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# -*- coding: utf-8 -*-
"""
Created on Thu Mar 23 00:09:06 2023
@author: salihcanturan
"""
# dogrulamaBOT değişkeni bağlı olmaksızın her zaman çalışır
dogrulamaBOT = True
# me tinBOT açık olsun mu, Metin konfigürasyonu yapılmalı
metinBOT = False
# dereceBOT açık olsun mu, Skill konfigürasyonu yapılması gerekebilir
dereceBOT = True
# skillBOT
skillBOT = False
from pytesseract import pytesseract
import threading
import pygetwindow
from pynput.keyboard import Key, Controller
import win32api, win32con
from win32gui import GetWindowText, GetForegroundWindow
from PIL import ImageFont
import pyautogui
import mss
import numpy as np
import cv2
import time
import pyuac
import keyboard
import pickle
import uuid
from unidecode import unidecode
from DatasetLoader import getItemIconDictionary
import re
path_to_tesseract = r'C:\Program Files\Tesseract-OCR\tesseract.exe'
pytesseract.tesseract_cmd = path_to_tesseract
print('Is user admin?', pyuac.isUserAdmin())
WINDOW_NAME = 'Harbi2 | shaula666'
titles = pygetwindow.getAllTitles()
program_active = 100
stopApp = False
screenshot = None
dogrulama_screenshot = None
active_window = None
resized = None
imageDataset = getItemIconDictionary()
controller = Controller()
def click(x, y):
old = pyautogui.position()
win32api.SetCursorPos((x,y))
time.sleep(0.1)
win32api.mouse_event(win32con.MOUSEEVENTF_LEFTDOWN,x,y,0,0)
time.sleep(0.1)
win32api.mouse_event(win32con.MOUSEEVENTF_LEFTUP,x,y,0,0)
win32api.SetCursorPos(old)
def string_benzerligi(str1, str2):
str1 = str1[:-4]
str1 = str1.lower()
str2 = str2.lower()
str1 = re.sub('[^A-Za-z]+', '', unidecode(str1))
str2 = re.sub('[^A-Za-z]+', '', unidecode(str2))
toplam_benzerlik = 0
for karakter in set(str1 + str2):
toplam_benzerlik += min(str1.count(karakter), str2.count(karakter))
return 100.0 * toplam_benzerlik / (len(str1) + len(str2)) + 1
def mse_benzerligi(img1, img2):
return np.mean((img1[:,:,:3].astype("float") - img2.astype("float")) ** 2)
metinThreadDone = True
def metinBOTThread(region, ratio):
global metinThreadDone
metinThreadDone = False
found = False
x = None
y = None
# Metin tespit kısa kodu tüm piksellere bakar.
for i in range(100, len(screenshot)-50, 2):
for j in range(0, len(screenshot[0]), 2):
blue = screenshot[i, j][0]
green = screenshot[i, j][1]
red = screenshot[i, j][2]
if abs(150 - blue) < 40 and abs(46 - green) < 20 and abs(95 - red) < 20:
found = True
x = int(region['left']+j*(1/ratio))
y = int(region['top']+i*(1/ratio))
break
if found:
break
if found:
click(x, y)
controller.press('q')
time.sleep(1.5)
controller.release('q')
if found:
time.sleep(10)
metinThreadDone = True
def dereceBOTThread():
global program_active
ss = {'1': [0, 274],
'2': [0, 174],
'3': [0, 174]}
curr_time = 0
cooldown = 30
while True and not stopApp and program_active > 0:
if active_window != WINDOW_NAME:
controller.release(Key.space)
continue
print(program_active)
program_active -= 1
controller.press(Key.space)
if curr_time % 40 == 0:
controller.press('4')
time.sleep(0.1)
for skill in ss:
ss[skill][0] -= 0.1
controller.release('4')
curr_time += 1
if skillBOT:
if cooldown > 0:
cooldown -= 1
else:
for skill in ss:
if ss[skill][0] < 0 and cooldown <= 0:
controller.press('h')
time.sleep(0.2)
controller.release('h')
controller.press(skill)
time.sleep(0.2)
controller.release(skill)
controller.press('h')
time.sleep(0.2)
controller.release('h')
for skill2 in ss:
ss[skill2][0] -= 0.4
ss[skill][0] = ss[skill][1]
print(ss[skill][0], ss[skill][1])
curr_time += 4
cooldown = 40
curr_time += 1
time.sleep(0.1)
for skill in ss:
