Python PIL.Image.composite() Examples

def mask_img(img, attn, upscale=32):
		"""
		Put attention weights to each region in image.
		--------------------
		Arguments:
			img (ndarray: H x W x C): image data.
			attn (ndarray: 14 x 14): attention weights of each region.
			upscale (int): the ratio between attention size and image size.
		"""
		attn = transform.pyramid_expand(attn, upscale=upscale, sigma=20)
		attn = misc.toimage(attn).convert("L")
		mask = misc.toimage(np.zeros(img.shape, dtype=np.uint8)).convert("RGBA")
		img = misc.toimage(img).convert("RGBA")
		img = Image.composite(img, mask, attn)

		return img 

def get_rotated_image_labels(client, image, bg, phi):

    # https://stackoverflow.com/a/5253554
    rot = image.rotate(-phi)   # clockwise
    image_tf = Image.composite(rot, bg, rot)

    filename = str(phi) + '.png'
    image_tf.convert('RGB').save(os.path.join(output_path, filename))

    # https://stackoverflow.com/a/33117447
    imgByteArr = io.BytesIO()
    image_tf.save(imgByteArr, format='PNG')
    imgByteArr = imgByteArr.getvalue() 

    image = types.Image(content=imgByteArr)
    response = client.label_detection(image=image)
    return response 

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 draw_mask_on_image_array(image, mask, color='red', alpha=0.7):
  """Draws mask on an image.

  Args:
    image: uint8 numpy array with shape (img_height, img_height, 3)
    mask: a uint8 numpy array of shape (img_height, img_height) with
      values between either 0 or 1.
    color: color to draw the keypoints with. Default is red.
    alpha: transparency value between 0 and 1. (default: 0.7)

  Raises:
    ValueError: On incorrect data type for image or masks.
  """
  if image.dtype != np.uint8:
    raise ValueError('`image` not of type np.uint8')
  if mask.dtype != np.uint8:
    raise ValueError('`mask` not of type np.uint8')
  if np.any(np.logical_and(mask != 1, mask != 0)):
    raise ValueError('`mask` elements should be in [0, 1]')
  rgb = ImageColor.getrgb(color)
  pil_image = Image.fromarray(image)

  solid_color = np.expand_dims(
      np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
  pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
  pil_mask = Image.fromarray(np.uint8(255.0*alpha*mask)).convert('L')
  pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
  np.copyto(image, np.array(pil_image.convert('RGB'))) 

def rotate_with_random_bg(img, angle, resample=Image.BILINEAR, expand=True):

    is_numpy = isinstance(img, np.ndarray)

    if not _is_pil_image(img):
        if is_numpy:
            img = Image.fromarray(img)
        else:
            raise TypeError(
                'img should be PIL Image or numpy array. \
                Got {}'.format(type(img)))

    img_np = np.array(img)

    img = img.convert('RGBA')
    img = rotate(img, angle, resample=resample, expand=expand)

    key = np.random.choice([0, 1, 2, 3])
    if key == 0:
        bg = Image.new('RGBA', img.size, (255, ) * 4)    # White image
    elif key == 1:
        bg = Image.new('RGBA', img.size, (0, 0, 0, 255)) # Black image
    elif key == 2:
        mean_color = map(int, img_np.mean((0, 1)))
        bg = Image.new('RGBA', img.size, (mean_color[0], mean_color[1], mean_color[2], 255)) # Mean
    elif key == 3:
        median_color = map(int, np.median(img_np, (0, 1)))
        bg = Image.new('RGBA', img.size, (median_color[0], median_color[1], median_color[2], 255)) # Median

    img = Image.composite(img, bg, img)
    img = img.convert('RGB')

    if is_numpy:
        img = np.array(img)

    return img 

def draw_mask_on_image_array(image, mask, color='red', alpha=0.7):
  """Draws mask on an image.

