import cv2
import numpy as np

from IPython.display import display, Image

def display_cv_image(image, format='.png'):
    decoded_bytes = cv2.imencode(format, image)[1].tobytes()
    display(Image(data=decoded_bytes))
    img = cv2.imread("{Chemin du fichier image}")
    display_cv_image(img)
    #Échelle de gris
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

    #Binarisation
    ret,th1 = cv2.threshold(gray,200,255,cv2.THRESH_BINARY)
    display_cv_image(th1)
    contours, hierarchy = cv2.findContours(th1,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)

    #Trier uniquement ceux qui ont une grande surface
    areas = []
    for cnt in contours:
        area = cv2.contourArea(cnt)
        if area > 10000:
            epsilon = 0.1*cv2.arcLength(cnt,True)
            approx = cv2.approxPolyDP(cnt,epsilon,True)
            areas.append(approx)

    cv2.drawContours(img,areas,-1,(0,255,0),3)
    display_cv_image(img)
    img = cv2.imread("{Chemin du fichier image}")

    dst = []

    pts1 = np.float32(areas[0])
    pts2 = np.float32([[600,300],[600,0],[0,0],[0,300]])

    M = cv2.getPerspectiveTransform(pts1,pts2)
    dst = cv2.warpPerspective(img,M,(600,300))

    display_cv_image(dst)

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