Python functional.adjust_gamma方法代碼示例

本文整理匯總了Python中torchvision.transforms.functional.adjust_gamma方法的典型用法代碼示例。如果您正苦於以下問題：Python functional.adjust_gamma方法的具體用法？Python functional.adjust_gamma怎麽用？Python functional.adjust_gamma使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類torchvision.transforms.functional的用法示例。

在下文中一共展示了functional.adjust_gamma方法的7個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: cv_transform

# 需要導入模塊: from torchvision.transforms import functional [as 別名]
# 或者: from torchvision.transforms.functional import adjust_gamma [as 別名]
def cv_transform(img):
    # img = resize(img, size=(100, 300))
    # img = to_tensor(img)
    # img = normalize(img, mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
    # img = pad(img, padding=(10, 10, 20, 20), fill=(255, 255, 255), padding_mode='constant')
    # img = pad(img, padding=(100, 100, 100, 100), fill=5, padding_mode='symmetric')
    # img = crop(img, -40, -20, 1000, 1000)
    # img = center_crop(img, (310, 300))
    # img = resized_crop(img, -10.3, -20, 330, 220, (500, 500))
    # img = hflip(img)
    # img = vflip(img)
    # tl, tr, bl, br, center = five_crop(img, 100)
    # img = adjust_brightness(img, 2.1)
    # img = adjust_contrast(img, 1.5)
    # img = adjust_saturation(img, 2.3)
    # img = adjust_hue(img, 0.5)
    # img = adjust_gamma(img, gamma=3, gain=0.1)
    # img = rotate(img, 10, resample='BILINEAR', expand=True, center=None)
    # img = to_grayscale(img, 3)
    # img = affine(img, 10, (0, 0), 1, 0, resample='BICUBIC', fillcolor=(255,255,0))
    # img = gaussion_noise(img)
    # img = poisson_noise(img)
    img = salt_and_pepper(img)
    return to_tensor(img)

開發者ID:YU-Zhiyang，項目名稱:opencv_transforms_torchvision，代碼行數:26，代碼來源:cvfunctional.py

示例2: pil_transform

# 需要導入模塊: from torchvision.transforms import functional [as 別名]
# 或者: from torchvision.transforms.functional import adjust_gamma [as 別名]
def pil_transform(img):
    # img = functional.resize(img, size=(100, 300))
    # img = functional.to_tensor(img)
    # img = functional.normalize(img, mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
    # img = functional.pad(img, padding=(10, 10, 20, 20), fill=(255, 255, 255), padding_mode='constant')
    # img = functional.pad(img, padding=(100, 100, 100, 100), padding_mode='symmetric')
    # img = functional.crop(img, -40, -20, 1000, 1000)
    # img = functional.center_crop(img, (310, 300))
    # img = functional.resized_crop(img, -10.3, -20, 330, 220, (500, 500))
    # img = functional.hflip(img)
    # img = functional.vflip(img)
    # tl, tr, bl, br, center = functional.five_crop(img, 100)
    # img = functional.adjust_brightness(img, 2.1)
    # img = functional.adjust_contrast(img, 1.5)
    # img = functional.adjust_saturation(img, 2.3)
    # img = functional.adjust_hue(img, 0.5)
    # img = functional.adjust_gamma(img, gamma=3, gain=0.1)
    # img = functional.rotate(img, 10, resample=PIL.Image.BILINEAR, expand=True, center=None)
    # img = functional.to_grayscale(img, 3)
    # img = functional.affine(img, 10, (0, 0), 1, 0, resample=PIL.Image.BICUBIC, fillcolor=(255,255,0))

    return functional.to_tensor(img)

開發者ID:YU-Zhiyang，項目名稱:opencv_transforms_torchvision，代碼行數:24，代碼來源:cvfunctional.py

示例3: adjust_gamma

# 需要導入模塊: from torchvision.transforms import functional [as 別名]
# 或者: from torchvision.transforms.functional import adjust_gamma [as 別名]
def adjust_gamma(img, gamma, gain=1):
    """Perform gamma correction on an image.

    Also known as Power Law Transform. Intensities in RGB mode are adjusted
    based on the following equation:

        I_out = 255 * gain * ((I_in / 255) ** gamma)

    See https://en.wikipedia.org/wiki/Gamma_correction for more details.

    Args:
        img (np.ndarray): CV Image to be adjusted.
        gamma (float): Non negative real number. gamma larger than 1 make the
            shadows darker, while gamma smaller than 1 make dark regions
            lighter.
        gain (float): The constant multiplier.
    """
    if not _is_numpy_image(img):
        raise TypeError('img should be CV Image. Got {}'.format(type(img)))

    if gamma < 0:
        raise ValueError('Gamma should be a non-negative real number')

    im = img.astype(np.float32)
    im = 255. * gain * np.power(im / 255., gamma)
    im = im.clip(min=0., max=255.)
    return im.astype(img.dtype)

開發者ID:YU-Zhiyang，項目名稱:opencv_transforms_torchvision，代碼行數:29，代碼來源:cvfunctional.py

示例4: gamma

# 需要導入模塊: from torchvision.transforms import functional [as 別名]
# 或者: from torchvision.transforms.functional import adjust_gamma [as 別名]
def gamma(self, gamma_ratio):
        self.data = TF.adjust_gamma(self.data, gamma_ratio, gain=1)

開發者ID:MichaelRamamonjisoa，項目名稱:SharpNet，代碼行數:4，代碼來源:representations.py

示例5: call

# 需要導入模塊: from torchvision.transforms import functional [as 別名]
# 或者: from torchvision.transforms.functional import adjust_gamma [as 別名]
def __call__(self, img, mask):
        assert img.size == mask.size
        return tf.adjust_gamma(img, random.uniform(1, 1 + self.gamma)), mask

開發者ID:RogerZhangzz，項目名稱:CAG_UDA，代碼行數:5，代碼來源:augmentations.py

示例6: call

# 需要導入模塊: from torchvision.transforms import functional [as 別名]
# 或者: from torchvision.transforms.functional import adjust_gamma [as 別名]
def __call__(self, img):
        if random.random() < 0.5:
            gamma = random.uniform(self.gamma_range[0],self.gamma_range[1])
            return  TrF.adjust_gamma(img, gamma)
        else: 
            return img

# ===============================label tranforms============================

開發者ID:gjy3035，項目名稱:NWPU-Crowd-Sample-Code，代碼行數:10，代碼來源:transforms.py

示例7: torchvision_transform

# 需要導入模塊: from torchvision.transforms import functional [as 別名]
# 或者: from torchvision.transforms.functional import adjust_gamma [as 別名]
def torchvision_transform(self, img):
        return torchvision.adjust_gamma(img, gamma=0.5)

開發者ID:albumentations-team，項目名稱:albumentations，代碼行數:4，代碼來源:benchmark.py

注：本文中的torchvision.transforms.functional.adjust_gamma方法示例由純淨天空整理自Github/MSDocs等開源代碼及文檔管理平台，相關代碼片段篩選自各路編程大神貢獻的開源項目，源碼版權歸原作者所有，傳播和使用請參考對應項目的License；未經允許，請勿轉載。