Release Deepforest v2.1.0 · weecology/DeepForest

Version 2.1.0 (Date: February 25, 2026)

The most important changes since 2.0.0:

Replace Albumentations with Kornia - Migrated augmentations to Kornia
CLI restructure - Split CLI into sub-scripts for clearer organization
Evaluation improvements - Refactored evaluation to support other geometries; migrated to torchmetrics
Prediction and training API - Simplified evaluation and prediction to mirror training; standardized train, eval and predict to accept lists not batches
Numpy 2.x support - Removed restriction to numpy<2.0
CropModel enhancements - Added macro-precision metric and expand context pixels for BoundingBoxDataset

Fix: Image color format when saving; now uses PIL instead of OpenCV to preserve colors
Fix: MultiImage dataset using same indices during batch processing
Fix: evaluate_boxes TypeError when ground truth has non-default index
Fix: DETR box coordinates
Fix: Support empty annotations in image callback
Fix: Detach losses when logging to avoid graph retention
Fix: CropModel docstring to match __init__ signature

Config: Added log_root config option; improved config handling; serialize dictconfig as plain data
read_file: Refactored for readability and to allow multiple image files; assume dataframe has root dir to simplify viz code
Bounding boxes: Add validation checks for boxes outside image boundaries
Compatibility: Block incompatible transformers versions; remove numpy<2.0 restriction
CropModel: Add expand context pixels for BoundingBoxDataset via cropmodel.expand config

Switch from tmpdir to tmp_path in tests
Add white-image model inference test; add regression test for HuggingFace model label_dict loading
Codecov test target and threshold; disable build failures from patch coverage diffs
New contributing guidelines and dev guidelines