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Python ImageEnhance.Color方法代码示例

本文整理汇总了Python中PIL.ImageEnhance.Color方法的典型用法代码示例。如果您正苦于以下问题:Python ImageEnhance.Color方法的具体用法?Python ImageEnhance.Color怎么用?Python ImageEnhance.Color使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在PIL.ImageEnhance的用法示例。


在下文中一共展示了ImageEnhance.Color方法的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: adjust_saturation

# 需要导入模块: from PIL import ImageEnhance [as 别名]
# 或者: from PIL.ImageEnhance import Color [as 别名]
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 
开发者ID:miraiaroha,项目名称:ACAN,代码行数:20,代码来源:transforms.py

示例2: adjust_saturation

# 需要导入模块: from PIL import ImageEnhance [as 别名]
# 或者: from PIL.ImageEnhance import Color [as 别名]
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) 
开发者ID:CMU-CREATE-Lab,项目名称:deep-smoke-machine,代码行数:19,代码来源:opencv_functional.py

示例3: resize_and_bitmap

# 需要导入模块: from PIL import ImageEnhance [as 别名]
# 或者: from PIL.ImageEnhance import Color [as 别名]
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() 
开发者ID:hhannine,项目名称:superpaper,代码行数:26,代码来源:gui.py

示例4: image_color

# 需要导入模块: from PIL import ImageEnhance [as 别名]
# 或者: from PIL.ImageEnhance import Color [as 别名]
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 
开发者ID:securisec,项目名称:chepy,代码行数:19,代码来源:multimedia.py

示例5: modifyImageBscc

# 需要导入模块: from PIL import ImageEnhance [as 别名]
# 或者: from PIL.ImageEnhance import Color [as 别名]
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 
开发者ID:BerkeleyLearnVerify,项目名称:VerifAI,代码行数:18,代码来源:generator.py

示例6: lomoize

# 需要导入模块: from PIL import ImageEnhance [as 别名]
# 或者: from PIL.ImageEnhance import Color [as 别名]
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 
开发者ID:Lavande,项目名称:wx-fancy-pic,代码行数:24,代码来源:lomolive.py

示例7: __getitem__

# 需要导入模块: from PIL import ImageEnhance [as 别名]
# 或者: from PIL.ImageEnhance import Color [as 别名]
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 
开发者ID:ImagingLab,项目名称:ICIAR2018,代码行数:23,代码来源:datasets.py

示例8: adjust_saturation

# 需要导入模块: from PIL import ImageEnhance [as 别名]
# 或者: from PIL.ImageEnhance import Color [as 别名]
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 
开发者ID:almazan,项目名称:deep-image-retrieval,代码行数:18,代码来源:transforms_tools.py

示例9: save_img

# 需要导入模块: from PIL import ImageEnhance [as 别名]
# 或者: from PIL.ImageEnhance import Color [as 别名]
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 
开发者ID:yuweiming70,项目名称:Style_Migration_For_Artistic_Font_With_CNN,代码行数:21,代码来源:neural_style_transfer.py

示例10: adjust_saturation

# 需要导入模块: from PIL import ImageEnhance [as 别名]
# 或者: from PIL.ImageEnhance import Color [as 别名]
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 
开发者ID:YuanXue1993,项目名称:SegAN,代码行数:18,代码来源:transform.py

示例11: __call__

# 需要导入模块: from PIL import ImageEnhance [as 别名]
# 或者: from PIL.ImageEnhance import Color [as 别名]
def __call__(self, img):
        """
        Args:
            img (numpy.ndarray (H x W x C)): Input image.

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

        pil = Image.fromarray(img)
        transform = self.get_params(self.brightness, self.contrast,
                                    self.saturation, self.hue)
        return np.array(transform(pil)) 
开发者ID:miraiaroha,项目名称:ACAN,代码行数:17,代码来源:transforms.py

