标定+USB摄像头启动

标定.py

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+import cv2
+import numpy as np
+import glob
+
+# 图片储存的路径
+img_path = "/home/sunrise/yiliao_ws/imagebag_outputs"
+
+# 棋盘格参数
+CHECKERBOARD = (8, 5)  # 内角点数量（列×行）
+square_size = 27  # 棋盘格方块实际尺寸（单位：毫米）
+
+# 存储3D和2D点
+objpoints = []  # 世界坐标系中的点
+imgpoints = []  # 图像坐标系中的点
+
+# 生成世界坐标系中的角点坐标（z=0）
+objp = np.zeros((CHECKERBOARD[0]*CHECKERBOARD[1], 3), np.float32)
+objp[:, :2] = np.mgrid[0:CHECKERBOARD[0], 0:CHECKERBOARD[1]].T.reshape(-1, 2) * square_size
+
+
+# 读取所有棋盘格图片
+images = glob.glob(f'{img_path}/*.png')
+
+for fname in images:
+    img = cv2.imread(fname)
+    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+
+    # 检测角点
+    ret, corners = cv2.findChessboardCorners(gray, CHECKERBOARD, None)
+
+    if ret:
+        objpoints.append(objp)
+
+        # 亚像素角点优化
+        criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
+        corners2 = cv2.cornerSubPix(gray, corners, (11,11), (-1,-1), criteria)
+        imgpoints.append(corners2)
+
+        # 绘制角点（可选）
+        # cv2.drawChessboardCorners(img, CHECKERBOARD, corners2, ret)
+        # cv2.imshow('Detected Corners', img)
+        # cv2.waitKey(500)
+
+# cv2.destroyAllWindows()
+
+# 相机标定
+ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(
+    objpoints, imgpoints, gray.shape[::-1], None, None
+)
+
+# 输出标定结果
+print("相机内参矩阵:\n", mtx)
+print("\n畸变系数:", dist.ravel())
+
+# 计算重投影误差
+mean_error = 0
+for i in range(len(objpoints)):
+    imgpoints2, _ = cv2.projectPoints(objpoints[i], rvecs[i], tvecs[i], mtx, dist)
+    error = cv2.norm(imgpoints[i], imgpoints2, cv2.NORM_L2) / len(imgpoints2)
+    mean_error += error
+print("\n平均重投影误差:", mean_error / len(objpoints))
+
+# 保存参数
+np.savez('cali.npz', mtx=mtx, dist=dist)
+
+
+# 测试校正效果
+img = cv2.imread(fname)  # 替换为实际的图片路径
+# ret, img = cap.read()
+h, w = img.shape[:2]
+newcameramtx, roi = cv2.getOptimalNewCameraMatrix(mtx, dist, (w,h), 1, (w,h))
+