  Args:
    image: uint8 numpy array with shape (img_height, img_height, 3)
    mask: a float numpy array of shape (img_height, img_height) with
      values between 0 and 1
    color: color to draw the keypoints with. Default is red.
    alpha: transparency value between 0 and 1. (default: 0.7)

  Raises:
    ValueError: On incorrect data type for image or masks.
  """
  if image.dtype != np.uint8:
    raise ValueError('`image` not of type np.uint8')
  if mask.dtype != np.float32:
    raise ValueError('`mask` not of type np.float32')
  if np.any(np.logical_or(mask > 1.0, mask < 0.0)):
    raise ValueError('`mask` elements should be in [0, 1]')
  rgb = ImageColor.getrgb(color)
  pil_image = Image.fromarray(image)

  solid_color = np.expand_dims(
      np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
  pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
  pil_mask = Image.fromarray(np.uint8(255.0*alpha*mask)).convert('L')
  pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
  np.copyto(image, np.array(pil_image.convert('RGB'))) 

def draw_mask_on_image_array(image, mask, color='red', alpha=0.7):
  """Draws mask on an image.

  Args:
    image: uint8 numpy array with shape (img_height, img_height, 3)
    mask: a float numpy array of shape (img_height, img_height) with
      values between 0 and 1
    color: color to draw the keypoints with. Default is red.
    alpha: transparency value between 0 and 1. (default: 0.7)

  Raises:
    ValueError: On incorrect data type for image or masks.
  """
  if image.dtype != np.uint8:
    raise ValueError('`image` not of type np.uint8')
  if mask.dtype != np.float32:
    raise ValueError('`mask` not of type np.float32')
  if np.any(np.logical_or(mask > 1.0, mask < 0.0)):
    raise ValueError('`mask` elements should be in [0, 1]')
  rgb = ImageColor.getrgb(color)
  pil_image = Image.fromarray(image)

  solid_color = np.expand_dims(
      np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
  pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
  pil_mask = Image.fromarray(np.uint8(255.0*alpha*mask)).convert('L')
  pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
  np.copyto(image, np.array(pil_image.convert('RGB'))) 

def draw_mask_on_image_array(image, mask, color='red', alpha=0.4):
  """Draws mask on an image.

  Args:
    image: uint8 numpy array with shape (img_height, img_height, 3)
    mask: a uint8 numpy array of shape (img_height, img_height) with
      values between either 0 or 1.
    color: color to draw the keypoints with. Default is red.
    alpha: transparency value between 0 and 1. (default: 0.4)

  Raises:
    ValueError: On incorrect data type for image or masks.
  """
  if image.dtype != np.uint8:
    raise ValueError('`image` not of type np.uint8')
  if mask.dtype != np.uint8:
    raise ValueError('`mask` not of type np.uint8')
  if np.any(np.logical_and(mask != 1, mask != 0)):
    raise ValueError('`mask` elements should be in [0, 1]')
  if image.shape[:2] != mask.shape:
    raise ValueError('The image has spatial dimensions %s but the mask has '
                     'dimensions %s' % (image.shape[:2], mask.shape))
  rgb = ImageColor.getrgb(color)
  pil_image = Image.fromarray(image)

  solid_color = np.expand_dims(
      np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
  pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
  pil_mask = Image.fromarray(np.uint8(255.0*alpha*mask)).convert('L')
  pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
  np.copyto(image, np.array(pil_image.convert('RGB'))) 

def draw_mask_on_image_array(image, mask, color='red', alpha=0.4):
  """Draws mask on an image.

  Args:
    image: uint8 numpy array with shape (img_height, img_height, 3)
    mask: a uint8 numpy array of shape (img_height, img_height) with
      values between either 0 or 1.
    color: color to draw the keypoints with. Default is red.
    alpha: transparency value between 0 and 1. (default: 0.4)

