我正在尝试使用代码阅读多项选择测试反馈中的答案，但出现以下错误消息:
error: (-215:Assertion failed) npoints >= 0 && (depth == CV_32F || depth == CV_32S) in function 'cv::contourArea
我已经尝试使用计算机中的 .png 图像而不是使用相机，但我遇到了同样的问题。我是 python 的新手，我不知道库或代码是否有问题。 这是我正在使用的代码:
from imutils.perspective import four_point_transform
from imutils import contours
import numpy as np
import imutils
import cv2
ct = 0
cap = cv2.VideoCapture(0)
correct = 0
gb = [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3]
while (1):
ct = 0
ret, image = cap.read()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (3, 3), 0)
edged = cv2.Canny(blurred, 20, 150)
cv2.imshow("Camera", edged)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cv2.moveWindow("Camera", 0, 0)
cnts = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if imutils.is_cv2() else cnts[1]
docCnt = None
if len(cnts) > 0:
cnts = sorted(cnts, key=cv2.contourArea, reverse=True)
for c in cnts:
peri = 0.02 * cv2.arcLength(c, True)
approx = cv2.approxPolyDP(c, peri, True)
if len(approx) == 4:
ct = 1
docCnt = approx
break
if ct == 1:
paper = four_point_transform(image, docCnt.reshape(4, 2))
warped = four_point_transform(gray, docCnt.reshape(4, 2))
altura = paper.shape[0] // 11
largura = paper.shape[0] // 2.95
paper = paper[altura:paper.shape[0], largura:paper.shape[1]]
thresh = cv2.threshold(warped, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
thresh = thresh[altura:thresh.shape[0], largura:thresh.shape[1]]
if thresh.shape[0] > 0 and thresh.shape[1] > 0:
cnts = cv2.findContours(thresh.copy(),
cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if imutils.is_cv2() else cnts[1]
questionCnts = []
for c in cnts:
tamanho = thresh.shape[1] / 5
(x, y, w, h) = cv2.boundingRect(c)
ar = w / float(h)
approx = cv2.approxPolyDP(c, peri, True)
if (w <= tamanho and h < tamanho) and (ar >= 1.6 and ar <= 2.6) and (w > tamanho / 10 and h > tamanho / 10):
questionCnts.append(c)
print(len(questionCnts))
if len(questionCnts) == 50:
break
cont = 0
x = 0
y = 0
res = []
bubbled = []
questao = []
for (q, i) in enumerate(np.arange(0, len(questionCnts), 5)):
cont = 0
cnts = contours.sort_contours(questionCnts[i:i + 5])[0]
bubbled = []
for (j, c) in enumerate(cnts):
x = thresh.shape[0]
y = thresh.shape[1]
mask = np.zeros(thresh.shape, dtype="uint8")
cv2.drawContours(mask, [c], -1, 255, -1)
mask = cv2.bitwise_and(thresh, thresh, mask=mask)
total = cv2.countNonZero(mask)
if total > x // 20 * y // 10:
bubbled.append(j)
cont += 1
if cont == 1:
res.append(bubbled[0])
else:
res.append(-1)
color = (0, 0, 255)
k = gb[q]
if cont == 1:
if k == bubbled[0]:
color = (0, 255, 0)
correct += 1
for s in range(cont):
cv2.drawContours(paper, [cnts[bubbled[s]]], -1, color, 3)
res2 = []
for i in range(len(res)):
res2.append(res[len(res) - i - 1])
print("Gabarito:", gb)
print("Respostas:", res2)
print("Nota:", float(correct))
cv2.imshow("Cartao Resposta", paper)
cv2.waitKey(0)
cv2.imshow("real", image)
cv2.waitKey(0)
cap.release()
最佳答案
你把这条线倒过来了。变化
cnts = cnts[0] if imutils.is_cv2() else cnts[1]
到
cnts = cnts[1] if imutils.is_cv2() else cnts[0]
