auto_aim_prov_single.py

import signal
import threading
import warnings
from multiprocessing import Pipe, Process

import cv2
import numpy as np
import pynput
import torch
import win32con
import win32gui

from auto_scripts.grabscreen import grab_screen
from auto_scripts.configs import *
# 创建一个命名窗口
from auto_scripts.get_model import load_model_infos
# loadConfig
from auto_scripts.mouse_controller import lock
# 消除警告信息
from utils.augmentations import letterbox
from utils.general import non_max_suppression, scale_coords, xyxy2xywh
from utils.plots import Annotator, colors

warnings.filterwarnings('ignore')
# loadModel
model, device, half = load_model_infos()

# 获取模型其他参
stride = int(model.stride.max())  # model stride
names = model.module.names if hasattr(model, 'module') else model.names  # get class names

# 锁开关
LOCK_MOUSE = False

# 鼠标控制
mouse = pynput.mouse.Controller()


# 点击监听
def on_click(x, y, button, pressed):
    global LOCK_MOUSE
    if pressed and button == button.x2:
        LOCK_MOUSE = not LOCK_MOUSE
        print('LOCK_MOUSE', LOCK_MOUSE)


if __name__ == '__main__':
    show_up = False
    show_tips = True
    listener = pynput.mouse.Listener(on_click=on_click)
    listener.start()
    while True:
        # 获取指定位置
        img0 = grab_screen(region=tuple(MONITOR.values()))

        # 将图片缩小指定大小
        img0 = cv2.resize(img0, (SCREEN_WIDTH, SCREEN_HEIGHT))

        # Padded resize
        img = letterbox(img0, IMGSZ, stride=stride)[0]

        # Convert
        img = img.transpose((2, 0, 1))[::-1]  # HWC to CHW, BGR to RGB
        img = np.ascontiguousarray(img)

        img = torch.from_numpy(img).to(device)
        img = img.half() if half else img.float()

        # 归一化处理
        img = img / 255.
        if len(img.shape) == 3:
            img = img[None]  # expand for batch dim

        pred = model(img, augment=False, visualize=False)[0]
        # NMS
        pred = non_max_suppression(pred, CONF_THRES, IOU_THRES, None, False, max_det=1000)
        aims = []
        for i, det in enumerate(pred):
            s = ''
            s += '%gx%g ' % img.shape[2:]  # print string
            gn = torch.tensor(img0.shape)[[1, 0, 1, 0]]  # normalization gain whwh
            # 设置方框绘制
            annotator = Annotator(img0, line_width=LINE_THICKNESS, example=str(names))
            if len(det):
                #  Rescale boxes from img_size to im0 size
                det[:, :4] = scale_coords(img.shape[2:], det[:, :4], img0.shape).round()

                # Write results
                for *xyxy, conf, cls in reversed(det):
                    # 获取类别索引
                    c = int(cls)  # integer class
                    # bbox 中的坐标
                    xywh = (xyxy2xywh(torch.tensor(xyxy).view(1, 4)) / gn).view(-1).tolist()  # normalized xywh

                    line = (c, *xywh)  # label format
                    aims.append(line)
                    # 图片绘制
                    label = SHOW_LABEL and names[c] or None
                    annotator.box_label(xyxy, label, color=colors(c, True))

        # 展示窗口
        if show_tips:
            print('传输坐标中 ...')
            show_tips = False
        if SHOW_IMG:
            cv2.namedWindow(SCREEN_NAME, cv2.WINDOW_NORMAL)
            # 重设窗口大小
            cv2.resizeWindow(SCREEN_NAME, RESIZE_X, RESIZE_Y)
            cv2.imshow(SCREEN_NAME, img0)

            if not show_up:
                hwnd = win32gui.FindWindow(None, SCREEN_NAME)
                win32gui.ShowWindow(hwnd, win32con.SW_SHOWNORMAL)
                win32gui.SetWindowPos(hwnd, win32con.HWND_TOPMOST, 0, 0, 0, 0,
                                      win32con.SWP_NOMOVE | win32con.SWP_NOACTIVATE | win32con.SWP_NOOWNERZORDER |
                                      win32con.SWP_SHOWWINDOW | win32con.SWP_NOSIZE)
                show_up = not show_up
            k = cv2.waitKey(1)
            if k % 256 == 27:
                cv2.destroyAllWindows()
                exit('结束进程中 ...')

        if aims and LOCK_MOUSE:
            t = threading.Thread(target=lock, args=(aims, mouse, GAME_X, GAME_Y), kwargs={'logitech': True})
            t.start()
            t.join()