User Guide#
The User Guide covers the core deepforest package usage and functionalities.
Guides#
- Reading in Data
- Writing Data
- Prebuilt models
- Prediction
- The CropModel
- Extending the deepforest module
- Extending DeepForest with Custom Models and Dataloaders
- Can be passed directly to main.deepforest(existing_train_dataloader) or reassign to existing deepforest object
- Multi-species models
- Scaling DeepForest using PyTorch Lightning
- Visualization
- Config
- How do I make the predictions better?
- Check patch size
- IoU threshold
- Annotate local training data
- Training
- Evaluation
- Calculating Evaluation Metrics
- Annotation
- Please Make Your Annotations Open-Source!
- Working with deepforest data
- Make geospatial predictions on the full tile
- Tutorial for training a nest detection model
- DeepForest - ESA Stats Seminar - January 2025
- Download data
- Make initial predictions and view
- How many annotations do we need?
- The future of DeepForest
- Tutorial loading Deepforest
- Software & Research Using DeepForest
- Using DeepForest from R