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run_agent.py
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run_agent.py
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import torch
import keyboard,time
model_name = r'./model/net_20 (3).pkl'
from queue import Queue
import pyautogui
import win32api
import win32con
from PIL import ImageGrab
import win32gui
from torchvision import transforms
from PIL import Image
from pynput.keyboard import Key, Controller
import time
# #
# handle = api.CSAPI(r"D:\PROJECT\BOT\api\csgo.json")
class KeyControll(object):
def __init__(self):
self.keyboard = Controller()
self.queue = Queue()
self.last_actions = []
def press_key(self, all_action_li):
for each_key in all_action_li:
self.keyboard.press(each_key)
self.last_actions = all_action_li
def release_key(self):
if not self.last_actions:
return
for each_key in self.last_actions:
self.keyboard.release(each_key)
class Aim(object):
def __init__(self):
window_handle = win32gui.FindWindow(None, u"Counter-Strike: Global Offensive - Direct3D 9")
win32gui.SetForegroundWindow(window_handle)
def set_aim(self, aim_list):
sensitivity = 2.5
m_pitch = 0.022
m_yaw = 0.022
pitch, yaw = aim_list
#print("aim_list", aim_list)
pixel_y = pitch / (sensitivity * m_pitch) # sensitivity = 2.5;m_pitch = 0.022
pixel_x = yaw / (sensitivity * m_yaw) # sensitivity = 2.5;m_yaw= 0.022
# y正的是向下走，这个跟内存中上负下正是一样的，因而取正值
# x的是往右走是正，这跟内存中是反过来的，取负值
win32api.mouse_event(win32con.MOUSEEVENTF_MOVE, -int(pixel_x), int(pixel_y), 0, 0)
def set_attack(self):
pyautogui.leftClick()
def set_attack2(self):
pyautogui.rightClick()
aim = Aim()
key_controll = KeyControll()
# time.sleep(0.124)
# def take_action(li):
tfms = transforms.Compose([transforms.Resize(128), transforms.ToTensor(),
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]), ])
hwnd = win32gui.FindWindow(None, u"Counter-Strike: Global Offensive - Direct3D 9")
frame_pool = [torch.zeros(size = (3,162,128)).half().cuda() for i in range(16)]
soft_max = torch.nn.Softmax()
from network_run import Net
with torch.no_grad():
# LOAD NET
state_dict = torch.load(model_name)
have_previous = True
net = Net(have_previous).half() # 16位精度训练
net.load_state_dict(state_dict)
net = net.cuda()
net.eval()
while True:
t0 = time.time()
if keyboard.is_pressed("q"):
time.sleep(1)
break
## run network
# catch frame\
dimensions = win32gui.GetWindowRect(hwnd)
image = ImageGrab.grab(dimensions)
# image.show()
image = tfms(image)
input = torch.permute(image, (0, 2, 1)).half().cuda()
frame_pool.append(input)
frame_pool = frame_pool[-16:]
input = torch.stack(frame_pool)
print("input shape", input.shape)
# forward
ouput = net(input)
win32gui.SetForegroundWindow(hwnd)
## take action
w,a,s,d,fire,scope,jump,crouch,walking,reload,e,switch,aim_x,aim_y = ouput
out = [w,a,s,d,fire,scope,jump,crouch,walking,reload,e,switch,aim_x,aim_y]
# print("w", w.shape)
#print("out", out)
#w,a,s,d,is_fire,is_scope,is_jump,is_crouch,is_walking,is_reload,is_e,switch
action = [torch.argmax(soft_max(a)).item() for a in out]
print(action[0], action)
## apply action
li = action
# out = [0 ,w,a,s,d,fire,scope,jump,crouch,walking,reload,e,switch, aim_x,aim_y]
# 0,w,a,s,d,is_fire,is_scope,is_jump,is_crouch,is_walking,is_reload,is_e,switch,aim_x,aim_y
li = [0] + li
print("action list", li)
w, a, s, d = li[1:5]
# 得到瞄准角度
mouse_x, mouse_y = li[-2:]
mouse_y_possibles = [-50.0, -40.0, -30.0, -20.0, -18.0, -16.0, -14.0, -12.0, -10.0, -8.0, -6.0, -5.0, -4.0,
-3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 8.0, 10.0, 12.0, 14.0, 16.0, 18.0,
20.0, 30.0, 40.0, 50.0]
mouse_x_possibles = [-170, -130, -100, -80, -70, -60, -50.0, -40.0, -30.0, -20.0, -18.0, -16.0, -14.0, -12.0,
-10.0, -8.0, -6.0, -5.0, -4.0, -3.0, -2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 8.0,
10.0, 12.0, 14.0, 16.0, 18.0, 20.0, 30.0, 40.0, 50.0, 60, 70, 80, 100, 130, 170]
try:
pix_x, pix_y = int(mouse_x_possibles[mouse_x]), int(mouse_y_possibles[mouse_y])
except IndexError:
print(mouse_x, mouse_y)
exit()
# 将行为映射成按键
is_fire, is_scope, is_jump, is_crouch, is_walking, is_reload, is_e, switch = li[5:-2]
action_li = []
if w:
action_li.append("w")
if a:
action_li.append("a")
if s:
action_li.append("s")
if d:
action_li.append("d")
if is_fire:
aim.set_attack()
if is_scope:
aim.set_attack2()
if is_jump:
action_li.append(" ")
if is_crouch:
action_li.append(Key.ctrl)
if is_walking:
action_li.append(Key.shift)
if is_reload:
action_li.append("r")
if is_e:
action_li.append("e")
action_li.append(str(switch))
# print("action_li", action_li)
# 瞄准
print("aim_li", [pix_y, pix_x])
aim.set_aim([pix_y, pix_x])
key_controll.release_key()
#time.sleep(abs(1 / 16 - (time.time() - t0)))
key_controll.press_key(action_li)
print("loop time cost: ", (time.time()-t0))
# time.sleep(1/16 - (time.time()-t0))