本文共 1442 字,大约阅读时间需要 4 分钟。
好处是
缺点是:
import timeimport win32gui, win32ui, win32con, win32apidef window_capture(filename): hwnd = 0 # 窗口的编号,0号表示当前活跃窗口 # 根据窗口句柄获取窗口的设备上下文DC(Divice Context) hwndDC = win32gui.GetWindowDC(hwnd) # 根据窗口的DC获取mfcDC mfcDC = win32ui.CreateDCFromHandle(hwndDC) # mfcDC创建可兼容的DC saveDC = mfcDC.CreateCompatibleDC() # 创建bigmap准备保存图片 saveBitMap = win32ui.CreateBitmap() # 获取监控器信息 MoniterDev = win32api.EnumDisplayMonitors(None, None) w = MoniterDev[0][2][2] h = MoniterDev[0][2][3] # print w,h #图片大小 # 为bitmap开辟空间 saveBitMap.CreateCompatibleBitmap(mfcDC, w, h) # 高度saveDC,将截图保存到saveBitmap中 saveDC.SelectObject(saveBitMap) # 截取从左上角(0,0)长宽为(w,h)的图片 saveDC.BitBlt((0, 0), (w, h), mfcDC, (0, 0), win32con.SRCCOPY) saveBitMap.SaveBitmapFile(saveDC, filename)beg = time.time()for i in range(10): window_capture("haha.jpg")end = time.time()print(end - beg)
输出结果为0.375秒,也就是说通过windows API每次截图只需要0.0375s,真是快得一逼呀。
import timefrom PIL import ImageGrabimport numpy as npimport cv2beg = time.time()debug = False# img = ImageGrab.grab(bbox=(250, 161, 1141, 610))img = ImageGrab.grab()end = time.time()print('time:',end - beg)img.show()img.save("screen.jpg")# PIL image to OpenCV imageim = np.array(img)cv2.imshow('cv image', im)cv2.waitKey()# OpenCV image to PIL imageim_pil = PIL.Image.fromarray(im)im_pil.show()
时间大概0.036秒,效率还是可以的。
参考:
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