diff --git a/calibrate_intri.py b/calibrate_intri.py index 974c962..320506a 100644 --- a/calibrate_intri.py +++ b/calibrate_intri.py @@ -4,19 +4,49 @@ import glob import cv2 as cv import numpy as np import json +import datetime import argparse -def calibrate_camera(imgFolder, chessboardSize, squareSize): +def format_json_data(mtx, dist, image_shape): + data = { + "time": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"), + "K": mtx.tolist(), + "dist": dist.tolist(), + "image_shape": image_shape + } + return data + + +def write_json(data, output_path): + with open(output_path, "w") as f: + json.dump(data, f, indent=4) + + +def read_json(input): + with open(input, "r") as f: + data = json.load(f) + return data + +def read_img_paths(imgFolder): + imgPaths = [] + for extension in ["jpg", "png", "jpeg", "bmp"]: + imgPaths += glob.glob(osp.join(imgFolder, "*.{}".format(extension))) + return imgPaths + +def create_output_folder(baseFolder, outputFolder): + folder = osp.join(baseFolder, outputFolder) + if not osp.exists(folder): + os.makedirs(folder) + return folder + +def calibrate_camera(baseFolder, chessboardSize, squareSize, visualization): # 设置输出目录 - outputFolder = osp.join(imgFolder, "output") - if not osp.exists(outputFolder): - os.makedirs(outputFolder) + if visualization: + outputFolder = create_output_folder(baseFolder, "calibrateOutputImages") # 图片路径 - imgPaths = [] - for extension in ["jpg", "png", "jpeg"]: - imgPaths += glob.glob(osp.join(imgFolder, "*.{}".format(extension))) + imgPaths = read_img_paths(baseFolder) if len(imgPaths) == 0: print("No images found!") return @@ -42,12 +72,13 @@ def calibrate_camera(imgFolder, chessboardSize, squareSize): (cv.TERM_CRITERIA_EPS + cv.TERM_CRITERIA_MAX_ITER, 30, 0.001)) pointsWorld.append(board_grid) pointsPixel.append(corners) - - cv.drawChessboardCorners(img, (board_w, board_h), corners, ret) - cv.imwrite(osp.join(outputFolder, osp.basename(imgPath)), img) + if visualization: + cv.drawChessboardCorners(img, (board_w, board_h), corners, ret) + cv.imwrite(osp.join(outputFolder, osp.basename(imgPath)), img) # 标定相机 - ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera(pointsWorld, pointsPixel, gray.shape[::-1], None, None) + image_shape = gray.shape[::-1] + ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera(pointsWorld, pointsPixel, image_shape, None, None) print("Intrinsic matrix:\n", mtx.astype(np.float32)) print("Distortion coefficients:\n", dist.astype(np.float32)) @@ -59,27 +90,49 @@ def calibrate_camera(imgFolder, chessboardSize, squareSize): error = cv.norm(pointsPixel[i], imgpoints2, cv.NORM_L2) / len(imgpoints2) img_error[i] = error - good_img = np.where(img_error < 0.5)[0] - mean_error = np.mean(img_error[good_img]) - print("Reprojection error: ", mean_error) + # good_img = np.where(img_error < 0.5)[0] + # mean_error = np.mean(img_error[good_img]) + mean_error = np.mean(img_error) + print("\nReprojection error: ", mean_error) # 挑选出重投影误差小于1.0的图片，重新标定相机 - if len(good_img) == 0: - print("No images with error < 0.5") - elif len(good_img) == nimg: - print("All images have error < 0.5") - pass - else: - pointsWorld2 = [pointsWorld[i] for i in good_img] - pointsPixel2 = [pointsPixel[i] for i in good_img] - ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera(pointsWorld2, pointsPixel2, gray.shape[::-1], None, None) - print("Intrinsic matrix:\n", mtx.astype(np.float32)) - print("Distortion coefficients:\n", dist.astype(np.float32)) + # if len(good_img) == 0: + # print("No images with error < 0.5") + # elif len(good_img) == nimg: + # print("All images have error < 0.5") + # pass + # else: + # pointsWorld2 = [pointsWorld[i] for i in good_img] + # pointsPixel2 = [pointsPixel[i] for i in good_img] + # ret, mtx, dist, rvecs, tvecs = cv.calibrateCamera(pointsWorld2, pointsPixel2, image_shape, None, None) + # print("Intrinsic matrix:\n", mtx.astype(np.float32)) + # print("Distortion coefficients:\n", dist.astype(np.float32)) - return mtx, dist + data = format_json_data(mtx, dist, image_shape) + # 在文件夹根目录下保存相机内参 + outputJsonPath = osp.join(baseFolder, "intri_calib.json") + write_json(data, outputJsonPath) + return mtx, dist, image_shape -def