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Beginner-friendly object detection projects using R-CNN and YOLOv3 with notebooks, utils, data, and pretrained models for hands-on learning.

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Object Detection Projects β€” R-CNN & YOLOv3

This repository contains two complete beginner-friendly object detection projects:

  • R-CNN (Region-Based Convolutional Neural Network)
  • YOLOv3 (You Only Look Once, Version 3)

Each project includes:

  • πŸ“˜ Jupyter Notebook β€” step-by-step implementation and explanation
  • 🧰 Utility functions β€” helper scripts for data processing and visualization
  • πŸ’Ύ Data β€” sample data to test and work with the models
  • 🧠 Pre-trained models β€” ready to use for inference or fine-tuning

πŸ” Overview

These projects are designed to help beginners understand and compare two of the most popular object detection architectures:

  • R-CNN: region-based approach focusing on accuracy
  • YOLOv3: real-time detection model focusing on speed

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Beginner-friendly object detection projects using R-CNN and YOLOv3 with notebooks, utils, data, and pretrained models for hands-on learning.

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