Tennis_analysis

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Tennis_analysis is an open-source computer vision tool that analyzes tennis players in video to measure speed, ball shot speed, and number of shots. It uses YOLO for detection and CNNs for court keypoint extraction.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is tennis_analysis?

Tennis_analysis is an open-source project designed to analyze tennis players and ball movements within video footage. It leverages advanced computer vision techniques, including YOLO v8 for player detection and a fine-tuned YOLO model for tennis ball detection. Additionally, the tool utilizes Convolutional Neural Networks (CNNs) to accurately extract court keypoints, providing a comprehensive understanding of on-court activity. This project is ideal for individuals looking to enhance their machine learning and computer vision skills through a practical, hands-on application. It measures player speed, ball shot speed, and the total number of shots, offering valuable insights for performance analysis.

Best used for

Ideal for professors and fitness coaches who need to analyze tennis player performance, track ball shot speed, and count shots in video. Especially valuable for those looking to apply and polish their machine learning and computer vision skills in a sports analytics context.

Common actions

analyze tennis performance

detect players

track ball speed

extract court keypoints

develop computer vision

github copilot"AI Agents"open-sourcecollaborationface swappingworkflowsautomated workflowdeepfakelow-code/no-code

Capabilities

Key features

Player detection
Tennis ball detection
Court keypoint extraction
Measure player speed
Measure ball shot speed
Count number of shots

Target Audience

professorfitness coach

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What machine learning models does Tennis_analysis use for detection?

Tennis_analysis primarily uses YOLO v8 for player detection and a fine-tuned YOLO model specifically for tennis ball detection. It also incorporates CNNs for extracting crucial court keypoints from video footage, providing detailed analytical capabilities.

What are the main metrics Tennis_analysis can measure from a video?

The tool is designed to measure several key performance indicators from tennis videos. These include the speed of the tennis players, the speed of the ball shots, and the total number of shots played within the analyzed video segment.

What are the technical requirements to run Tennis_analysis?

To run Tennis_analysis, you will need Python 3.8, along with several libraries including ultralytics, pytorch, pandas, numpy, and opencv. The project is open-source, allowing for local setup and execution on compatible systems.

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Research & Education › Academic Research Coding & Development › Open Source & Models Data & Analytics › Statistical & Scientific

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