  Raises:
    ValueError: On incorrect data type for image or masks.
  """
  if image.dtype != np.uint8:
    raise ValueError('`image` not of type np.uint8')
  if mask.dtype != np.uint8:
    raise ValueError('`mask` not of type np.uint8')
  if np.any(np.logical_and(mask != 1, mask != 0)):
    raise ValueError('`mask` elements should be in [0, 1]')
  if image.shape[:2] != mask.shape:
    raise ValueError('The image has spatial dimensions %s but the mask has '
                     'dimensions %s' % (image.shape[:2], mask.shape))
  rgb = ImageColor.getrgb(color)
  pil_image = Image.fromarray(image)

  solid_color = np.expand_dims(
      np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
  pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
  pil_mask = Image.fromarray(np.uint8(255.0*alpha*mask)).convert('L')
  pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
  np.copyto(image, np.array(pil_image.convert('RGB'))) 

def rotate(self):
        img1 = self.image.rotate(random.randint(-1, 1), expand=0)
        # 默认为0，表示剪裁掉伸到画板外面的部分
        img = Image.new('RGBA', img1.size, (255,) * 4)
        self.image = Image.composite(img1, img, img1) 

def do_composite(self):
        """usage: composite <image:pic1> <image:pic2> <image:mask>

        Replace two images and a mask with their composite.
        """
        image1 = self.do_pop()
        image2 = self.do_pop()
        mask = self.do_pop()
        self.push(Image.composite(image1, image2, mask)) 

def draw_mask_on_image_array(image, mask, color='red', alpha=0.7):
  """Draws mask on an image.

  Args:
    image: uint8 numpy array with shape (img_height, img_height, 3)
    mask: a uint8 numpy array of shape (img_height, img_height) with
      values between either 0 or 1.
    color: color to draw the keypoints with. Default is red.
    alpha: transparency value between 0 and 1. (default: 0.7)

  Raises:
    ValueError: On incorrect data type for image or masks.
  """
  if image.dtype != np.uint8:
    raise ValueError('`image` not of type np.uint8')
  if mask.dtype != np.uint8:
    raise ValueError('`mask` not of type np.uint8')
  if np.any(np.logical_and(mask != 1, mask != 0)):
    raise ValueError('`mask` elements should be in [0, 1]')
  rgb = ImageColor.getrgb(color)
  pil_image = Image.fromarray(image)

  solid_color = np.expand_dims(
      np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
  pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
  pil_mask = Image.fromarray(np.uint8(255.0*alpha*mask)).convert('L')
  pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
  np.copyto(image, np.array(pil_image.convert('RGB'))) 

def draw_mask_on_image_array(image, mask, color='red', alpha=0.4):
  """Draws mask on an image.

  Args:
    image: uint8 numpy array with shape (img_height, img_height, 3)
    mask: a uint8 numpy array of shape (img_height, img_height) with
      values between either 0 or 1.
    color: color to draw the keypoints with. Default is red.
    alpha: transparency value between 0 and 1. (default: 0.4)

  Raises:
    ValueError: On incorrect data type for image or masks.
  """
  if image.dtype != np.uint8:
    raise ValueError('`image` not of type np.uint8')
  if mask.dtype != np.uint8:
    raise ValueError('`mask` not of type np.uint8')
  if np.any(np.logical_and(mask != 1, mask != 0)):
    raise ValueError('`mask` elements should be in [0, 1]')
  if image.shape[:2] != mask.shape:
    raise ValueError('The image has spatial dimensions %s but the mask has '
                     'dimensions %s' % (image.shape[:2], mask.shape))
  rgb = ImageColor.getrgb(color)
  pil_image = Image.fromarray(image)

  solid_color = np.expand_dims(
      np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
  pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
  pil_mask = Image.fromarray(np.uint8(255.0*alpha*mask)).convert('L')
  pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
  np.copyto(image, np.array(pil_image.convert('RGB'))) 

def draw_mask_on_image_array(image, mask, color='red', alpha=0.7):
    """
    :param image: uint8 numpy array with shape (img_height, img_height, 3)
    :param mask: uint8 numpy array of shape (img_height, img_height) with values between either 0 or 1
    :param color: Color to draw the keypoints with
    :param alpha: Transparency value between 0 and 1
    """
    if image.dtype != np.uint8:
        raise ValueError('`image` not of type np.uint8')

    if mask.dtype != np.uint8:
        raise ValueError('`mask` not of type np.uint8')

    if np.any(np.logical_and(mask != 1, mask != 0)):
        raise ValueError('`mask` elements should be in [0, 1]')

    rgb = ImageColor.getrgb(color)
    pil_image = Image.fromarray(image)
    solid_color = np.expand_dims(np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
    pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
    pil_mask = Image.fromarray(np.uint8(255.0 * alpha * mask)).convert('L')
    pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
    np.copyto(image, np.array(pil_image.convert('RGB')))


# Method: Used to overlay labeled boxes on an image with formatted scores and label names 

def draw_mask_on_image_array(image, mask, color='red', alpha=0.4):
    """Draws mask on an image.

