 3)
                patch = ImageEnhance.Color(patch).enhance(factors[0])
                patch = ImageEnhance.Contrast(patch).enhance(factors[1])
                patch = ImageEnhance.Brightness(patch).enhance(factors[2])

            label = self.labels[self.names[im]]
            return transforms.ToTensor()(patch), label 

def adjust_saturation(img, saturation_factor):
    """Adjust color saturation of an image.
    Args:
        img (numpy ndarray): numpy ndarray to be adjusted.
        saturation_factor (float):  How much to adjust the saturation. 0 will
            give a black and white image, 1 will give the original image while
            2 will enhance the saturation by a factor of 2.
    Returns:
        numpy ndarray: Saturation adjusted image.
    """
    # ~10ms slower than PIL!
    if not _is_numpy_image(img):
        raise TypeError('img should be numpy Image. Got {}'.format(type(img)))
    img = Image.fromarray(img)
    enhancer = ImageEnhance.Color(img)
    img = enhancer.enhance(saturation_factor)
    return np.array(img) 

def modifyImageBscc(imageData, brightness, sharpness, contrast, color):
    """Update with brightness, sharpness, contrast and color."""

    brightnessMod = ImageEnhance.Brightness(imageData)
    imageData = brightnessMod.enhance(brightness)

    sharpnessMod = ImageEnhance.Sharpness(imageData)
    imageData = sharpnessMod.enhance(sharpness)

    contrastMod = ImageEnhance.Contrast(imageData)
    imageData = contrastMod.enhance(contrast)

    colorMod = ImageEnhance.Color(imageData)
    imageData = colorMod.enhance(color)

    return imageData 

def adjust_saturation(img, saturation_factor):
    """Adjust color saturation of an image.
    Args:
        img (PIL.Image): PIL Image to be adjusted.
        saturation_factor (float):  How much to adjust the saturation. 0 will
            give a black and white image, 1 will give the original image while
            2 will enhance the saturation by a factor of 2.
    Returns:
        PIL.Image: Saturation adjusted image.
    """
    if not _is_pil_image(img):
        raise TypeError('img should be PIL Image. Got {}'.format(type(img)))

    enhancer = ImageEnhance.Color(img)
    img = enhancer.enhance(saturation_factor)
    return img 

def lomoize (image,darkness,saturation):
	
	(width,height) = image.size

	max = width
	if height > width:
		max = height
	
	mask = Image.open("./lomolive/lomomask.jpg").resize((max,max))

	left = round((max - width) / 2)
	upper = round((max - height) / 2)
	
	mask = mask.crop((left,upper,left+width,upper + height))

#	mask = Image.open('mask_l.png')

	darker = ImageEnhance.Brightness(image).enhance(darkness)	
	saturated = ImageEnhance.Color(image).enhance(saturation)
	lomoized = Image.composite(saturated,darker,mask)
	
	return lomoized 

def __call__(self, img):
        factor = np.sqrt(np.sqrt(np.random.rand(1)))
        # print("gray {}".format(factor))
        enhancer = ImageEnhance.Color(img)
        return enhancer.enhance(factor) 

def __call__(self, image, *args):
        alpha = 1.0 + np.random.uniform(-self.var, self.var)
        image = ImageEnhance.Color(image).enhance(alpha)
        return (image, *args) 

def color(im, k=3):
	enhancer = ImageEnhance.Color(im)
	return enhancer.enhance(k) 

def __call__(self, img):
        """
        Args:
            img (PIL.Image): Input image.
        Returns:
            PIL.Image: Color jittered image.
        """
        transform = self.get_params(self.brightness, self.contrast,
                                    self.saturation, self.hue)
        return transform(img) 

def color(pil_img, level):
    level = float_parameter(sample_level(level), 1.8) + 0.1
    return ImageEnhance.Color(pil_img).enhance(level)


# operation that overlaps with ImageNet-C's test set 

def __call__(self, img):
        """
        Args:
            img (numpy.ndarray (C x H x W)): Input image.

