Python从其他代码文件导入变量时img未定义报错如何解决

报错原因 #

当你使用import语句导入Python文件时，解释器会完整执行目标文件的所有顶层代码，你的报错触发逻辑为：

• 如果./images/目录下没有匹配的.jpg图片，images列表为空，for fname in images循环完全不会运行，img变量从未被创建
• 循环结束后执行h, w = img.shape[:2]时就会抛出NameError: name 'img' is not defined
  即便目录下有图片，导入时也会触发cv2.imshow逐张弹出校准图片需要手动确认，完全不符合工具模块导入的使用需求。

最优解决方法 #

不要直接导入变量，先将校准生成的参数持久化存储到本地文件，主代码直接读取文件获取参数即可，效率更高也不会触发不必要的代码执行。

第一步：修改Calibration.py代码

增加入口保护和参数存储逻辑，修改后代码如下：

import cv2
import numpy as np
import os
import glob

# 仅在直接运行本文件时执行校准逻辑，导入时不会运行
if __name__ == "__main__":
    # Defining the dimensions of checkerboard
    CHECKERBOARD = (7, 9)
    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)

    # Creating vector to store vectors of 3D points for each checkerboard image
    objpoints = []
    # Creating vector to store vectors of 2D points for each checkerboard image
    imgpoints = []

    # Defining the world coordinates for 3D points
    objp = np.zeros((1, CHECKERBOARD[0] * CHECKERBOARD[1], 3), np.float32)
    objp[0, :, :2] = np.mgrid[0:CHECKERBOARD[0], 0:CHECKERBOARD[1]].T.reshape(-1, 2)
    prev_img_shape = None

    # Extracting path of individual image stored in a given directory
    images = glob.glob('./images/*.jpg')
    for fname in images:
        img = cv2.imread(fname)
        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        # Find the chess board corners
        # If desired number of corners are found in the image then ret = true
        ret, corners = cv2.findChessboardCorners(gray, CHECKERBOARD,
                                                 cv2.CALIB_CB_ADAPTIVE_THRESH + cv2.CALIB_CB_FAST_CHECK + cv2.CALIB_CB_NORMALIZE_IMAGE)

        """
        If desired number of corner are detected,
        we refine the pixel coordinates and display 
        them on the images of checker board
        """
        if ret == True:
            objpoints.append(objp)
            # refining pixel coordinates for given 2d points.
            corners2 = cv2.cornerSubPix(gray, corners, (11, 11), (-1, -1), criteria)

            imgpoints.append(corners2)

            # Draw and display the corners
            img = cv2.drawChessboardCorners(img, CHECKERBOARD, corners2, ret)

        cv2.imshow('img', img)
        cv2.waitKey(0)

    cv2.destroyAllWindows()

    h, w = img.shape[:2]

    """
    Performing camera calibration by 
    passing the value of known 3D points (objpoints)
    and corresponding pixel coordinates of the 
    detected corners (imgpoints)
    """
    ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1], None, None)

    print("Camera matrix : \n")
    print(mtx)
    print("dist : \n")
    print(dist)
    print("rvecs : \n")
    print(rvecs)
    print("tvecs : \n")
    print(tvecs)
    
    # 保存校准参数到本地文件
    np.savez("calib_params.npz", mtx=mtx, dist=dist, rvecs=rvecs, tvecs=tvecs)

修改完成后直接单独运行一次Calibration.py，会在同级目录生成calib_params.npz参数文件。

第二步：主代码读取参数

不需要导入Calibration.py，直接读取参数文件即可获取需要的变量：

import numpy as np

# 加载校准参数
params = np.load("calib_params.npz")
mtx = params["mtx"]
dist = params["dist"]
rvecs = params["rvecs"]
tvecs = params["tvecs"]

内容的提问来源于stack exchange，提问作者Rami El-Assaad