这一行实质上是检查您正在运行的 OpenCV 版本。如果是 OpenCV 3.4.X，则 cv2.findContours()函数返回 3 项，因此要获取实际轮廓，您需要获取第二个返回值。同样，如果您运行的是 OpenCV 4.1.X，cv2.findContours()返回 2 个项目，因此您需要获取第一个值才能获得实际轮廓。
这是固定代码
from imutils.perspective import four_point_transform
from imutils import contours
import numpy as np
import imutils
import cv2
ct = 0
cap = cv2.VideoCapture(0)
correct = 0
gb = [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3]
while (1):
ct = 0
ret, image = cap.read()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (3, 3), 0)
edged = cv2.Canny(blurred, 20, 150)
cv2.imshow("Camera", edged)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cv2.moveWindow("Camera", 0, 0)
cnts = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[1] if imutils.is_cv2() else cnts[0]
docCnt = None
if len(cnts) > 0:
cnts = sorted(cnts, key=cv2.contourArea, reverse=True)
for c in cnts:
peri = 0.02 * cv2.arcLength(c, True)
approx = cv2.approxPolyDP(c, peri, True)
if len(approx) == 4:
ct = 1
docCnt = approx
break
if ct == 1:
paper = four_point_transform(image, docCnt.reshape(4, 2))
warped = four_point_transform(gray, docCnt.reshape(4, 2))
altura = paper.shape[0] // 11
largura = paper.shape[0] // 2.95
paper = paper[altura:paper.shape[0], largura:paper.shape[1]]
thresh = cv2.threshold(warped, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
thresh = thresh[altura:thresh.shape[0], largura:thresh.shape[1]]
if thresh.shape[0] > 0 and thresh.shape[1] > 0:
cnts = cv2.findContours(thresh.copy(),
cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cnts = cnts[0] if imutils.is_cv2() else cnts[1]
questionCnts = []
for c in cnts:
tamanho = thresh.shape[1] / 5
(x, y, w, h) = cv2.boundingRect(c)
ar = w / float(h)
approx = cv2.approxPolyDP(c, peri, True)
if (w <= tamanho and h < tamanho) and (ar >= 1.6 and ar <= 2.6) and (w > tamanho / 10 and h > tamanho / 10):
questionCnts.append(c)
print(len(questionCnts))
if len(questionCnts) == 50:
break
cont = 0
x = 0
y = 0
res = []
bubbled = []
questao = []
for (q, i) in enumerate(np.arange(0, len(questionCnts), 5)):
cont = 0
cnts = contours.sort_contours(questionCnts[i:i + 5])[0]
bubbled = []
for (j, c) in enumerate(cnts):
x = thresh.shape[0]
y = thresh.shape[1]
mask = np.zeros(thresh.shape, dtype="uint8")
cv2.drawContours(mask, [c], -1, 255, -1)
mask = cv2.bitwise_and(thresh, thresh, mask=mask)
total = cv2.countNonZero(mask)
if total > x // 20 * y // 10:
bubbled.append(j)
cont += 1
if cont == 1:
res.append(bubbled[0])
else:
res.append(-1)
color = (0, 0, 255)
k = gb[q]
if cont == 1:
if k == bubbled[0]:
color = (0, 255, 0)
correct += 1
for s in range(cont):
cv2.drawContours(paper, [cnts[bubbled[s]]], -1, color, 3)
res2 = []
for i in range(len(res)):
res2.append(res[len(res) - i - 1])
print("Gabarito:", gb)
print("Respostas:", res2)
print("Nota:", float(correct))
cv2.imshow("Cartao Resposta", paper)
cv2.waitKey(0)
cv2.imshow("real", image)
cv2.waitKey(0)
cap.release()
关于python - 出现以下错误消息 : error: (-215:Assertion failed) npoints >= 0 && (depth == CV_32F || depth == CV_32S) in function 'cv::contourArea' ，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/57980005/