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

• 🎯 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

# 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()

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

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

Apache License 2.0