OpenCV图像距离检测
代码实现：
import cv2
import numpy as np
def calculate_distance(p1, p2, focal_length, known_width):
"""
计算两点之间的实际距离
:param p1: 点1坐标
:param p2: 点2坐标
:param focal_length: 相机焦距
:param known_width: 已知物体的实际宽度
:return: 两点之间的实际距离
"""
# 计算像素距离
pixel_distance = np.linalg.norm(np.array(p1) - np.array(p2))
# 计算实际距离
distance = (known_width * focal_length) / pixel_distance
return distance
def detect_distance(image_path, focal_length, known_width):
"""
检测图像中物体之间的距离
:param image_path: 图像路径
:param focal_length: 相机焦距
:param known_width: 已知物体的实际宽度
"""
# 读取图像
image = cv2.imread(image_path)
if image is None:
print("无法读取图像")
return
# 创建窗口
cv2.namedWindow("Distance Detection")
points = []
def mouse_callback(event, x, y, flags, param):
if event == cv2.EVENT_LBUTTONDOWN:
if len(points) < 2:
points.append((x, y))
cv2.circle(image, (x, y), 5, (0, 255, 0), -1)
if len(points) == 2:
# 计算距离
distance = calculate_distance(points[0], points[1], focal_length, known_width)
cv2.line(image, points[0], points[1], (255, 0, 0), 2)
cv2.putText(image, f"Distance: {distance:.2f} cm",
(10, 30), cv2.FONT_HERSHEY_SIMPLEX,
1, (0, 0, 255), 2)
cv2.imshow("Distance Detection", image)
cv2.setMouseCallback("Distance Detection", mouse_callback)
while True:
cv2.imshow("Distance Detection", image)
key = cv2.waitKey(1) & 0xFF
if key == ord('q') or key == 27: # 按q或ESC退出
break
cv2.destroyAllWindows()
if __name__ == "__main__":
# 示例参数
image_path = "example.jpg" # 替换为实际图像路径
focal_length = 1000 # 相机焦距（需要根据实际情况调整）
known_width = 10 # 已知物体的实际宽度（单位：厘米）
detect_distance(image_path, focal_length, known_width)