import cv2
import numpy as np
from numpy import mean
# 读取图像以及图像的宽和高
img = cv2.imread('./img.png')
h = img.shape[0]
w = img.shape[1]
# 求取图像的平均灰度值
img_gray = cv2.cvtColor(img, cv2.COLOR_RGBA2GRAY)
all_gray = []
for i in range(h):
for j in range(w):
all_gray.append(img_gray[i, j])
print('图像的平均灰度值：', mean(all_gray))
# Canny算子寻找图像的边缘
image_edge = cv2.Canny(img, 200, 200)
# 寻找霍夫直线
lines = cv2.HoughLines(image_edge, 1, np.pi/180, 180)
# 绘画霍夫直线
if lines is not None:
for n, line in enumerate(lines):
# 沿着左上角的原点，作目标直线的垂线得到长度和角度
rho = line[0][0]
theta = line[0][1]
# if np.pi / 3 < theta < np.pi * (3 / 4):
a = np.cos(theta)
b = np.sin(theta)
# 得到目标直线上的点
x0 = a * rho
y0 = b * rho
# 延长直线的长度
x1 = int(x0 + 2000 * (-b))
y1 = int(y0 + 2000 * (a))
x2 = int(x0 - 2000 * (-b))
y2 = int(y0 - 2000 * (a))
# 连接两点画直线
# print((x1, y1), (x2, y2)) # (-148, 993) (335, -947)
cv2.line(img, (x1, y1), (x2, y2), (0, 0, 255), 1)
# ===============================CAB================================ #
xDis = x2 - x1 # x的增量
yDis = y2 - y1 # y的增量
if (abs(xDis) > abs(yDis)):
maxstep = abs(xDis)
else:
maxstep = abs(yDis)
xUnitstep = xDis / maxstep # x每步骤增量
yUnitstep = yDis / maxstep # y的每步增量
x = x1
y = y1
average_gray = []
for k in range(maxstep):
x = x + xUnitstep
y = y + yUnitstep
# print("x: %d, y:%d" % (x, y))
if 0 < x < h and 0 < y < w:
# print(img_gray[int(x), int(y)])
average_gray.append(img[int(x), int(y)])
print('第{}霍夫直线的平均灰度值：'.format(n), mean(average_gray)) # 平均115，阴影的边界在125以上，堵料的边界在105左右
# ================================================================== #
print('直线的数量：', len(lines))
else:
print('直线的数量：', 0)
# 可视化图像
cv2.imshow('0', img)
cv2.imshow('1', image_edge)
cv2.waitKey(0)
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