    Args:
      image: uint8 numpy array with shape (img_height, img_height, 3)
      mask: a uint8 numpy array of shape (img_height, img_height) with
        values between either 0 or 1.
      color: color to draw the keypoints with. Default is red.
      alpha: transparency value between 0 and 1. (default: 0.4)

    Raises:
      ValueError: On incorrect data type for image or masks.
    """
    if image.dtype != np.uint8:
        raise ValueError('`image` not of type np.uint8')
    if mask.dtype != np.uint8:
        raise ValueError('`mask` not of type np.uint8')
    if np.any(np.logical_and(mask != 1, mask != 0)):
        raise ValueError('`mask` elements should be in [0, 1]')
    if image.shape[:2] != mask.shape:
        raise ValueError('The image has spatial dimensions %s but the mask has '
                         'dimensions %s' % (image.shape[:2], mask.shape))
    rgb = ImageColor.getrgb(color)
    pil_image = Image.fromarray(image)

    solid_color = np.expand_dims(
        np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
    pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
    pil_mask = Image.fromarray(np.uint8(255.0*alpha*mask)).convert('L')
    pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
    np.copyto(image, np.array(pil_image.convert('RGB'))) 

def _rotate_img(self, img, degree):
        temp_img = img.convert("RGBA").rotate(degree, expand=True)
        empty_img = Image.new('RGBA', temp_img.size, "white")
        out_img = Image.composite(temp_img, empty_img, temp_img)
        return out_img 

def _rotate_img(self, img, degree):
        temp_img = img.convert("RGBA").rotate(degree, expand=True)
        empty_img = Image.new('RGBA', temp_img.size, "white")
        out_img = Image.composite(temp_img, empty_img, temp_img)
        return out_img 

def draw_mask_on_image_array(image, mask, color='red', alpha=0.7):
  """Draws mask on an image.

  Args:
    image: uint8 numpy array with shape (img_height, img_height, 3)
    mask: a float numpy array of shape (img_height, img_height) with
      values between 0 and 1
    color: color to draw the keypoints with. Default is red.
    alpha: transparency value between 0 and 1. (default: 0.7)

  Raises:
    ValueError: On incorrect data type for image or masks.
  """
  if image.dtype != np.uint8:
    raise ValueError('`image` not of type np.uint8')
  if mask.dtype != np.float32:
    raise ValueError('`mask` not of type np.float32')
  if np.any(np.logical_or(mask > 1.0, mask < 0.0)):
    raise ValueError('`mask` elements should be in [0, 1]')
  rgb = ImageColor.getrgb(color)
  pil_image = Image.fromarray(image)

  solid_color = np.expand_dims(
      np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
  pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
  pil_mask = Image.fromarray(np.uint8(255.0*alpha*mask)).convert('L')
  pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
  np.copyto(image, np.array(pil_image.convert('RGB'))) 

def draw_mask_on_image_array(image, mask, color='red', alpha=0.4):
  """Draws mask on an image.

