OpenCV版本:3.4.0(无法为其创建标记)
在尝试近似找到的轮廓时,我遇到了以下错误:
cv2.error:/io/opencv/modules/imgproc/src/shapedescr.cpp:237:错误: (-215)计数> = 0&& (深度== 5 ||深度== 4)函数arcLength
错误是由行
引起的EPS = cv2.arcLength(CNT,真)
此外,如果我评论这部分代码
EPS = cv2.arcLength(CNT,真)
approx = cv2.approxPolyDP(cnt,0.01 * eps,True)
我收到以下错误
cv2.error:/io/opencv/modules/imgproc/src/drawing.cpp:2506:错误: (-215)npoints>函数drawContours中的0
来自行:
cv2.drawContours(gray1,[cnt],0,(0,0,255,1),3)
也许是(以某种方式)由首先拆分然后合并视频输入的通道引起的?
我发现类似的问题似乎可以通过
来解决gray1 = cv2.convertScaleAbs(gray1)
哪个不幸的不是我的情况。将非常感谢帮助。 :)
我提供以下代码:
import numpy as np
import cv2
cap = cv2.VideoCapture('video2.mp4')
while cap.isOpened():
ret, frame = cap.read()
frame = cv2.resize(frame, (640, 480), interpolation = cv2.INTER_LINEAR)
gray1=frame # Is this right?
frameArea = frame.shape[0]*frame.shape[1]
# split the RGB image into R,G,B channels respectively
b, g, r = frame[:, :, 0], frame[:, :, 1], frame[:, :, 2]
# put back thresholded channels into one RGB image
retvalb, b = cv2.threshold(b, 90, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
retvalg,g = cv2.threshold(g, 0, 70, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
retvalr,r = cv2.threshold(r, 0, 70, cv2.THRESH_BINARY+cv2.THRESH_OTSU)
frame = cv2.merge((b,g,r))
# create gray image in order to further threshold the result
gray1 = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY);
retvalgray, gray = cv2.threshold(gray1,0, 255, cv2.THRESH_BINARY+cv2.THRESH_OTSU);
gray1 = cv2.bilateralFilter(gray1, 11, 17, 17)
gray1 = cv2.convertScaleAbs(gray1)
# find the region of interest by drawing contours around it
_, val,cnts = cv2.findContours(gray1, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) #gray / edged ?
for cnt in cnts:
eps=cv2.arcLength(cnt,True)
approx = cv2.approxPolyDP(cnt,0.01*eps,True)
cv2.drawContours(gray1,[cnt],0,(0,0,255, 1),3)
cv2.imshow("Detection", gray1)
if cv2.waitKey(1) & 0xFF is ord('q'):
cv2.destroyAllWindows()
print("Stop programm and close all windows")
break
答案 0 :(得分:0)
问题非常简单 - findcountours方法中的变量顺序错误
WRONG:
_,val,cnts = cv2.findContours(gray1,cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)#gray / edged?
RIGHT:
_,cnts,val = cv2.findContours(gray1,cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)#gray / edged?
答案 1 :(得分:0)
findContour()输出修改后的图像,轮廓和层次结构。轮廓是图像中所有轮廓的Python列表。每个轮廓都是对象边界点的(x,y)坐标的Numpy数组。
例如: im2,轮廓,层次结构= cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
您正在遍历层次结构。不是轮廓。
有关更多信息,请参见documentation。