示例12: __init__

# 需要导入模块: from PIL import ImageEnhance [as 别名]
# 或者: from PIL.ImageEnhance import Color [as 别名]
def __init__(self):
        self.policies = [
            ['Invert', 0.1, 7, 'Contrast', 0.2, 6],
            ['Rotate', 0.7, 2, 'TranslateX', 0.3, 9],
            ['Sharpness', 0.8, 1, 'Sharpness', 0.9, 3],
            ['ShearY', 0.5, 8, 'TranslateY', 0.7, 9],
            ['AutoContrast', 0.5, 8, 'Equalize', 0.9, 2],
            ['ShearY', 0.2, 7, 'Posterize', 0.3, 7],
            ['Color', 0.4, 3, 'Brightness', 0.6, 7],
            ['Sharpness', 0.3, 9, 'Brightness', 0.7, 9],
            ['Equalize', 0.6, 5, 'Equalize', 0.5, 1],
            ['Contrast', 0.6, 7, 'Sharpness', 0.6, 5],
            ['Color', 0.7, 7, 'TranslateX', 0.5, 8],
            ['Equalize', 0.3, 7, 'AutoContrast', 0.4, 8],
            ['TranslateY', 0.4, 3, 'Sharpness', 0.2, 6],
            ['Brightness', 0.9, 6, 'Color', 0.2, 8],
            ['Solarize', 0.5, 2, 'Invert', 0, 0.3],
            ['Equalize', 0.2, 0, 'AutoContrast', 0.6, 0],
            ['Equalize', 0.2, 8, 'Equalize', 0.6, 4],
            ['Color', 0.9, 9, 'Equalize', 0.6, 6],
            ['AutoContrast', 0.8, 4, 'Solarize', 0.2, 8],
            ['Brightness', 0.1, 3, 'Color', 0.7, 0],
            ['Solarize', 0.4, 5, 'AutoContrast', 0.9, 3],
            ['TranslateY', 0.9, 9, 'TranslateY', 0.7, 9],
            ['AutoContrast', 0.9, 2, 'Solarize', 0.8, 3],
            ['Equalize', 0.8, 8, 'Invert', 0.1, 3],
            ['TranslateY', 0.7, 9, 'AutoContrast', 0.9, 1],
        ] 
开发者ID:ngessert,项目名称:isic2019,代码行数:30,代码来源:auto_augment.py

示例13: color

# 需要导入模块: from PIL import ImageEnhance [as 别名]
# 或者: from PIL.ImageEnhance import Color [as 别名]
def color(img, magnitude):
    magnitudes = np.linspace(0.1, 1.9, 11)
    img = ImageEnhance.Color(img).enhance(random.uniform(magnitudes[magnitude], magnitudes[magnitude+1]))
    return img 
开发者ID:ngessert,项目名称:isic2019,代码行数:6,代码来源:auto_augment.py

示例14: __call__

# 需要导入模块: from PIL import ImageEnhance [as 别名]
# 或者: from PIL.ImageEnhance import Color [as 别名]
def __call__(self, image, label):


        #aug blur
        if random.random() > set_ratio:
            select = random.random()
            if select < 0.3:
                kernalsize = random.choice([3, 5])
                image = cv2.GaussianBlur(image, (kernalsize, kernalsize), 0)
            elif select < 0.6:
                kernalsize = random.choice([3, 5])
                image = cv2.medianBlur(image, kernalsize)
            else:
                kernalsize = random.choice([3, 5])
                image = cv2.blur(image, (kernalsize, kernalsize))

        # aug noise
        if random.random() > set_ratio:
            mu = 0
            sigma = random.random() * 10.0
            image = np.array(image, dtype=np.float32)
            image += np.random.normal(mu, sigma, image.shape)
            image[image > 255] = 255
            image[image < 0] = 0

        # aug_color
        if random.random() > set_ratio:

            random_factor = np.random.randint(4, 17) / 10.
            color_image = ImageEnhance.Color(image).enhance(random_factor)
            random_factor = np.random.randint(4, 17) / 10.
            brightness_image = ImageEnhance.Brightness(color_image).enhance(random_factor)
            random_factor = np.random.randint(6, 15) / 10.
            contrast_image = ImageEnhance.Contrast(brightness_image).enhance(random_factor)
            random_factor = np.random.randint(8, 13) / 10.
            image = ImageEnhance.Sharpness(contrast_image).enhance(random_factor)

        return np.array(image), label 
开发者ID:clovaai,项目名称:ext_portrait_segmentation,代码行数:40,代码来源:CVTransforms.py

示例15: random_perturbation

# 需要导入模块: from PIL import ImageEnhance [as 别名]
# 或者: from PIL.ImageEnhance import Color [as 别名]
def random_perturbation(imgs):
    for i in range(imgs.shape[0]):
        im=Image.fromarray(imgs[i,...].astype(np.uint8))
        en=ImageEnhance.Brightness(im)
        im=en.enhance(random.uniform(0.8,1.2))
        en=ImageEnhance.Color(im)
        im=en.enhance(random.uniform(0.8,1.2))
        en=ImageEnhance.Contrast(im)
        im=en.enhance(random.uniform(0.8,1.2))
        imgs[i,...]= np.asarray(im).astype(np.float32)
    return imgs 
开发者ID:jaeminSon,项目名称:V-GAN,代码行数:13,代码来源:utils.py


注:本文中的PIL.ImageEnhance.Color方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。