undistort_image(img, mtx, dist): +# calibrate_cameras函数中，照片按照相机编号进行分类 +def calibrate_cameras(baseFolder, chessboardSize, squareSize, visualization): + cameras = glob.glob(osp.join(baseFolder, '[0-9]')) + if len(cameras) == 0: + print("No camera folders found!") + return + outputJsonPath = osp.join(baseFolder, "intri_calib.json") + data = {} + for camera in cameras: + cameraId = osp.basename(camera) + print("\nCalibrating camera{}...".format(cameraId)) + mtx, dist, image_shape = calibrate_camera(camera, chessboardSize, squareSize, visualization) + data[cameraId] = format_json_data(mtx, dist, image_shape) + write_json(data, outputJsonPath) + print("\nCalibration data saved to: ", outputJsonPath) + +# 去除图像畸变 +def remove_image_distortion(img, mtx, dist): h, w = img.shape[:2] newcameramtx, roi = cv.getOptimalNewCameraMatrix(mtx, dist, (w, h), 1, (w, h)) dst = cv.undistort(img, mtx, dist, None, newcameramtx) @@ -87,55 +140,50 @@ def undistort_image(img, mtx, dist): dst = dst[y:y + h, x:x + w] return dst - -def undistort_images(imgFolder, mtx, dist): - imgPaths = [] - for extension in ["jpg", "png", "jpeg"]: - imgPaths += glob.glob(osp.join(imgFolder, "*.{}".format(extension))) +# 用于去除整个文件夹中的图像畸变，保存到文件夹下的distortion_corrected_images文件夹中 +def remove_images_distortion(baseFolder, mtx, dist): + imgPaths = read_img_paths(baseFolder) if len(imgPaths) == 0: print("No images found!") return - outputFolder = osp.join(imgFolder, "undistorted_images") - if not osp.exists(outputFolder): - os.makedirs(outputFolder) + outputFolder = create_output_folder(baseFolder, "distortion_corrected_images") for imgPath in imgPaths: img = cv.imread(imgPath) - dst = undistort_image(img, mtx, dist) + dst = remove_image_distortion(img, mtx, dist) cv.imwrite(osp.join(outputFolder, osp.basename(imgPath)), dst) - print("Undistorted images saved to: ", outputFolder) - - -def calibrate_cameras(imgFolder, chessboardSize, squareSize): - mtxs = [] - dists = [] - for folder in glob.glob(osp.join(imgFolder, "*")): - if not osp.isdir(folder): - continue - mtx, dist = calibrate_camera(folder, chessboardSize, squareSize) - mtxs.append(mtx) - dists.append(dist) - return mtxs, dists - - -def write_json_data(mtx, dist, outputFolder): - data = { - "intrinsic_matrix": mtx.tolist(), - "distortion_coefficients": dist.tolist() - } - with open(osp.join(outputFolder, "calibration.json"), "w") as f: - json.dump(data, f, indent=4) + print("Distortion corrected images saved to: ", outputFolder) if __name__ == "__main__": - parser = argparse.ArgumentParser() - parser.add_argument("imgFolder", help="Folder containing images for calibration") - parser.add_argument("--chessboardSize", help="Size of chessboard (rows, cols)", default="11,8") - parser.add_argument("--squareSize", help="Size of square in chessboard", default=60) + parser = argparse.ArgumentParser(description="相机内参标定和图像去畸变") + parser.add_argument("--action", type=str, required=True, choices=["camera", "cameras", "distortion"], + help=" --action camera: 标定单个相机" + " --action cameras: 标定多个相机" + " --action distortion: 去除图像畸变") + parser.add_argument("--folder", type=str, required=True, help="包含相机文件夹的基础文件夹") + parser.add_argument("--chessboardSize", type=str, default="11,8", help="棋盘格尺寸，格式为'w,h'") + parser.add_argument("--squareSize", type=float, default=60.0, help="棋盘格方块尺寸") + parser.add_argument("--no-vis", dest="vis", action="store_false", help="禁用标定结果的可视化输出") args = parser.parse_args() chessboardSize = tuple(map(int, args.chessboardSize.split(","))) - squareSize = float(args.squareSize) + if args.action == "camera": + print("Calibrating camera...") + mtx, dist, image_shape = calibrate_camera(args.folder, chessboardSize, args.squareSize, args.vis) + outputJsonPath = osp.join(args.folder, "intri_calib.json") + print("Calibration data saved to: ", outputJsonPath) + elif args.action == "cameras": + calibrate_cameras(args.folder, chessboardSize, args.squareSize, args.vis) + elif args.action == "distortion": + print("Removing image distortion...") + data = read_json(osp.join(args.folder, "intri_calib.json")) + mtx = np.array(data["K"]) + dist = np.array(data["dist"]) + remove_images_distortion(args.folder, mtx, dist) + else: + print("Invalid action!") + parser.print_help()