  Args:
    image: uint8 numpy array with shape (img_height, img_height, 3)
    mask: a uint8 numpy array of shape (img_height, img_height) with
      values between either 0 or 1.
    color: color to draw the keypoints with. Default is red.
    alpha: transparency value between 0 and 1. (default: 0.4)

  Raises:
    ValueError: On incorrect data type for image or masks.
  """
  if image.dtype != np.uint8:
    raise ValueError('`image` not of type np.uint8')
  if mask.dtype != np.uint8:
    raise ValueError('`mask` not of type np.uint8')
  if np.any(np.logical_and(mask != 1, mask != 0)):
    raise ValueError('`mask` elements should be in [0, 1]')
  if image.shape[:2] != mask.shape:
    raise ValueError('The image has spatial dimensions %s but the mask has '
                     'dimensions %s' % (image.shape[:2], mask.shape))
  rgb = ImageColor.getrgb(color)
  pil_image = Image.fromarray(image)

  solid_color = np.expand_dims(
      np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
  pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
  pil_mask = Image.fromarray(np.uint8(255.0*alpha*mask)).convert('L')
  pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
  np.copyto(image, np.array(pil_image.convert('RGB'))) 

def draw_mask_on_image_array(image, mask, color='red', alpha=0.7):
  """Draws mask on an image.

  Args:
    image: uint8 numpy array with shape (img_height, img_height, 3)
    mask: a float numpy array of shape (img_height, img_height) with
      values between 0 and 1
    color: color to draw the keypoints with. Default is red.
    alpha: transparency value between 0 and 1. (default: 0.7)

  Raises:
    ValueError: On incorrect data type for image or masks.
  """
  if image.dtype != np.uint8:
    raise ValueError('`image` not of type np.uint8')
  if mask.dtype != np.float32:
    raise ValueError('`mask` not of type np.float32')
  if np.any(np.logical_or(mask > 1.0, mask < 0.0)):
    raise ValueError('`mask` elements should be in [0, 1]')
  rgb = ImageColor.getrgb(color)
  pil_image = Image.fromarray(image)

  solid_color = np.expand_dims(
      np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
  pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
  pil_mask = Image.fromarray(np.uint8(255.0*alpha*mask)).convert('L')
  pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
  np.copyto(image, np.array(pil_image.convert('RGB'))) 

def do_composite(self):
        """usage: composite <image:pic1> <image:pic2> <image:mask>

        Replace two images and a mask with their composite.
        """
        image1 = self.do_pop()
        image2 = self.do_pop()
        mask = self.do_pop()
        self.push(Image.composite(image1, image2, mask)) 

def draw_mask_on_image_array(image, mask, color='red', alpha=0.4):
    """Draws mask on an image.

    Args:
        image: uint8 numpy array with shape (img_height, img_height, 3)
        mask: a uint8 numpy array of shape (img_height, img_height) with
            values between either 0 or 1.
        color: color to draw the keypoints with. Default is red.
        alpha: transparency value between 0 and 1. (default: 0.4)

    Raises:
        ValueError: On incorrect data type for image or masks.
    """
    if image.dtype != np.uint8:
        raise ValueError('`image` not of type np.uint8')
    if mask.dtype != np.uint8:
        raise ValueError('`mask` not of type np.uint8')
    if np.any(np.logical_and(mask != 1, mask != 0)):
        raise ValueError('`mask` elements should be in [0, 1]')
    if image.shape[:2] != mask.shape:
        raise ValueError('The image has spatial dimensions %s but the mask has '
                                         'dimensions %s' % (image.shape[:2], mask.shape))
    rgb = ImageColor.getrgb(color)
    pil_image = Image.fromarray(image)

    solid_color = np.expand_dims(
            np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
    pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
    pil_mask = Image.fromarray(np.uint8(255.0*alpha*mask)).convert('L')
    pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
    np.copyto(image, np.array(pil_image.convert('RGB'))) 

def captcha_draw(label, fonts, dir_path, pic_id):
    # width, height = 512, 48
    # size_cha = random.randint(24, 48) # 字符大小
    # derx = random.randint(0, 16)
    # im = Image.new(mode='L', size=(width, height), color='white') # color 背景颜色，size 图片大小
    # drawer = ImageDraw.Draw(im)
    # font = ImageFont.truetype(random.choice(fonts), size_cha)
    # drawer.text(xy=(derx, 0), text=label, font=font, fill='black') #text 内容，font 字体（包括大小）
    # # im.show()
    # write2file(dir_path, label, im)

