from unittest import result
import torch
import pyautogui
import gc
import numpy as np
import cv2
import time
import mss
import win32api, win32con
import dxcam

def main():
    # Window title to go after and the height of the screenshots
    videoGameWindowTitle = "Rainbow Six"

    # Portion of screen to be captured (This forms a square/rectangle around the center of screen)
    screenShotHeight = 320
    screenShotWidth = 320

    # How big the Autoaim box should be around the center of the screen
    aaDetectionBox = 320

    # For use in games that are 3rd person and character model interferes with the autoaim
    # EXAMPLE: Fortnite and New World
    aaRightShift = 0

    # Autoaim mouse movement amplifier
    aaMovementAmp = 1.1

    # Person Class Confidence
    confidence = 0.5

    # What key to press to quit and shutdown the autoaim
    aaQuitKey = "B"

    # If you want to main slightly upwards towards the head
    headshot_mode = False

    # Displays the Corrections per second in the terminal
    cpsDisplay = False

    # Set to True if you want to get the visuals
    visuals = True

    # Selecting the correct game window
    try:
        videoGameWindows = pyautogui.getWindowsWithTitle(videoGameWindowTitle)
        videoGameWindow = videoGameWindows[0]
    except:
        print("The game window you are trying to select doesn't exist.")
        print("Check variable videoGameWindowTitle (typically on line 13")
        exit()

    # Select that Window
    videoGameWindow.activate()

    # Setting up the screen shots
    left,top,=aaRightShift + ((videoGameWindow.left + videoGameWindow.right) // 2 - (screenShotWidth // 2)),videoGameWindow.top + (videoGameWindow.height - screenShotHeight) // 2,

    width,height=screenShotWidth,screenShotHeight

    sctArea=(left,top,width,height)

    
    # Starting screenshoting engine
    sct = dxcam.create()

    # Calculating the center Autoaim box
    cWidth = width / 2
    cHeight = height / 2

    # Used for forcing garbage collection
    count = 0
    sTime = time.time()

    # Loading Yolo5 Small AI Model
    model = torch.hub.load('WongKinYiu/yolov7','custom','yolov7-tiny.pt')
    model.classes = [0]

    # Used for colors drawn on bounding boxes
    COLORS = np.random.uniform(0, 255, size=(1500, 3))

    # Main loop Quit if Q is pressed
    last_mid_coord = None
    aimbot=False

    while win32api.GetAsyncKeyState(ord(aaQuitKey)) == 0:
        # Getting screenshop, making into np.array and dropping alpha dimention.
        npImg = np.delete(np.array(sct.grab(sctArea)))