• ClipSaver
ClipSaver
Русские видео
  • Смешные видео
  • Приколы
  • Обзоры
  • Новости
  • Тесты
  • Спорт
  • Любовь
  • Музыка
  • Разное
Сейчас в тренде
  • Фейгин лайф
  • Три кота
  • Самвел адамян
  • А4 ютуб
  • скачать бит
  • гитара с нуля
Иностранные видео
  • Funny Babies
  • Funny Sports
  • Funny Animals
  • Funny Pranks
  • Funny Magic
  • Funny Vines
  • Funny Virals
  • Funny K-Pop

Fast Window Capture - OpenCV Object Detection in Games #4 скачать в хорошем качестве

Fast Window Capture - OpenCV Object Detection in Games #4 5 years ago

opencv

python

opencv video capture python

windows game capture

real time image

real time image processing

opencv video capture

capture screen

screenshot python

python record window

swapping through frame

imagegrab

pywin32

opencv tutorial

computer vision tutorial

real time window capture

capturing screen

real time screen capture python

screen reading python

opencv window capture

computer vision beginner tutorial

programming tutorial

grab screen

Не удается загрузить Youtube-плеер. Проверьте блокировку Youtube в вашей сети.
Повторяем попытку...
Fast Window Capture - OpenCV Object Detection in Games #4
  • Поделиться ВК
  • Поделиться в ОК
  •  
  •  


Скачать видео с ютуб по ссылке или смотреть без блокировок на сайте: Fast Window Capture - OpenCV Object Detection in Games #4 в качестве 4k

У нас вы можете посмотреть бесплатно Fast Window Capture - OpenCV Object Detection in Games #4 или скачать в максимальном доступном качестве, видео которое было загружено на ютуб. Для загрузки выберите вариант из формы ниже:

  • Информация по загрузке:

Скачать mp3 с ютуба отдельным файлом. Бесплатный рингтон Fast Window Capture - OpenCV Object Detection in Games #4 в формате MP3:


Если кнопки скачивания не загрузились НАЖМИТЕ ЗДЕСЬ или обновите страницу
Если возникают проблемы со скачиванием видео, пожалуйста напишите в поддержку по адресу внизу страницы.
Спасибо за использование сервиса ClipSaver.ru



Fast Window Capture - OpenCV Object Detection in Games #4

Learn how to capture window data in real-time as a video stream for processing with OpenCV. We try several different methods searching for the fastest way possible. In this tutorial I also discuss the importance of good Google search skills as a programmer, and we revisit some basic object-oriented programming concepts. Full tutorial playlist:    • OpenCV Object Detection in Games   Grab the code on GitHub: https://github.com/learncodebygaming/... Research discussed: OpenCV getting started with videos: https://docs.opencv.org/4.2.0/dd/d43/... Fastest way to take a screenshot with Python on Windows: https://stackoverflow.com/a/3586280/1... Convert PyAutoGUI image to OpenCV: https://stackoverflow.com/q/32918978/... Convert SaveBitmapFile to an OpenCV image instead: https://stackoverflow.com/q/41785831/... Best Numpy reference: https://numpy.org/doc/1.18/user/quick... List all your windows: https://stackoverflow.com/q/55547940/... 0:47 Main capture loop 3:16 Using PyAutoGUI screenshot() 6:24 Measure FPS 8:27 Using Pillow ImageGrab 9:31 Using Pywin32 for screenshots 13:48 Converting win32ui.CreateBitmap() for OpenCV 17:23 Confining screenshots to a specific window 18:42 Creating a WindowCapture class 25:05 Trimming the window capture 28:15 Image to screen position conversion 29:35 Wrap up Read the full written tutorial with code samples here: https://learncodebygaming.com/blog/fa... Up to this point, we've been using OpenCV to detect objects in static images. Now we're ready to apply those same techniques to video games in real time. Remember that video is just a series of still images shown in rapid succession. In this tutorial our goal is to capture screenshots as fast as possible and display them in an OpenCV window, so that we get a real time video stream of the game we're interested in. This will set us up to begin processing image data with OpenCV in real-time. OpenCV has a tutorial on "Getting Started with Videos" that will serve as the basis for our code. Our starting point differs from the official tutorial only in that we are preparing to work with screenshot data instead of frames from a camera. When defining get_screenshot() you could simply use pyautogui.screenshot() from the PyAutoGUI library, or ImageGrab.grab() from the Python Image Library. And this would work, but there are several benefits to calling the Windows API directly instead. Firstly, we approach the theoretical limit for how fast we can take these screenshots by dealing right with the operating system itself. Secondly, the Windows API has methods that will allow us to grab the screen data for only the window we're interested in, even when it's minimized or off screen. To do this, we must first pip install pywin32 to get access to the Win32 API in Python. Let's start with some code to capture a single screenshot of our entire desktop and save that to a file. This will confirm for us that the Windows API calls are working. By calling this function, you should end up with a debug.bmp screenshot file. The next step is to modify this function so that instead of saving an image file, it instead returns the image data, formatted to work with OpenCV. Now we can call this function from our original infinite loop and get a real-time stream of our desktop. To improve upon this, we can use win32gui.FindWindow(None, window_name) to capture just the window we're interested in. Replace the window_name with a string that contains the name found in the title bar of the window you want to capture. Doing so will allow you to capture the frames from that window even when it's hidden behind other windows. If you're having trouble figuring out the name of the window you want, you can use this code to list the names of all your existing windows: We can improve our code further by trimming off the excess around the window we're interested in. When you run the above code, you will notice black space to the right and below the window image, as well as the window borders and title bar. Removing these will not only clean things up, it will also improve our frame rate. We can also get improvements by not calling win32gui.FindWindow() on every call to get_screenshot(), so let's turn this into a class. Finally, we'll need a way to convert positions we detect in our screenshots back to pixel positions on our actual monitor. In the WindowCapture class constructor, I've already included code to calculate the window offset using the window position data from win32gui.GetWindowRect(). Let's add a method to our class that uses this offset to return that converted screen position. Continue with the written tutorial here: https://learncodebygaming.com/blog/fa...

