用opencv量角器的代码
时间: 2023-08-31 18:44:05 浏览: 156
基于opencv的角点坐标代码 直接可以用
### 回答1:
以下是使用OpenCV实现量角器的Python代码:
```python
import cv2
import numpy as np
# Load image and convert it to grayscale
img = cv2.imread("sample.jpg")
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Apply thresholding to create binary image
ret, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY_INV)
# Find contours in the binary image
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# Sort contours by area in descending order
contours = sorted(contours, key=cv2.contourArea, reverse=True)
# Select the largest contour (which should be the outline of the angle)
angle_contour = contours[0]
# Fit a line to the angle contour
rows, cols = img.shape[:2]
[vx, vy, x, y] = cv2.fitLine(angle_contour, cv2.DIST_L2, 0, 0.01, 0.01)
lefty = int((-x * vy / vx) + y)
righty = int(((cols - x) * vy / vx) + y)
# Draw the line on the image
cv2.line(img, (cols-1, righty), (0, lefty), (0, 255, 0), 2)
# Compute the angle of the line
angle = np.arctan2(righty - lefty, cols - 1) * 180 / np.pi
# Display the image and angle measurement
cv2.imshow("Image", img)
print("Angle: ", angle)
cv2.waitKey(0)
cv2.destroyAllWindows()
```
在这个代码中,我们首先加载图像并将其转换为灰度图像,然后应用二值化以创建二进制图像。接下来,我们找到二进制图像中的轮廓,并按面积降序排序。然后选择最大的轮廓(即角的轮廓),并将其拟合为一条线。我们根据线的起点和终点计算出线的角度,并在原始图像上绘制该线。最后,我们计算并输出线的角度。
### 回答2:
使用OpenCV实现量角器功能的代码如下:
```python
import cv2
import numpy as np
def measure_angle(image, point1, point2, point3):
# 绘制角度的辅助线段
cv2.line(image, point1, point2, (0, 255, 0), 2) # 第一条辅助线段
cv2.line(image, point2, point3, (0, 255, 0), 2) # 第二条辅助线段
# 计算两条辅助线段的向量
vector1 = np.array(point1) - np.array(point2)
vector2 = np.array(point3) - np.array(point2)
# 根据向量的点乘和模长计算角度
cos_angle = np.dot(vector1, vector2) / (np.linalg.norm(vector1) * np.linalg.norm(vector2))
angle = np.arccos(cos_angle)
angle = np.degrees(angle)
# 在图像上显示角度值
cv2.putText(image, f"Angle: {angle:.1f}", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
# 返回角度值
return angle
# 读取图像
image = cv2.imread("image.jpg")
# 设置辅助点坐标
point1 = (100, 100)
point2 = (200, 200)
point3 = (300, 100)
# 调用函数测量角度并绘制结果
angle = measure_angle(image, point1, point2, point3)
# 显示图像
cv2.imshow("Image", image)
cv2.waitKey(0)
cv2.destroyAllWindows()
```
通过该代码,可以在图像上绘制两条辅助线段,并计算两条辅助线段之间的夹角。同时,在图像上显示出测量得到的角度值。你只需要根据实际情况,将辅助点的坐标进行设定即可。
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