灰度二值化图识别和处理python代码

import numpy as np from PIL import Image import pandas as pd def coordinates_left(img, img_array, Value): cols, rows = img.size for y in range(cols - 1, -1, -1): for x in range(rows - 1, -1, -1): Value[x][y] = img_array[x, y] # 存入数组 if Value[x][y] == 0: L = (x-7) * 180 * 5 return x, y, L def coordinates_up(img, img_array, Value): cols, rows = img.size for x in range(0, rows): for y in range(0, cols): Value[x][y] = img_array[x, y] # 存入数组 if Value[x][y] == 0: L = (x-7) * 180 * 5 return x, y, L def test(i): img = Image.open('G:\\pythonProject1\\二值化图像\\'+ str(i) + '.jpg') # 读取图片 img = img.convert('L') # 灰度化 cols, rows = img.size # 图像大小 print('rows, cols:', rows, cols) Value = [[255] * cols for i in range(rows)] # 创建一个大小与图片相同的二维数组 # print('Value:', Value) img_array = np.array(img) # print(img_array) x1, y1, L1 = coordinates_left(img, img_array, Value) print('（从右往左）输出像素坐标x,y:[', x1, y1, ']') print('输出长度为:', L1, '厘米') x2, y2, L2 = coordinates_up(img, img_array, Value) print('（从上往下）输出像素坐标x,y:[', x2, y2, ']') print('输出长度为:', L2, '厘米') return x1, y1, L1, x2, y2, L2 if __name__ == '__main__': output = [] for i in range(225): x1, y1, L1, x2, y2, L2 = test(i) output.append([x1, y1, L1, x2, y2, L2]) # print('output:', output) output_new = pd.DataFrame(output) print('output:', output_new) # 6个数字，从左往右依次是（从右往左）坐标1、坐标1、长度1，（从上往下）坐标2、坐标2、长度2 output_new.to_csv("灰度判断结果.csv", encoding="utf_8_sig")