Comments
  • Real-time Object Detection - OpenCV Object Detection in Games #5 4 years ago
    Real-time Object Detection - OpenCV Object Detection in Games #5
    Опубликовано: 4 years ago
    102740
  • OpenCV Object Detection in Games Python Tutorial #1 5 years ago
    OpenCV Object Detection in Games Python Tutorial #1
    Опубликовано: 5 years ago
    293789
  • I tried to make a Valorant AI using computer vision 4 years ago
    I tried to make a Valorant AI using computer vision
    Опубликовано: 4 years ago
    1665205
  • LEARN OPENCV in 3 HOURS with Python | Including 3xProjects | Computer Vision 5 years ago
    LEARN OPENCV in 3 HOURS with Python | Including 3xProjects | Computer Vision
    Опубликовано: 5 years ago
    3533003
  • ИНФОУГРОЗЫ. ЭТО видео МЕНЯЕТ сознание (на 3 МЕСЯЦА) — ТОПЛЕС 22 hours ago
    ИНФОУГРОЗЫ. ЭТО видео МЕНЯЕТ сознание (на 3 МЕСЯЦА) — ТОПЛЕС
    Опубликовано: 22 hours ago
    1087278
  • Less talk....  more action. / Lo-fi for study, work ( with Rain sounds) 1 month ago
    Less talk.... more action. / Lo-fi for study, work ( with Rain sounds)
    Опубликовано: 1 month ago
    1346651
  • Северная Корея - о чем врут и блогеры, и пропаганда! Реальная жизнь, Часть ПЕРВАЯ! @staspognali 4 days ago
    Северная Корея - о чем врут и блогеры, и пропаганда! Реальная жизнь, Часть ПЕРВАЯ! @staspognali
    Опубликовано: 4 days ago
    826201
  • How to Train YOLO Object Detection Models in Google Colab (YOLO11, YOLOv8, YOLOv5) 4 months ago
    How to Train YOLO Object Detection Models in Google Colab (YOLO11, YOLOv8, YOLOv5)
    Опубликовано: 4 months ago
    153946
  • Game Automation with YOLOv8: Python Bot Tutorial 1 year ago
    Game Automation with YOLOv8: Python Bot Tutorial
    Опубликовано: 1 year ago
    78054
  • Python Object Oriented Programming (OOP) - Full Course for Beginners 4 months ago
    Python Object Oriented Programming (OOP) - Full Course for Beginners
    Опубликовано: 4 months ago
    156868

Контактный email для правообладателей: [email protected] © 2017 - 2025

Отказ от ответственности - Disclaimer Правообладателям - DMCA Условия использования сайта - TOS



Карта сайта 1 Карта сайта 2 Карта сайта 3 Карта сайта 4 Карта сайта 5