写一段python代码将图像中最大的缺陷边缘进行用矩形框起来
时间: 2023-03-13 20:11:08 浏览: 49
import cv2
img = cv2.imread("image.jpg")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (3, 3), 0)
edges = cv2.Canny(gray, 50, 150, apertureSize = 3)
minLineLength = 100
maxLineGap = 10
lines = cv2.HoughLinesP(edges, 1, np.pi / 180, 100, minLineLength, maxLineGap)
for x1, y1, x2, y2 in lines[0]:
cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 0), 2)
cv2.imshow("Edges", edges)
cv2.imshow("Image", img)
cv2.waitKey(0)
相关问题
写一段python代码将图像中所有缺陷边缘进行用矩形框起来
# 导入所需的模块
import cv2
import numpy as np # 读取图像
img = cv2.imread('image.jpg') # 转换为灰度图像
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) # 检测边缘
edges = cv2.Canny(gray,50,150,apertureSize = 3) # 检测缺陷边缘
lines = cv2.HoughLines(edges,1,np.pi/180,200) # 遍历检测到的缺陷边缘
for line in lines:
for rho,theta in line:
a = np.cos(theta)
b = np.sin(theta)
x0 = a*rho
y0 = b*rho
x1 = int(x0 + 1000*(-b))
y1 = int(y0 + 1000*(a))
x2 = int(x0 - 1000*(-b))
y2 = int(y0 - 1000*(a))
# 用矩形框起来
cv2.rectangle(img,(x1,y1),(x2,y2),(0,255,0),2) # 显示结果
cv2.imshow('Result Image',img)
cv2.waitKey(0)
用python写一段提取图像主体部分的代码
好的,以下是Python代码示例来提取图像主体部分:
```python
import cv2
# 读取图片
img = cv2.imread('your_image.jpg')
# 转换为灰度图像
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# 进行二值化
_, thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)
# 获取边缘
contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnt = max(contours, key=cv2.contourArea)
# 获取矩形框坐标
x, y, w, h = cv2.boundingRect(cnt)
# 裁剪图像
crop = img[y:y + h, x:x + w]
# 显示结果
cv2.imshow('crop', crop)
cv2.waitKey(0)
cv2.destroyAllWindows()
```
这段代码使用 OpenCV 库来提取图像主体部分。它将图像转换为灰度图像,进行二值化,并查找图像中的轮廓。接着,它找到面积最大的轮廓,并从中提取矩形框坐标。最后,它对原始图像进行裁剪,只保留主体部分,并将结果显示出来。
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