rectangle, Contour detection with python3, opencv3

Question

I want to detect paper sheet from image. i applied medianBlur, Canny , dilate, threshold, etc. algorithms to find.i am able to find sheet but don't know how to crop rectangle and apply transformation

answer sheet

This my code

import numpy as np
import cv2

image = cv2.imread('im_1.jpg')
image = cv2.resize(image, (800, 600))
draw = np.zeros_like(image)

gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))
thresh = cv2.erode(thresh, kernel, iterations=4)
thresh = cv2.dilate(thresh, kernel, iterations=4)
im, cnts, hier = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

max_area = -1
max_c = 0
for i in range(len(cnts)):
    contour = cnts[i]
    area = cv2.contourArea(contour)
    if (area > max_area):
        max_area = area
        max_c = i

contour = cnts[max_c]


rect = cv2.minAreaRect(contour)
box = cv2.boxPoints(rect)
box = np.int0(box)



cv2.drawContours(image, [box],-1, (0, 255, 0), 2)

cv2.imshow('Sheet', image)

cv2.waitKey(0)
cv2.destroyAllWindows()

result of code: result

Answer 1

There are some minor flaws in your approach. The following code will help. I have mentioned the changes made as well.

Code:

import numpy as np
import cv2

image = cv2.imread('C:/Users/Jackson/Desktop/score.jpg')

#--- Resized the image to half its dimension maintaining the aspect ratio ---
image = cv2.resize(image, (0, 0), fx = 0.5, fy = 0.5)
draw = np.zeros_like(image)

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

#--- I found the inverse binary image, because contours are found for objects in white. Since the border of the page is in black you have to invert the binary image. This is where it went wrong.
ret, thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV|cv2.THRESH_OTSU)

#--- I did not perform any morphological operation ---    
im, cnts, hier = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

max_area = -1
max_c = 0
for i in range(len(cnts)):
    contour = cnts[i]
    area = cv2.contourArea(contour)
    if (area > max_area):
        max_area = area
        max_c = i

contour = cnts[max_c]


rect = cv2.minAreaRect(contour)
box = cv2.boxPoints(rect)
box = np.int0(box)

cv2.drawContours(image, [box],-1, (0, 255, 0), 2)

cv2.imshow('Sheet', image) 
cv2.waitKey(0)
cv2.destroyAllWindows()

Result: