1
Run a pretrained demo
Start with a known image and inspect bounding boxes masks and scores.
Tutorials
Learning path for Detectron2
Follow a simple project path from environment setup to dataset registration and model evaluation.
2
Register a dataset
Prepare annotations and register train validation splits before training.
3
Train a baseline
Use a model zoo config then tune learning rate batch size iterations and augmentation.
4
Evaluate metrics
Review AP metrics plus qualitative predictions on hard examples.
5
Optimize inference
Measure latency and memory use before moving to production.
6
Document results
Keep configs checkpoints data versions and evaluation notes traceable.