main.py

import pyautogui
import time

import cv2
import numpy as np

from mss import mss

sct = mss() 
 
bounding_box = {'top': 275, 'left': 275, 'width': 1325, 'height': 475}    

template = cv2.imread('claw.png')

filename = sct.shot()
print(filename)  

def find_cheese(img_rgb):
    img_rgb = (img_rgb).astype(np.uint8)[:,:,:3]

    lower_yellow = np.array([25, 150, 0])
    upper_yellow = np.array([30, 255, 255])
    mask = cv2.inRange(img_rgb, lower_yellow, upper_yellow)

    points = cv2.findNonZero(mask)

    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10, 1.0)
    # Find x,y coordinates of all non-white pixels in original image
    Y, X = np.where(mask==255)
    Z = np.column_stack((X,Y)).astype(np.float32)

    nClusters = 2
    try:
        ret,label,center=cv2.kmeans(Z,nClusters,None,criteria,10,cv2.KMEANS_RANDOM_CENTERS)
    except:
        return [(-1, -1), (-1,-1)]


    return center

def find_claw(sct_img_np):
    find_claw_img = (sct_img_np[10:60, 0:1325]).astype(np.uint8)[:,:,:3]
    w, h = template.shape[:-1]

    res = cv2.matchTemplate(find_claw_img, template, cv2.TM_CCOEFF_NORMED)

    threshold = .85
    loc = np.where(res >= threshold)
    for pt in zip(*loc[::-1]):  # Switch columns and rows
        return pt[0] 


lower_grey = np.array([130, 130, 130])
upper_grey = np.array([255, 255, 255])

def find_claw_2(sct_img_np):
    find_claw_img = (sct_img_np[10:30, 0:1325]).astype(np.uint8)[:,:,:3]

    mask = cv2.inRange(find_claw_img, lower_grey, upper_grey)
    res = cv2.bitwise_and(find_claw_img, find_claw_img, mask=mask)

    points = cv2.findNonZero(mask)

    try:
        return points[0][0][0]
    except TypeError:
        return -1



def claw_loop():
    error = 2
    x,y = centers[0]
    x = int(x)

    while True:
        sct_img = sct.grab(bounding_box)

        sct_img_np = np.array(sct_img) 

        claw_loc = find_claw_2(sct_img_np)

        if x > claw_loc - error and x < claw_loc + error :
            pyautogui.press('space') 
            print("OVER") 
            return


while True:
    print("wait") 
    time.sleep(5)
    print("go")

    pyautogui.press('space')  

    sct_img = sct.grab(bounding_box)

    sct_img_np = np.array(sct_img)

    centers = find_cheese(sct_img_np)

    if(centers[0][0] == -1):
        print("no cheese")
        pyautogui.press('space')   
    else:
        claw_loop()