利用opencv以及easygui实现的简易的视觉系统（一）彩色灰度化 彩色直方图灰色图像的伪彩色图像

import numpy as np from matplotlib import pyplot as plt import torch import cv2 as cv import easygui as g import sys def winname(name): return name.encode('gbk').decode(errors='ignore') def fake_color_image(image_gray): r = 0 g=0 b=0 height = image_gray.shape[0] weight = image_gray.shape[1] out_color_image = np.zeros((height,weight,3),np.uint8) for i in range(height): for j in range(weight): val = image_gray[i,j] if (val <128): r = 0 elif (val <192): r=255/64*(val-128) else: r = 255 if (val < 64): g = 255 / 64 * val elif (val < 192): g = 255 else: g = -255 / 63 * (val - 192) + 255 if (val < 64): b = 255 elif (val < 128): b = -255 / 63 * (val - 192) + 255 else: b = 0 out_color_image[i,j,0] = b out_color_image[i,j,1] = g out_color_image[i,j,2] = r cv.imshow("fake color image",out_color_image) def image_gray1(img_gray): img_gray1 = img_gray.copy() width = img_gray1.shape[1] height = img_gray1.shape[0] for i in range(height): for j in range(width): img_gray1[i,j]= (int(img_gray[i,j, 0]) + int(img_gray[i,j, 1]) + int(img_gray[i,j, 2]))/ 3 #强行int类型，实现了灰度化 # img_gray1 = (img_gray[:, :, 0] + img_gray[:, :, 1] + img_gray[:, :, 2]) / 3 # 第一种方式为对各个通道求均值 img_gray1 = img_gray1.astype(np.uint8) # 猪油数组类型为unit类型时，才会认为是一张图片 cv.imshow("gray image 1",img_gray1) cv.waitKey(1000) def image_gray2(img_gray): img_gray2 = img_gray.copy() img_gray2 = img_gray[:, :, 0] * 0.11 + img_gray[:, :, 1] * 0.59 + img_gray[:, :, 2] * 0.3 img_gray2 = img_gray2.astype(np.uint8) # GRAY=0.3*R+0.59*G+0.11*B： cv.imshow("gray image 2",img_gray2) cv.waitKey(10) plt.rcParams['font.sans-serif']=['SimHei'] # 用黑体显示中文 plt.rcParams['axes.unicode_minus']=False # 正常显示负号 a='' filename = '' img = np.ones((3,3),dtype=np.uint8) msg="请输入您想要完成的任务（建议您第一步先打开图片）" title='第一次作业' choice=('打开图片','退出') a=g.buttonbox(msg=msg,title=title,choices=choice) if a == '打开图片': filename = g.fileopenbox(msg="请打开一个jpg文件") img = cv.imread(filename) msg1 = "选择您想要实现的功能" title1 = '第一次作业' choice1 = ('灰度化1', '灰度化2', '伪彩色', '直方图', '显示图片', '退出') q=1 while q: b=g.buttonbox(msg=msg1,title=title1,choices=choice1) #while b!='退出': if b == '灰度化1': image_gray1(img) elif b == '灰度化2': image_gray2(img) elif b == '显示图片': cv.imshow("original image", img) cv.waitKey(1000) elif b == '伪彩色': img_gray = img[:, :, 0] * 0.11 + img[:, :, 1] * 0.59 + img[:, :, 2] * 0.3 img_gray = img_gray.astype(np.uint8) #GRAY=0.3*R+0.59*G+0.11*B： fake_color_image(img_gray) #显示伪彩色图 elif b == '直方图': img_gray = img[:, :, 0] * 0.11 + img[:, :, 1] * 0.59 + img[:, :, 2] * 0.3 img_gray = img_gray.astype(np.uint8) pix = [] height = img_gray.shape[0] weight = img_gray.shape[1] for i in range(height): for j in range(weight): pix.append(int(img_gray[i,j])) pix1=[] for i in range(256): number = pix.count(i) pix1.append(number) # pix = np.array(pix) pix1 = np.array(pix1) # data:必选参数，绘图数据 # bins:直方图的长条形数目，可选项，默认为10 # normed:是否将得到的直方图向量归一化，可选项，默认为0，代表不归一化，显示频数。normed=1，表示归一化，显示频率。 # facecolor:长条形的颜色 # edgecolor:长条形边框的颜色 # alpha:透明度 # plt.hist(pix,bins=256,range=[0,255]) #绘制直方图（第二种方式的） plt.plot(pix1) #利用plot直接根据每个像素点的个数直接绘制直方图 plt.xlabel( " gray number " ) plt.ylabel( " number " ) plt.title("灰度直方图") plt.show() else: q=0 cv.waitKey(0)