56 lines
2.4 KiB
Python
56 lines
2.4 KiB
Python
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import cv2
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import yaml
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import numpy as np
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# 定义函数读取标定数据
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def read_calibration_data(calibration_file):
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with open(calibration_file, 'r') as f:
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calib_data = yaml.safe_load(f)
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cameraMatrix_l = np.array(calib_data['camera_matrix_left']['data']).reshape(3, 3)
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distCoeffs_l = np.array(calib_data['dist_coeff_left']['data'])
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cameraMatrix_r = np.array(calib_data['camera_matrix_right']['data']).reshape(3, 3)
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distCoeffs_r = np.array(calib_data['dist_coeff_right']['data'])
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R = np.array(calib_data['R']['data']).reshape(3, 3)
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T = np.array(calib_data['T']['data']).reshape(3, 1)
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return cameraMatrix_l, distCoeffs_l, cameraMatrix_r, distCoeffs_r, R, T
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# 定义函数对图像进行矫正
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def rectify_images(left_image_path, right_image_path, calibration_file):
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# 读取标定数据
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cameraMatrix_l, distCoeffs_l, cameraMatrix_r, distCoeffs_r, R, T = read_calibration_data(calibration_file)
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# 读取左右图像
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img_left = cv2.imread(left_image_path)
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img_right = cv2.imread(right_image_path)
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# 获取图像尺寸（假设左右图像尺寸相同）
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img_size = img_left.shape[:2][::-1]
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# 立体校正
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R1, R2, P1, P2, Q, roi1, roi2 = cv2.stereoRectify(cameraMatrix_l, distCoeffs_l,
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cameraMatrix_r, distCoeffs_r,
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img_size, R, T)
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# 计算映射参数
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map1_l, map2_l = cv2.initUndistortRectifyMap(cameraMatrix_l, distCoeffs_l, R1, P1, img_size, cv2.CV_32FC1)
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map1_r, map2_r = cv2.initUndistortRectifyMap(cameraMatrix_r, distCoeffs_r, R2, P2, img_size, cv2.CV_32FC1)
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# 应用映射并显示结果
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rectified_img_l = cv2.remap(img_left, map1_l, map2_l, cv2.INTER_LINEAR)
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rectified_img_r = cv2.remap(img_right, map1_r, map2_r, cv2.INTER_LINEAR)
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# 合并图像显示
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combined_img = np.hstack((rectified_img_l, rectified_img_r))
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cv2.imshow('Rectified Images', combined_img)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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# 设置路径和文件名
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left_image_path = "left/left_WIN_20241023_14_54_55_Pro.jpg"
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right_image_path = "right/right_WIN_20241023_14_54_55_Pro.jpg"
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calibration_file = "calibration_parameters.yaml"
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# 调用函数进行图像矫正
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rectify_images(left_image_path, right_image_path, calibration_file)
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