结果如上,因为图像是使用matplotlib显示,matplotlib的彩色图像是RGB排列顺序,与OpenCV读入图像的BGR不同,因此图像颜色会有所不同。
importcv2defgray_to_rgb(image_path):# 读取灰度图像gray_image=cv2.imread(image_path,cv2.IMREAD_GRAYSCALE)# 将灰度图像转换为RGB图像rgb_image=cv2.cvtColor(gray_image,cv2.COLOR_GRAY2RGB)# 显示图像cv2.imshow("Gray Image",gray_image)cv2.imshow("RGB Image",rgb_image)cv2.waitKey(0)cv2.destroyA...
22if($rgbarray['red'] < 125 ||$rgbarray['green'] < 125 ||23$rgbarray['blue'] < 12524) {25$data[$i][$j] = 1;26}else{27$data[$i][$j] = 0;28}2930}31}
RGB就是指Red,Green和Blue,一副图像由这三个channel(通道)构成 Gray就是只有灰度值一个channel HSV即Hue(色调),Saturation(饱和度)和Value(亮度)三个channel RGB是为了让机器更好的显示图像,对于人类来说并不直观,HSV更为贴近我们的认知,所以通常我们在针对某种颜色做提取时会转换到HSV颜色空间里面来处理. 需要注...
小小杨树IP属地: 云南 0.1782022.01.15 09:58:01字数 0阅读 431 importcv2 img=cv2.imread('test.jpg')gray=cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)hsv=cv2.cvtColor(img,cv2.COLOR_BGR2HSV)defmouse_click(event,x,y,flags,para):ifevent==cv2.EVENT_LBUTTONDOWN:# 左边鼠标点击print('PIX:',x,y)print...
Python Optimizing RGB to Grayscale, Gaussian Blur and Sobel-Filter operations on FPGAs for reduced dynamic power consumption fpgaimage-processinggaussian-blursobel-filterrgb-grayscale UpdatedAug 6, 2024 Verilog Improve this page Add a description, image, and links to thergb-grayscaletopic page so ...
根据一定的权重计算公式,将RGB值转换为灰度值。常用的计算公式是:Gray = 0.299 * R + 0.587 * G + 0.114 * B。 将计算得到的灰度值赋给对应的像素位置,形成灰度图像。 BGR2GRAY函数的优势在于能够将彩色图像转换为灰度图像,简化了图像处理的复杂度。灰度图像通常比彩色图像占用更少的存储空间,且在某...
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import matplotlib.pyplot as plt import cv2 sample = r'G:\Python\knight-mare\screenshots\2020-07-12-02-40-44.jpg' img_read_as_grayscale = cv2.imread(sample, cv2.IMREAD_GRAYSCALE) img_read_as_color = cv2.imread(sample, cv2.IMREAD_COLOR) img_RGB_to_grayscale = cv2.cvtColor(img_read_...
def gray_world(rgb_image): """ adapt gray word assumption to rgb image """ new_rgb_image = np.zeros(shape=rgb_image.shape, dtype=np.float32) # 计算三个通道的平均灰度值的平均值 ave_r = np.average(rgb_image[:, :, 0])