DetectX: Simple Yet Powerful Object Detection Framework

A lightweight and modular object detection framework powered by Detectron2, focusing on easy training and deployment.

Core Features

• 🎯 Pre-configured Detectron2 models (Faster R-CNN, RetinaNet)
• 🔄 Simple data pipeline for custom datasets
• 📊 Built-in evaluation metrics (COCO metrics, RMSE, MSE, PSNR)
• 🚀 Easy model configuration and training

Quick Start

# Install dependencies
pip install -r requirements.txt

# Train a model
from Model.modelling.detectron2 import Detectron2

model = Detectron2(
    model="COCO-Detection/faster_rcnn_X_101_32x8d_FPN_3x.yaml",
    max_iter=500,
    base_lr=0.00025
)
model.train()

Project Structure

ML/
├── Model/
│   ├── modelling/       # Core model implementations
│   ├── dataset/         # Dataset handling utilities
│   └── metrics/         # Evaluation metrics
└── tests/              # Unit tests

Currently Supported

• Models: Faster R-CNN, RetinaNet
• Metrics: COCO AP, RMSE, MSE, PSNR
• Data formats: COCO-style annotations
• GPU acceleration with CUDA

License

Apache License 2.0