Reputation: 51
Сode taken from article A guide to finding books in images using Python and OpenCV.
I launch the project at PyCharm. They are deduced from the picture, and when there must be a fourth - it is knocking out the error
(cnts , _) = cv2.findContours(closed.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) ValueError: too many values to unpack (expected 2)
# 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)
# find contours (i.e. the 'outlines') in the image and initialize the
# total number of books found
(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
print "I found {0} books in that image".format(total)
cv2.imshow("Output", image)
cv2.waitKey(0)
Upvotes: 0
Views: 680
Reputation: 33197
Depending on the cv2 version, this function may return a different number of elements. The problem is that you are using cv2 version 3, and not version 2.
First of all, what is your version?
Use:
import cv2
cv2.__version__
To solve the error try first this:
(_, cnts, _) = cv2.findContours(closed.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
Upvotes: 2