    width, height = 32, 32
    size_cha = random.randint(16, 28) # 字符大小
    derx = random.randint(0, max(width-size_cha-10, 0))
    dery = random.randint(0, max(height-size_cha-10, 0))
    im = Image.new(mode='L', size=(width, height), color='white') # color 背景颜色，size 图片大小
    drawer = ImageDraw.Draw(im)
    font = ImageFont.truetype(random.choice(fonts), size_cha)

    drawer.text(xy=(derx, dery), text=label, font=font, fill='black') #text 内容，font 字体（包括大小）
    # if label != ' ' and (img_as_float(im) == np.ones((48, 48))).all():
    #     # in case the label is not in this font, then the image will be all white
    #     return 0
    im = im.convert('RGBA')
    max_angle = 45 # to be tuned
    angle = random.randint(-max_angle, max_angle)
    im = im.rotate(angle, Image.BILINEAR, expand=0)
    fff = Image.new('RGBA', im.size, (255,)*4)
    im = Image.composite(im, fff, im)
    # if random.random() < 0.5:
    #     im = Image.fromarray(grey_erosion(im, size=(2, 2))) # erosion
    # if random.random() < 0.5:
    #     im = Image.fromarray((random_noise(img_as_float(im), mode='s&p')*255).astype(np.uint8))
    # im = im.filter(ImageFilter.GaussianBlur(radius=random.random()))
    # im.show()
    write2file(dir_path, label, im, pic_id)
    return 1 

def draw_mask_on_image_array(image, mask, color='red', alpha=0.7):
  """Draws mask on an image.

  Args:
    image: uint8 numpy array with shape (img_height, img_height, 3)
    mask: a float numpy array of shape (img_height, img_height) with
      values between 0 and 1
    color: color to draw the keypoints with. Default is red.
    alpha: transparency value between 0 and 1. (default: 0.7)

  Raises:
    ValueError: On incorrect data type for image or masks.
  """
  if image.dtype != np.uint8:
    raise ValueError('`image` not of type np.uint8')
  if mask.dtype != np.float32:
    raise ValueError('`mask` not of type np.float32')
  if np.any(np.logical_or(mask > 1.0, mask < 0.0)):
    raise ValueError('`mask` elements should be in [0, 1]')
  rgb = ImageColor.getrgb(color)
  pil_image = Image.fromarray(image)

  solid_color = np.expand_dims(
      np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
  pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
  pil_mask = Image.fromarray(np.uint8(255.0*alpha*mask)).convert('L')
  pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
  np.copyto(image, np.array(pil_image.convert('RGB'))) 

def draw_mask_on_image_array(image, mask, color='red', alpha=0.4):
  """Draws mask on an image.

  Args:
      image: uint8 numpy array with shape (img_height, img_height, 3)
      mask: a uint8 numpy array of shape (img_height, img_height) with
          values between either 0 or 1.
      color: color to draw the keypoints with. Default is red.
      alpha: transparency value between 0 and 1. (default: 0.4)

  Raises:
      ValueError: On incorrect data type for image or masks.
  """
  if image.dtype != np.uint8:
    raise ValueError('`image` not of type np.uint8')
  if mask.dtype != np.uint8:
    raise ValueError('`mask` not of type np.uint8')
  if np.any(np.logical_and(mask != 1, mask != 0)):
    raise ValueError('`mask` elements should be in [0, 1]')
  if image.shape[:2] != mask.shape:
    raise ValueError('The image has spatial dimensions %s but the mask has '
                     'dimensions %s' % (image.shape[:2], mask.shape))
  rgb = ImageColor.getrgb(color)
  pil_image = Image.fromarray(image)

  solid_color = np.expand_dims(
    np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
  pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
  pil_mask = Image.fromarray(np.uint8(255.0 * alpha * mask)).convert('L')
  pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
  np.copyto(image, np.array(pil_image.convert('RGB'))) 

def draw_mask_on_image_array(image, mask, color='red', alpha=0.4):
  """Draws mask on an image.

