cv.findContours() - ValueError: not enough values to unpack (expected 3, got 2)

Question

So, I was running the code from this tutorial on OpenCV on how to find contour on images and create the bounding box. I didn't change anything (besides the image source filename) from the code. It's exactly like on the tutorial. But when I'm running it, it encounters this error:

Traceback (most recent call last):
  File "contour.py", line 78, in <module>
    thresh_callback(thresh)
  File "contour.py", line 19, in thresh_callback
    _, contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
ValueError: not enough values to unpack (expected 3, got 2)

I think I know what the error is, it's because it doesn't get the expected values from cv.findContours but I don't know how to solve it. What happened and what should I do? Like I said, the code is exactly like on the tutorial.

This is the code.

from __future__ import print_function
import cv2 as cv
import numpy as np
import argparse
import random as rng

rng.seed(12345)

def thresh_callback(val):
    threshold = val

    ## [Canny]
    # Detect edges using Canny
    canny_output = cv.Canny(src_gray, threshold, threshold * 2)
    ## [Canny]

    ## [findContours]
    # Find contours
    _, contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
    ## [findContours]

    ## [allthework]
    # Approximate contours to polygons + get bounding rects and circles
    contours_poly = [None]*len(contours)
    boundRect = [None]*len(contours)
    centers = [None]*len(contours)
    radius = [None]*len(contours)
    for i, c in enumerate(contours):
        contours_poly[i] = cv.approxPolyDP(c, 3, True)
        boundRect[i] = cv.boundingRect(contours_poly[i])
        centers[i], radius[i] = cv.minEnclosingCircle(contours_poly[i])
    ## [allthework]

    ## [zeroMat]
    drawing = np.zeros((canny_output.shape[0], canny_output.shape[1], 3), dtype=np.uint8)
    ## [zeroMat]

    ## [forContour]
    # Draw polygonal contour + bonding rects + circles
    for i in range(len(contours)):
        color = (rng.randint(0,256), rng.randint(0,256), rng.randint(0,256))
        cv.drawContours(drawing, contours_poly, i, color)
        cv.rectangle(drawing, (int(boundRect[i][0]), int(boundRect[i][1])), (int(boundRect[i][0]+boundRect[i][2]), int(boundRect[i][1]+boundRect[i][3])), color, 2)
        cv.circle(drawing, (int(centers[i][0]), int(centers[i][1])), int(radius[i]), color, 2)
    ## [forContour]

    ## [showDrawings]
    # Show in a window
    cv.imshow('Contours', drawing)
    ## [showDrawings]

## [setup]
# Load source image
parser = argparse.ArgumentParser(description='Code for Creating Bounding boxes and circles for contours tutorial.')
parser.add_argument('--input', help='Path to input image.', default='example.png')
args = parser.parse_args()

src = cv.imread(cv.samples.findFile(args.input))
if src is None:
    print('Could not open or find the image:', args.input)
    exit(0)

# Convert image to gray and blur it
src_gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
src_gray = cv.blur(src_gray, (3,3))
## [setup]

## [createWindow]
# Create Window
source_window = 'Source'
cv.namedWindow(source_window)
cv.imshow(source_window, src)
## [createWindow]
## [trackbar]
max_thresh = 255
thresh = 100 # initial threshold
cv.createTrackbar('Canny thresh:', source_window, thresh, max_thresh, thresh_callback)
thresh_callback(thresh)
## [trackbar]

cv.waitKey()

There's a similar question here but it didn't get any answer.

please look up findContours in the documentation. the tutorial is somewhat outdated. findContours returns a different number of things now. that is also what the error message tells you. — Christoph Rackwitz, Jan 05 '21 at 19:15

score 1 · Accepted Answer · answered Jan 05 '21 at 19:16

1

"findContours" returns a tuple of two values. The correct usage is:

contours, _ = cv.findContours(canny_output, cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)

answered Jan 05 '21 at 19:16

Hihikomori

950
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cv.findContours() - ValueError: not enough values to unpack (expected 3, got 2)

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