OpenCV项目中cv2.findContours解包报错：too many values to unpack

这个报错的核心原因是OpenCV版本之间的API差异，不同版本的cv2.findContours返回值数量不一样：

• OpenCV 2.x 和 OpenCV 4.x：返回(contours, hierarchy)两个值
• OpenCV 3.x：返回(image, contours, hierarchy)三个值

你的代码是按2个值来解包的，但当前运行环境用的是OpenCV 3.x，所以会触发"too many values to unpack"错误。

修复步骤 #

1. 调整findContours的解包语句
   把原来的：

   (cnts, _) = cv2.findContours(closed.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
   

   修改为适配OpenCV 3.x的写法（忽略第一个返回的图像值，我们用不到它）：

   _, cnts, _ = cv2.findContours(closed.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
   

2. 修复Python3的print语法问题
   你的代码里的print "I found..."是Python2的写法，在Python3环境中会报错，需要改成函数形式：

   print("I found {0} books in that image".format(total))
   

完整修复后的代码 #

# import the necessary packages
import numpy as np
import cv2

# load the image, convert it to grayscale, and blur it
image = cv2.imread("example.jpg")
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (3, 3), 0)
cv2.imshow("Gray", gray)
cv2.waitKey(0)

# detect edges in the image
edged = cv2.Canny(gray, 10, 250)
cv2.imshow("Edged", edged)
cv2.waitKey(0)

# construct and apply a closing kernel to 'close' gaps between 'white'
# pixels
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (7, 7))
closed = cv2.morphologyEx(edged, cv2.MORPH_CLOSE, kernel)
cv2.imshow("Closed", closed)
cv2.waitKey(0)

# 适配OpenCV 3.x的findContours返回值
_, cnts, _ = cv2.findContours(closed.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
total = 0

# loop over the contours
for c in cnts:
    # approximate the contour
    peri = cv2.arcLength(c, True)
    approx = cv2.approxPolyDP(c, 0.02 * peri, True)

    # if the approximated contour has four points, then assume that the
    # contour is a book -- a book is a rectangle and thus has four vertices
    if len(approx) == 4:
        cv2.drawContours(image, [approx], -1, (0, 255, 0), 4)
        total += 1

# display the output（适配Python3的print语法）
print("I found {0} books in that image".format(total))
cv2.imshow("Output", image)
cv2.waitKey(0)

额外提示 #

可以通过print(cv2.__version__)查看当前OpenCV的版本号，确认自己属于哪一类情况；如果后续升级到OpenCV4.x，改回原来的2值解包写法也可以正常运行。

内容的提问来源于stack exchange，提问作者Romka_10101