guilhermemauro

#compare contour founded with the pattern in X.png and O.png files
def compareContourHSV(cnt):
    global player, computer
    if cnt is False:
        return False
    patternX = cv2.cvtColor(cv2.imread('X.png'), cv2.COLOR_BGR2GRAY)
    patternX = findBiggestContour(patternX)
    resX = cv2.matchShapes(patternX, cnt, 1, 0.0)
    patternO = cv2.cvtColor(cv2.imread('O.png'), cv2.COLOR_BGR2GRAY)
    patternO = findBiggestContour(patternO)

guilhermemauro

#cut image staying just the field choosed
def getField(coord, frame):
    crop_img = frame[coord[0]:coord[1], coord[2]:coord[3]]
    return crop_img

#find X and/or O with color detection in cut image
def getContoursHSV(img):
    mask = cv2.inRange(cv2.cvtColor(img, cv2.COLOR_BGR2HSV), CARD_COLOR_LOW, CARD_COLOR_UP)
    if len(mask) > 0:
        dilation = cv2.dilate(mask,KERNEL,iterations = 2)

guilhermemauro

#like the function's name, choose the biggest contour in mask
def findBiggestContour(mask):
    temp_bigger = []
    img1, cont, hier = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
    if len(cont) == 0:
        return False
    for cnt in cont:
        temp_bigger.append(cv2.contourArea(cnt))
    greatest = max(temp_bigger)
    index_big = temp_bigger.index(greatest)

guilhermemauro

import numpy as np
import cv2
import tictactoe as tic
import time

#choose X and O color for color detection
CARD_COLOR_UP = np.array([255,255,255],dtype="uint8")
CARD_COLOR_LOW = np.array([150,150,150],dtype="uint8")

#font to cv2.putText