  Args:
    image: uint8 numpy array with shape (img_height, img_height, 3)
    mask: a uint8 numpy array of shape (img_height, img_height) with
      values between either 0 or 1.
    color: color to draw the keypoints with. Default is red.
    alpha: transparency value between 0 and 1. (default: 0.4)

  Raises:
    ValueError: On incorrect data type for image or masks.
  """
  if image.dtype != np.uint8:
    raise ValueError('`image` not of type np.uint8')
  if mask.dtype != np.uint8:
    raise ValueError('`mask` not of type np.uint8')
  if np.any(np.logical_and(mask != 1, mask != 0)):
    raise ValueError('`mask` elements should be in [0, 1]')
  if image.shape[:2] != mask.shape:
    raise ValueError('The image has spatial dimensions %s but the mask has '
                     'dimensions %s' % (image.shape[:2], mask.shape))
  rgb = ImageColor.getrgb(color)
  pil_image = Image.fromarray(image)

  solid_color = np.expand_dims(
      np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
  pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
  pil_mask = Image.fromarray(np.uint8(255.0*alpha*mask)).convert('L')
  pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
  np.copyto(image, np.array(pil_image.convert('RGB'))) 

def augment_background(img, mask, bg):
    return Image.composite(img, bg, mask) 

def augment_clothing(img, mask, texture):
    a = np.array(img)
    grey = a.mean(axis=-1)
    blackness = (255 - grey).clip(min=0) / 255

    texture = np.array(texture, dtype=np.float)
    texture -= blackness[..., np.newaxis] * texture
    texture = Image.fromarray(texture.round().astype(np.uint8))

    return Image.composite(texture, img, mask) 

def draw_mask_on_image_array(image, mask, color='red', alpha=0.4):
  """Draws mask on an image.

  Args:
    image: uint8 numpy array with shape (img_height, img_height, 3)
    mask: a uint8 numpy array of shape (img_height, img_height) with
      values between either 0 or 1.
    color: color to draw the keypoints with. Default is red.
    alpha: transparency value between 0 and 1. (default: 0.4)

  Raises:
    ValueError: On incorrect data type for image or masks.
  """
  if image.dtype != np.uint8:
    raise ValueError('`image` not of type np.uint8')
  if mask.dtype != np.uint8:
    raise ValueError('`mask` not of type np.uint8')
  if np.any(np.logical_and(mask != 1, mask != 0)):
    raise ValueError('`mask` elements should be in [0, 1]')
  if image.shape[:2] != mask.shape:
    raise ValueError('The image has spatial dimensions %s but the mask has '
                     'dimensions %s' % (image.shape[:2], mask.shape))
  rgb = ImageColor.getrgb(color)
  pil_image = Image.fromarray(image)

  solid_color = np.expand_dims(
      np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
  pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
  pil_mask = Image.fromarray(np.uint8(255.0*alpha*mask)).convert('L')
  pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
  np.copyto(image, np.array(pil_image.convert('RGB'))) 

def draw_mask_on_image_array(image, mask, color='red', alpha=0.4):
  """Draws mask on an image.

  Args:
    image: uint8 numpy array with shape (img_height, img_height, 3)
    mask: a uint8 numpy array of shape (img_height, img_height) with
      values between either 0 or 1.
    color: color to draw the keypoints with. Default is red.
    alpha: transparency value between 0 and 1. (default: 0.4)

  Raises:
    ValueError: On incorrect data type for image or masks.
  """
  if image.dtype != np.uint8:
    raise ValueError('`image` not of type np.uint8')
  if mask.dtype != np.uint8:
    raise ValueError('`mask` not of type np.uint8')
  if np.any(np.logical_and(mask != 1, mask != 0)):
    raise ValueError('`mask` elements should be in [0, 1]')
  if image.shape[:2] != mask.shape:
    raise ValueError('The image has spatial dimensions %s but the mask has '
                     'dimensions %s' % (image.shape[:2], mask.shape))
  rgb = ImageColor.getrgb(color)
  pil_image = Image.fromarray(image)

  solid_color = np.expand_dims(
      np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
  pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
  pil_mask = Image.fromarray(np.uint8(255.0*alpha*mask)).convert('L')
  pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
  np.copyto(image, np.array(pil_image.convert('RGB')))