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