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import cv2 |
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import numpy as np |
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from PIL import Image |
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import math |
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import numpy as np |
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def rotate_image(image, angle, center = None, scale = 1.0): |
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(h, w) = image.shape[:2] |
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if center is None: |
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center = (w / 2, h / 2) |
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M = cv2.getRotationMatrix2D(center, angle, scale) |
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rotated = cv2.warpAffine(image, M, (w, h)) |
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return rotated |
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class watermark_image: |
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def __init__(self, logo_path, size=0.3, oritation="DR", margin=(5,20,20,20), angle=15, rgb_weight=(0,1,1.5), input_frame_shape=None) -> None: |
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logo_image = cv2.imread(logo_path, cv2.IMREAD_UNCHANGED) |
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h,w,c = logo_image.shape |
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if angle%360 != 0: |
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new_h = w*math.sin(angle/180*math.pi) + h*math.cos(angle/180*math.pi) |
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pad_h = int((new_h-h)//2) |
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padding = np.zeros((pad_h, w, c), dtype=np.uint8) |
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logo_image = cv2.vconcat([logo_image, padding]) |
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logo_image = cv2.vconcat([padding, logo_image]) |
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logo_image = rotate_image(logo_image, angle) |
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print(logo_image.shape) |
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self.logo_image = logo_image |
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if self.logo_image.shape[2] < 4: |
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print("No alpha channel found!") |
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self.logo_image = self.__addAlpha__(self.logo_image) |
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self.size = size |
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self.oritation = oritation |
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self.margin = margin |
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self.ori_shape = self.logo_image.shape |
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self.resized = False |
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self.rgb_weight = rgb_weight |
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self.logo_image[:, :, 2] = self.logo_image[:, :, 2]*self.rgb_weight[0] |
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self.logo_image[:, :, 1] = self.logo_image[:, :, 1]*self.rgb_weight[1] |
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self.logo_image[:, :, 0] = self.logo_image[:, :, 0]*self.rgb_weight[2] |
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if input_frame_shape is not None: |
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logo_w = input_frame_shape[1] * self.size |
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ratio = logo_w / self.ori_shape[1] |
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logo_h = int(ratio * self.ori_shape[0]) |
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logo_w = int(logo_w) |
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size = (logo_w, logo_h) |
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self.logo_image = cv2.resize(self.logo_image, size, interpolation = cv2.INTER_CUBIC) |
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self.resized = True |
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if oritation == "UL": |
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self.coor_h = self.margin[1] |
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self.coor_w = self.margin[0] |
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elif oritation == "UR": |
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self.coor_h = self.margin[1] |
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self.coor_w = input_frame_shape[1] - (logo_w + self.margin[2]) |
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elif oritation == "DL": |
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self.coor_h = input_frame_shape[0] - (logo_h + self.margin[1]) |
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self.coor_w = self.margin[0] |
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else: |
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self.coor_h = input_frame_shape[0] - (logo_h + self.margin[3]) |
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self.coor_w = input_frame_shape[1] - (logo_w + self.margin[2]) |
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self.logo_w = logo_w |
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self.logo_h = logo_h |
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self.mask = self.logo_image[:,:,3] |
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self.mask = cv2.bitwise_not(self.mask//255) |
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def apply_frames(self, frame): |
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if not self.resized: |
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shape = frame.shape |
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logo_w = shape[1] * self.size |
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ratio = logo_w / self.ori_shape[1] |
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logo_h = int(ratio * self.ori_shape[0]) |
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logo_w = int(logo_w) |
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size = (logo_w, logo_h) |
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self.logo_image = cv2.resize(self.logo_image, size, interpolation = cv2.INTER_CUBIC) |
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self.resized = True |
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if self.oritation == "UL": |
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self.coor_h = self.margin[1] |
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self.coor_w = self.margin[0] |
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elif self.oritation == "UR": |
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self.coor_h = self.margin[1] |
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self.coor_w = shape[1] - (logo_w + self.margin[2]) |
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elif self.oritation == "DL": |
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self.coor_h = shape[0] - (logo_h + self.margin[1]) |
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self.coor_w = self.margin[0] |
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else: |
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self.coor_h = shape[0] - (logo_h + self.margin[3]) |
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self.coor_w = shape[1] - (logo_w + self.margin[2]) |
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self.logo_w = logo_w |
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self.logo_h = logo_h |
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self.mask = self.logo_image[:,:,3] |
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self.mask = cv2.bitwise_not(self.mask//255) |
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original_frame = frame[self.coor_h:(self.coor_h+self.logo_h), self.coor_w:(self.coor_w+self.logo_w),:] |
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blending_logo = cv2.add(self.logo_image[:,:,0:3],original_frame,mask = self.mask) |
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frame[self.coor_h:(self.coor_h+self.logo_h), self.coor_w:(self.coor_w+self.logo_w),:] = blending_logo |
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return frame |
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def __addAlpha__(self, image): |
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shape = image.shape |
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alpha_channel = np.ones((shape[0],shape[1],1),np.uint8)*255 |
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return np.concatenate((image,alpha_channel),2) |
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