我们从Python开源项目中，提取了以下12个代码示例，用于说明如何使用cv2.randn()。
def augment_image(rgbImg): augmented_images = [] # original image augmented_images.append(rgbImg) # fliped x-axis rimg = rgbImg.copy() cv2.flip(rimg, 1, rimg) augmented_images.append(rimg) # add gaussian noise for _ in range(10): gaussian_noise = rgbImg.copy() cv2.randn(gaussian_noise, 0, 150) augmented_images.append(rgbImg + gaussian_noise) augmented_images.append(rimg + gaussian_noise) for _ in range(10): uniform_noise = rgbImg.copy() cv2.randu(uniform_noise, 0, 1) augmented_images.append(rgbImg + uniform_noise) augmented_images.append(rimg + uniform_noise) return augmented_images
def read(self, dst=None): w, h = self.frame_size if self.bg is None: buf = np.zeros((h, w, 3), np.uint8) else: buf = self.bg.copy() self.render(buf) if self.noise > 0.0: noise = np.zeros((h, w, 3), np.int8) cv2.randn(noise, np.zeros(3), np.ones(3)*255*self.noise) buf = cv2.add(buf, noise, dtype=cv2.CV_8UC3) return True, buf
def applyNoise(self, gaussian): # clone HSV channels first from copy import deepcopy self.n_h = deepcopy(self.h) self.n_s = deepcopy(self.s) self.n_v = deepcopy(self.v) mean, var = gaussian.get('mean'), gaussian.get('var') cv2.randn(self.n_h, mean, var) cv2.randn(self.n_s, mean, var) cv2.randn(self.n_v, mean, var)
def read(self, dst=None): noise = np.zeros(self.render.sceneBg.shape, np.int8) cv2.randn(noise, np.zeros(3), np.ones(3)*255*self.noise) return True, cv2.add(self.render.getNextFrame(), noise, dtype=cv2.CV_8UC3)
