deepforest 2.0.0rc1

Version 2.0.0rc1 (Date: October 23, 2025)

Release Candidate 1 - Beta Release

Breaking Changes - Deprecated Items Removed:

Removed Functions:

• xml_to_annotations() - Use utilities.read_pascal_voc(path) or the general utilities.read_file(path).
• boxes_to_shapefile() - Use image_to_geo_coordinates().
• project_boxes() - Use image_to_geo_coordinates().
• annotations_to_shapefile - Use image_to_geo_coordinates().
• plot_points() - Use plot_results
• draw_points() - Use plot_results
• plot_predictions() - Use plot_results
• draw_predictions() - Use plot_results
• use_release() - Use load_model('weecology/deepforest-tree') instead
• use_bird_release() - Use load_model('weecology/deepforest-bird') instead

Removed Parameters:

• geometry_type and save_dir from shapefile_to_annotations()
• num_classes and label_dict from deepforest() constructor - Use config file instead
• augment parameter from all functions - Use augmentations parameter instead
• raster_path parameter from predict_tile() - Use path parameter instead

Migration Guide:

• Replace xml_to_annotations(xml_path) with read_pascal_voc(xml_path)
• Replace boxes_to_shapefile(df, root_dir) with image_to_geo_coordinates(df, root_dir)
• Replace plot_points(image, points) with plot_results(results)
• Replace draw_points(image, points) with plot_results(results)
• Replace plot_predictions(image, df) with plot_results(results)
• Replace draw_predictions(image, df) with plot_results(results)
• Replace use_release() with load_model('weecology/deepforest-tree')
• Replace use_bird_release() with load_model('weecology/deepforest-bird')
• Use config file or config_args instead of constructor parameters
• Use augmentations parameter instead of augment parameter

Pytorch release

This a major version change transition from tensorflow backend to pytorch. The pytorch backend was previously in a different repo and pypi package deepforest-pytorch. Continued tensorflow updates means that the pinned 1.14.0 version for keras-retinanet (which itself is deprecated) is a real risk to package longevity. To avoid needing to patch upstream dependencies we are deprecating the tensorflow backend and moving to pytorch. The release

model score is very close, within 1% of the tensorflow model, and we do not expect significant performance changes. Please see the README for links to updating code and please submit an issues you may have as we transition to 1.0.

This release is the same as https://github.com/weecology/DeepForest-pytorch/releases/tag/v0.1.17

Conda Version Distribution

This release is inline with the first release of the conda build. The prebuilt model has not changed from previous release.

21SiteModel

Model training parameters: https://www.comet.ml/bw4sz/deepforest/fabe532d9e5f4edaa98edf0d2c080011

red is the new release, blue the previous release. Recall and precision for each of the sites in the NeonTreeEvaluation Benchmark

> summary_statistics(results,method="all")
# A tibble: 2 x 3
  Method                mean_precision mean_recall
  <chr>                          <dbl>       <dbl>
1 Weinstein_unpublished          0.617       0.726
2 Weinstein2019                  0.567       0.645

https://github.com/weecology/NeonTreeEvaluation

Python Package

This is the first model version - corresponding to Weinstein et al. 2019. Four site NEON model (NIWO, TEAK, SJER, MLBS sites) with pretraining and hand-annotations.