        Returns:
            img (numpy.ndarray (C x H x W)): Color jittered image.
        """
        if not (_is_numpy_image(img)):
            raise TypeError('img should be ndarray. Got {}'.format(type(img)))

        pil = Image.fromarray(img)
        return np.array(self.transform(pil)) 

def __call__(self, image):
        if random.uniform(0, 1) > self.prob:
            return image
        else:
            magnitude_range = np.linspace(0.1, 1.9, 10)
            factor = magnitude_range[self.magnitude]
            enhancer = ImageEnhance.Color(image)
            return enhancer.enhance(factor) 

def __init__(self, prob, magnitude):
        super(Color, self).__init__(prob, magnitude) 

def __call__(self, im_lb):
        im = im_lb['im']
        lb = im_lb['lb']
        r_brightness = random.uniform(self.brightness[0], self.brightness[1])
        r_contrast = random.uniform(self.contrast[0], self.contrast[1])
        r_saturation = random.uniform(self.saturation[0], self.saturation[1])
        im = ImageEnhance.Brightness(im).enhance(r_brightness)
        im = ImageEnhance.Contrast(im).enhance(r_contrast)
        im = ImageEnhance.Color(im).enhance(r_saturation)
        return dict(im = im,
                    lb = lb,
                ) 

def __getitem__(self, index):
        im, rotation, flip, enhance = np.unravel_index(index, self.shape)

        with Image.open(self.names[im]) as img:

            if flip != 0:
                img = img.transpose(Image.FLIP_LEFT_RIGHT)

            if rotation != 0:
                img = img.rotate(rotation * 90)

            if enhance != 0:
                factors = np.random.uniform(.5, 1.5, 3)
                img = ImageEnhance.Color(img).enhance(factors[0])
                img = ImageEnhance.Contrast(img).enhance(factors[1])
                img = ImageEnhance.Brightness(img).enhance(factors[2])

            extractor = PatchExtractor(img=img, patch_size=PATCH_SIZE, stride=self.stride)
            patches = extractor.extract_patches()

            label = self.labels[self.names[im]]

            b = torch.zeros((len(patches), 3, PATCH_SIZE, PATCH_SIZE))
            for i in range(len(patches)):
                b[i] = transforms.ToTensor()(patches[i])

            return b, label 

def color(pil_img, level, *args):
    level = float_parameter(sample_level(level), 1.8) + 0.1
    return ImageEnhance.Color(pil_img).enhance(level)


# operation that overlaps with ImageNet-C's test set 

def auto_augment_policy_originalr(hparams):
    # ImageNet policy from https://arxiv.org/abs/1805.09501 with research posterize variation
    policy = [
        [('PosterizeIncreasing', 0.4, 8), ('Rotate', 0.6, 9)],
        [('Solarize', 0.6, 5), ('AutoContrast', 0.6, 5)],
        [('Equalize', 0.8, 8), ('Equalize', 0.6, 3)],
        [('PosterizeIncreasing', 0.6, 7), ('PosterizeIncreasing', 0.6, 6)],
        [('Equalize', 0.4, 7), ('Solarize', 0.2, 4)],
        [('Equalize', 0.4, 4), ('Rotate', 0.8, 8)],
        [('Solarize', 0.6, 3), ('Equalize', 0.6, 7)],
        [('PosterizeIncreasing', 0.8, 5), ('Equalize', 1.0, 2)],
        [('Rotate', 0.2, 3), ('Solarize', 0.6, 8)],
        [('Equalize', 0.6, 8), ('PosterizeIncreasing', 0.4, 6)],
        [('Rotate', 0.8, 8), ('Color', 0.4, 0)],
        [('Rotate', 0.4, 9), ('Equalize', 0.6, 2)],
        [('Equalize', 0.0, 7), ('Equalize', 0.8, 8)],
        [('Invert', 0.6, 4), ('Equalize', 1.0, 8)],
        [('Color', 0.6, 4), ('Contrast', 1.0, 8)],
        [('Rotate', 0.8, 8), ('Color', 1.0, 2)],
        [('Color', 0.8, 8), ('Solarize', 0.8, 7)],
        [('Sharpness', 0.4, 7), ('Invert', 0.6, 8)],
        [('ShearX', 0.6, 5), ('Equalize', 1.0, 9)],
        [('Color', 0.4, 0), ('Equalize', 0.6, 3)],
        [('Equalize', 0.4, 7), ('Solarize', 0.2, 4)],
        [('Solarize', 0.6, 5), ('AutoContrast', 0.6, 5)],
        [('Invert', 0.6, 4), ('Equalize', 1.0, 8)],
        [('Color', 0.6, 4), ('Contrast', 1.0, 8)],
        [('Equalize', 0.8, 8), ('Equalize', 0.6, 3)],
    ]
    pc = [[AugmentOp(*a, hparams=hparams) for a in sp] for sp in policy]
    return pc