card_detection.py

import numpy as np
import cv2
from matplotlib import pyplot as plt
from mpl_toolkits.axes_grid1 import ImageGrid
import math


def rectify(h):
    h = h.reshape((4,2))
    hnew = np.zeros((4,2),dtype = np.float32)

    add = h.sum(1)
    hnew[0] = h[np.argmin(add)]
    hnew[2] = h[np.argmax(add)]

    diff = np.diff(h,axis = 1)
    hnew[1] = h[np.argmin(diff)]
    hnew[3] = h[np.argmax(diff)]

    return hnew

def Imagedetection(imagepath,numcards,epsilon=0.03):
    img = cv2.imread(imagepath)
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    blur = cv2.GaussianBlur(gray,(1,1),1000)
    flag, thresh = cv2.threshold(blur, 120, 255, cv2.THRESH_BINARY)
    # Find contours
    image,contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
    contours = sorted(contours, key=cv2.contourArea,reverse=True)
    # Select long perimeters only
    perimeters = [cv2.arcLength(contours[i],True) for i in range(len(contours))]
    listindex=[i for i in range(numcards) if perimeters[i]>perimeters[0]/2]
    # Show image
    imgcont = img.copy()
    [cv2.drawContours(imgcont, [contours[i]], 0, (0,255,0), 5) for i in listindex]

    warp = list(range(numcards))

    for i in range(numcards):
        card = contours[i]
        peri = 0.02*cv2.arcLength(card,True)
        approx =  cv2.approxPolyDP(card,peri,True)
        rect = cv2.minAreaRect(contours[i])
        r = cv2.boxPoints(rect)

        h = np.float32([[0,0],[399,0],[399,399],[0,399]])
        approx = np.float32([item for sublist in approx for item in sublist])
        print(approx.shape)
        transform = cv2.getPerspectiveTransform(approx,h)
        warp[i] = cv2.warpPerspective(img,transform,(400,400))

    # Show perspective correction

    new_img_list = []
    for i in range(numcards):
        new_img = cv2.cvtColor(warp[i],cv2.COLOR_BGR2RGB)
        new_img_list.append(new_img)

        cv2.imwrite(f"static/images/cropped/Image{i}.jpg",warp[i])

    return new_img_list