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此為由Python編寫的程式,旨在分析影片中的網球選手,測量其速度、球速和擊球次數。 通過輸入的網球對打影片,該程式通過 YOLO 進行網球及球員的偵測,且利用 CNNs 提取網球場的 Key Points,接著透過 Pandas 進行分析工作。

Python 21.99% Jupyter Notebook 78.01%

tennnis_analysis_system_yolov's Introduction

YOLOv8 Tennis Analysis System

Table of contents

About the Program

一個用Python編寫的程式,旨在分析影片中的網球選手,測量其速度、球速和擊球次數。

通過輸入的網球對打影片,該程式通過 YOLO 進行網球及球員的偵測,且利用 CNNs 提取網球場的 Key Points,接著透過 Panda 進行分析工作。

Getting Started - Steps by Steps

Environments

此程式可以在 Windows 和 MacOS 系統上運行,在 Python IDE 中執行。

Install python

使用 Python 3 執行此程式。(download python

Install Other Libraries

該程式需要在 Python 中安裝

  1. OpenCV 套件,通過執行以下指令來安裝:

    pip3 install opencv-python
  2. YOLO ,通過執行以下指令來安裝:

    pip3 install ultralytics
  3. RoboFlow ,通過執行以下指令來安裝:

    pip3 install roboflow
  4. PyTorch

  5. Numpy ,通過執行以下指令來安裝:

    pip3 install numpy
  6. Pandas ,通過執行以下指令來安裝:

    pip3 install pandas

How to Use the Program

Clone This Repo

可以使用各種源代碼管理工具,例如 Source Tree 和 GitHub Desktop 複製此存儲庫,或者執行以下指令:

git clone https://github.com/jeannie068/Tennnis_Analysis_System_YOLOv8.git

Running the Program

只需執行 main.py 腳本即可產生結果,

python3 main.py

Result and Test

程式執行成功後,會在相對路徑: "output_video/output_video.avi" 中看到 avi 影片,其中包含了球員速度、球員擊球球速和球員擊球次數等數據,以及球員、球的物體偵測,以及球員與球**中的平面位置。

影片最終結果如圖: image

Issue

  • Analysis ball bouncing and show on mini-court
  • Ball tracker model from YOLOv5 change to TrackNet Model

tennnis_analysis_system_yolov's People

Contributors

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