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Hello guys, today i see one library in python with name OpenCV, this is a IA for recongite images on screen/webcam and more..
I think this is a good way to resolve problem with battleye service, because with python you can migrate a linux/osx app easy and when u debbug your code this generate another process name. here is my code, he's detect a item from png image (the item is cropped without borders and 15x15) and find cordinates in screen in x milisecond.
this is the teste.png for codes work, note read the firsts lines on code.
teste.png
I think this is a good way to resolve problem with battleye service, because with python you can migrate a linux/osx app easy and when u debbug your code this generate another process name. here is my code, he's detect a item from png image (the item is cropped without borders and 15x15) and find cordinates in screen in x milisecond.
Code:
import time
import pyautogui
import cv2
import numpy as np
from PIL import ImageGrab
#simple bot for detect Tibia item image on screen without inject in client
#You need only crop the image of item in 15x15 (for work)
#note i develope this for works on 1360x768 resolution if you need another change the bbox on ImageGrab().grab
#for completly use u need adapt this with win32gui (for get window rect/position)
#Thanks a lot.
#_JMG/Sleepy22
def imagesearch(image, precision=0.8):
im = ImageGrab.grab()
img_rgb = np.array(im)
img_gray = cv2.cvtColor(img_rgb, cv2.COLOR_BGR2GRAY)
w,h = image.shape[::-1]
res = cv2.matchTemplate(img_gray, image, cv2.TM_CCOEFF_NORMED)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
if max_val < precision:
return [-1,-1]
return max_loc
def imageinrange(image,precision,type):
if type == "ground":
im = ImageGrab.grab(bbox=(288, 85, 897, 529))
img_rgb = np.array(im)
img_gray = cv2.cvtColor(img_rgb, cv2.COLOR_BGR2GRAY)
w, h = image.shape[::-1]
res = cv2.matchTemplate(img_gray, image, cv2.TM_CCOEFF_NORMED)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
if max_val < precision:
return [-1, -1]
return max_loc[0]+288, max_loc[1]+85
else:
im = ImageGrab.grab(bbox=(1188, 40, 1360, 726))
img_rgb = np.array(im)
img_gray = cv2.cvtColor(img_rgb, cv2.COLOR_BGR2GRAY)
w, h = image.shape[::-1]
res = cv2.matchTemplate(img_gray, image, cv2.TM_CCOEFF_NORMED)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
if max_val < precision:
return [-1, -1]
return max_loc[0]+1188,max_loc[1]+40
def getground(image):
template = cv2.imread(image, 0)
template = cv2.resize(template, dsize=(19, 19), interpolation=cv2.INTER_CUBIC)
tp = imageinrange(template,0.8,'ground')
return tp
def getinventory(image):
template = cv2.imread(image, 0)
template = cv2.resize(template, dsize=(15, 15), interpolation=cv2.INTER_CUBIC)
tp = imageinrange(template, 0.8,'inventory')
return tp
def getall(image):
tp = getground(image)
if tp == [-1,-1]:
tp = getinventory(image)
return tp
time.sleep(3)
p = getall("teste.png")
pyautogui.moveTo(p[0],p[1])
teste.png
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