/object-detection-optimization

Efficient Object Detection Model Optimization

Primary LanguagePython

Optimization Strategies for Object Detection Models

This repository is dedicated to adding different optimization strategies for object detection models. The aim is to enhance real-time inference capabilities while balancing speed and accuracy, even with limited hardware resources.

Contents

  1. YOLOv8 for Real-Time Inference
    Optimizing YOLOv8 to achieve real-time inference with reduced hardware requirements. This includes techniques to balance speed and accuracy using fewer hardware resources.
    Go to YOLOv8 Optimization Documentation

    Go to YOLOv8 Optimization Code

  1. Surveillance Setup with 4 Video Sources
    A detailed explanation of setting up a surveillance system with four concurrent video feeds. This setup demonstrates how multiple video sources can work concurrently, optimized for real-time processing.
    Go to Surveillance Setup Documentation

    Go to Surveillance Setup Code

  1. 𝐘𝐎𝐋𝐎-𝐁𝐚𝐭𝐭𝐥𝐞𝐟𝐢𝐞𝐥𝐝 ⚠️🔥
    Compare YOLO models and find out the best one for your application. Try this on Huggingface Spaces

    𝐘𝐎𝐋𝐎-𝐁𝐚𝐭𝐭𝐥𝐞𝐟𝐢𝐞𝐥𝐝 Code