screenshot.py

import numpy as np
import re
import cv2
import time
import win32api
import datetime
import os
from PIL import ImageGrab
from PIL import Image
from pywinauto import Desktop
from pywinauto import mouse
from pywinauto.application import Application

THRESHOLD_VALUE = 127  # Tweak as needed
# The reference image of the golden cookie
reference_path = os.path.join(os.path.dirname(__file__), 'reference.png')
# A file containing a screenshot with the golden cookie, for testing purposes
cheat_path = os.path.join(os.path.dirname(__file__), 'cheat.jpg')
# When true, will bypass the screenshot function and use the cheat image instead
TESTING = False
# When true, will automatically click the golden cookie when it appears
AUTOCLICK = True


def get_cookie_clicker_screenshot():
    if TESTING:
        img = Image.open(cheat_path).convert('L')
        img = np.array(img)
        ret, img = cv2.threshold(img, THRESHOLD_VALUE, 255, cv2.THRESH_BINARY)
        return img

    title_pattern = re.compile(r"^.*cookies.*Cookie Clicker.*")
    app = Application().connect(title_re=title_pattern)
    window = app.window(title_re=title_pattern)
    x, y, width, height = window.rectangle().left, window.rectangle(
    ).top, window.rectangle().width(), window.rectangle().height()
    # print("Window position is (", x, ",", y, ")")
    img = ImageGrab.grab(
        bbox=(x, y, x + width, y + height)).convert('L')
    img = np.array(img)
    ret, img = cv2.threshold(img, THRESHOLD_VALUE, 255, cv2.THRESH_BINARY)
    return img


def prepare_reference_image(image_path):
    # Open the image and convert it to grayscale
    img = Image.open(image_path).convert('L')
    # Convert the image to a numpy array and apply thresholding
    img_array = np.array(img)
    img_array[img_array < THRESHOLD_VALUE] = 0
    img_array[img_array >= THRESHOLD_VALUE] = 255
    # Create an SIFT object
    sift = cv2.SIFT_create()
    # Detect keypoints and compute their descriptors
    keypoints, descriptors = sift.detectAndCompute(img_array, None)
    # Return the keypoints and descriptors
    return keypoints, descriptors, img_array


def find_golden_cookie(screenshot, kp_reference, des_reference, img_reference):
    sift = cv2.SIFT_create()
    # Finding keypoints and descriptor of the screenshot
    game_screenshot = screenshot
    kp_screenshot, des_screenshot = sift.detectAndCompute(
        game_screenshot, None)
    # create BFMatcher object
    bf = cv2.BFMatcher(cv2.NORM_L2)
    # Match descriptors.
    matches = bf.knnMatch(des_reference, des_screenshot, k=2)
    good_matches = []
    # Lowe's ratio test
    ratio = 0.6
    for match in matches:
        if len(match) == 2 and match[0].distance < match[1].distance * ratio:
            good_matches.append(match[0])
    img_matches = cv2.drawMatches(
        img_reference, kp_reference, screenshot, kp_screenshot, good_matches, None)
    # Obtain the coordinates of the best match
    if len(good_matches) > 0:
        x, y = kp_screenshot[good_matches[0].trainIdx].pt
        # print("Match found")
        return x, y
    else:
        # print("No match found")
        return -1, -1


def click_mouse(x, y):
    mouse.press(button='left', coords=(x, y))
    time.sleep(0.2)
    mouse.release(button='left', coords=(x, y))


while True:
    current_x, current_y = win32api.GetCursorPos()

    # print("Mouse position is (", current_x, ",", current_y, ")")
    screenshot = get_cookie_clicker_screenshot()
    kp_reference, des_reference, img_reference = prepare_reference_image(
        reference_path)
    x, y = find_golden_cookie(screenshot, kp_reference,
                              des_reference, img_reference)
    if x >= 0 and y >= 0:
        x, y = int(x), int(y)
        print("******** Cookie found at:", datetime.datetime.now(),
              "at (", int(x), ", ", int(y), ")")
        if AUTOCLICK:
            click_mouse(int(x), int(y))
            click_mouse(int(x), int(y))
            click_mouse(int(x), int(y))
            mouse.move(coords=(current_x, current_y))
    time.sleep(1)