Error on ContourAreas

[thelwyn]

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Hi,

While initially playing your code i was running into this error:

` File "C:/Users/thinkpad/Desktop/read_serial.py", line 56, in if cv2.contourArea(c) < 300:

error: OpenCV(4.0.1-dev) C:\Users\thinkpad\Documents\openCV4Win\opencv-master\opencv\modules\imgproc\src\shapedescr.cpp:274: error: (-215:Assertion failed) npoints >= 0 && (depth == CV_32F || depth == CV_32S) in function 'cv::contourArea'`

I fixed it by adding one variable in this line:

#cnts = cv2.findContours(dilate.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE) cnts,hierarchy = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)

It seens related to how different versions of OpenCv need different numbers of parameters for findContours.

I would have thought that the next line would cover for that, but apparently not: cnts = cnts[0] if imutils.is_cv2() else cnts[1]

Anyway, I got it working, and I actually post this issue because I didn't find another way to thank you and send my greetings :) Cheers!

[shanmugamani96]

hai i am using your given code: import cv2 import numpy as np import imutils import pytesseract

read image from disk

image = cv2.imread('images/test1.jpg')

make it gray

img = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

blur it to remove noise

img = cv2.GaussianBlur(img, (7,7), 0)

perform edge detection, then perform a dilation + erosion to

close gaps in between object edges

edged = cv2.Canny(img, 40, 90) dilate = cv2.dilate(edged, None, iterations=2)

perform erosion if necessay, it completely depends on the image

erode = cv2.erode(dilate, None, iterations=1)

create an empty masks

mask = np.ones(img.shape[:2], dtype="uint8") * 255

find contours

cnts = cv2.findContours(dilate.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)[0]

cnts = cv2.findContours(dilate.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)

cnts,hierarchy = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE) print(cnts)

cnts = cnts[0] if imutils.is_cv2() else cnts[1]

cnts = cnts[0] if imutils.is_cv2() else cnts[1]

orig = img.copy() for c in cnts: # if the contour is not sufficiently large, ignore it if cv2.contourArea(c) < 300: cv2.drawContours(mask, [c], -1, 0, -1)

x,y,w,h = cv2.boundingRect(c)

# filter more contours if nessesary
if(w>h):
    cv2.drawContours(mask, [c], -1, 0, -1)

newimage = cv2.bitwise_and(dilate.copy(), dilate.copy(), mask=mask) img2 = cv2.dilate(newimage, None, iterations=3) ret2,th1 = cv2.threshold(img2 ,0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)

Tesseract OCR on the image

temp = pytesseract.image_to_string(th1)

Write results on the image

cv2.putText(image, temp, (100,100), cv2.FONT_HERSHEY_SIMPLEX, 1.8, (0,255,255), 3)

show the outputs

cv2.imshow('Original image', cv2.resize(image,(640,480))) cv2.imshow('Dilated', cv2.resize(dilate,(640,480))) cv2.imshow('New Image', cv2.resize(newimage,(640,480))) cv2.imshow('Inverted Threshold', cv2.resize(th1,(640,480)))

cv2.waitKey(0) cv2.destroyAllWindows() but i didnt get results; here i attached result image ,kindly check it, cv2.destroyAllWindows() but i didnt get results;

[shanmugamani96]

Is the accuracy level low, so is there any method to improve?