ss[skill][0] -= 0.1
def updateScreenshotThread():
global dogrulama_screenshot, screenshot
sct = mss.mss()
window = pygetwindow.getWindowsWithTitle(WINDOW_NAME)
if len(window) == 0:
return
window = window[0]
left, top = window.topleft
right, bottom = window.bottomright
region = {'top': top, 'left': left, 'width': right-left, 'height': bottom-top}
raw_screenshot = sct.grab(region)
raw_screenshot = np.array(raw_screenshot)[:,:,:3]
ratio = 1000 / raw_screenshot.shape[0]
width = int(raw_screenshot.shape[1] * ratio)
height = int(raw_screenshot.shape[0] * ratio + 0.001)
raw_screenshot = cv2.resize(raw_screenshot, (width, height), interpolation=cv2.INTER_AREA)
screenshot = raw_screenshot.copy()
dogrulama_screenshot = raw_screenshot[203:446, 405:884, :]
return ratio, region, np.sum(dogrulama_screenshot[20:30, 0:100]) / \
np.prod(dogrulama_screenshot[20:30, 0:100].shape) < 20
def mainThread():
global stopApp, screenshot, active_window, metinThreadDone, resized, program_active
i = 0
while True:
program_active = 100
pack = updateScreenshotThread()
if pack is None:
time.sleep(0.5)
continue
ratio, region, validation_came = pack
active_window = GetWindowText(GetForegroundWindow())
if not validation_came:
if metinThreadDone and active_window == WINDOW_NAME and metinBOT:
metinThread = threading.Thread(target=metinBOTThread, args=(region, ratio,)).start()
time.sleep(0.1)
if resized is not None:
cv2.imshow("DOGRULAMA TESPIT", resized)
continue
if screenshot is None:
time.sleep(0.1)
continue
if active_window != WINDOW_NAME:
print(GetWindowText(GetForegroundWindow()))
cv2.imshow("DOGRULAMA TESPIT", resized)
if cv2.waitKey(1) == ord('x'):
stopApp=True
cv2.destroyAllWindows()
break
continue
text_img = dogrulama_screenshot[5:40, 50:400, :]
text = pytesseract.image_to_string(text_img, lang="tur")
max_val = 0
max_key = None
for key in imageDataset:
if max_val < string_benzerligi(key, text):
max_val = string_benzerligi(key, text)
max_key = key
image_to_compare = imageDataset[max_key]
resized = cv2.resize(dogrulama_screenshot, (dogrulama_screenshot.shape[1]*2, dogrulama_screenshot.shape[0]*2), interpolation=cv2.INTER_AREA)
resized = cv2.rectangle(resized, (100, 10), ((800, 80)), (0, 255, 0), 1)
slots = []
for j in range(9):
slots.append(cv2.resize(dogrulama_screenshot[45:165,10+j*52:50+j*52], (4, 12), interpolation=cv2.INTER_AREA))
min_fark = 9999999
match_idx = 0
for idx, slot in enumerate(slots):
if min_fark > mse_benzerligi(image_to_compare, slot):
match_idx = idx
min_fark = mse_benzerligi(image_to_compare, slot)
resized = cv2.rectangle(resized, (124, 90), ((204, 330)), (0, 255, 0), -1)
for j in range(9):
resized[90:330, 20+104*j:100+104*j] = cv2.resize(slots[j], (80, 240), interpolation=cv2.INTER_AREA)
for j in range(9):
if j == match_idx:
print(text)
print(max_key)
click(int(region['left'] + (405 + 30+j*52) * (1/ratio)),
int(region['top'] + (203 + 105) * (1/ratio))
)
time.sleep(0.1)
cv2.rectangle(resized, (20+j*104, 90), ((100+j*104, 330)), (0, 255, 0), 5)
else:
cv2.rectangle(resized, (20+j*104, 90), ((100+j*104, 330)), (255, 0, 0), 1)
font = cv2.FONT_HERSHEY_DUPLEX
fontScale = 2
thickness = 2
cv2.putText(resized, re.sub('[^A-Za-z]+', '', unidecode(text)), (200, 70), font,
fontScale, (0,255,0), thickness, cv2.LINE_AA)
cv2.putText(resized, unidecode(max_key), (100, 400), font,
fontScale, (0,255,0), thickness, cv2.LINE_AA)
cv2.imshow("DOGRULAMA TESPIT", resized)
if cv2.waitKey(1) == ord('x'):
cv2.destroyAllWindows()
stopApp=True
break
i += 1
if dereceBOT:
threading.Thread(target=dereceBOTThread).start()
mainThread()
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