# Ignore large/local datasets
/data/
/docs/examples/data/

# Artifacts not to commit
/neon_training_annotations.zip
/data_prep/images_annotated/
/data_prep/images_to_annotate/
/data_prep/AutoArborist/
/data_prep/neon_token.txt
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class

# C extensions
*.so

docs/examples/data

# Distribution / packaging
.Python
build/
develop-eggs/
dist/
downloads/
eggs/
.eggs/
lib/
lib64/
parts/
sdist/
var/
wheels/
share/python-wheels/
*.egg-info/
.installed.cfg
*.egg
MANIFEST
*uv.lock*

# PyInstaller
#  Usually these files are written by a python script from a template
#  before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest
*.spec

# Installer logs
pip-log.txt
pip-delete-this-directory.txt

# Unit test / coverage reports
htmlcov/
.tox/
.nox/
.coverage
.coverage.*
.cache
nosetests.xml
coverage.xml
*.cover
*.py,cover
.hypothesis/
.pytest_cache/
cover/

# Translations
*.mo
*.pot

# Django stuff:
*.log
local_settings.py
db.sqlite3
db.sqlite3-journal

# Flask stuff:
instance/
.webassets-cache

# Scrapy stuff:
.scrapy

# Sphinx documentation
docs/_build/

# PyBuilder
.pybuilder/
target/

# Jupyter Notebook
.ipynb_checkpoints

# IPython
profile_default/
ipython_config.py

# pyenv
#   For a library or package, you might want to ignore these files since the code is
#   intended to run in multiple environments; otherwise, check them in:
# .python-version

# pipenv
#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
#   However, in case of collaboration, if having platform-specific dependencies or dependencies
#   having no cross-platform support, pipenv may install dependencies that don't work, or not
#   install all needed dependencies.
#Pipfile.lock

# poetry
#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
#   This is especially recommended for binary packages to ensure reproducibility, and is more
#   commonly ignored for libraries.
#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
#poetry.lock

# pdm
#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
#pdm.lock
#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
#   in version control.
#   https://pdm.fming.dev/#use-with-ide
.pdm.toml

# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
__pypackages__/

# Celery stuff
celerybeat-schedule
celerybeat.pid

# SageMath parsed files
*.sage.py

# Environments
.env
.venv
env/
venv/
ENV/
env.bak/
venv.bak/

# Spyder project settings
.spyderproject
.spyproject

# Rope project settings
.ropeproject

# mkdocs documentation
/site

# mypy
.mypy_cache/
.dmypy.json
dmypy.json

# Pyre type checker
.pyre/

# pytype static type analyzer
.pytype/

# Cython debug symbols
cython_debug/

# PyCharm
#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
#  and can be added to the global gitignore or merged into this file.  For a more nuclear
#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/
 

# MacOS
*.DS_store*

# Ignore large/local datasets
/data/
/docs/examples/data/
/data_prep/images_annotated/
/data_prep/AutoArborist/
/data_prep/neon_token.txt
/neon_training_annotations.zip
# IDE
/.vscode/

# Local training run artifacts (outputs, checkpoints, lightning logs, SLURM logs)
training/*/outputs/
training/*/outputs_*/
training/*/mini_test/
training/**/lightning_logs/
slurm/**/*.out
training/slurm/*.out
existing_models/*/outputs/

# Comet ML credentials (copy .comet.config.example to .comet.config)
.comet.config

# Local logs directory
/logs/

# Local Word output (not tracked)
/docs/NEON_combined_crowns_TAC_workflow.docx

# Ignore large/local datasets
/data/
/docs/examples/data/
/data_prep/images_annotated/
/data_prep/AutoArborist/
/data_prep/neon_token.txt
/neon_training_annotations.zip
# IDE
/.vscode/

# HuggingFace token (secret, never commit)
.hf_token

# Local run artifacts: model outputs, checkpoints, logs, scratch downloads.
# These are regenerated by the training/eval/packaging scripts and are far too
# large to version (ofo_downloads and treeformer_sam2 are >10 GB each).
/outputs/
/public/
/lightning_logs/
/ofo_downloads/
/q
slurm-*.out
existing_models/treeformer/private_data/
existing_models/treeformer_sam2/
training/weak_supervision/outputs/
training/polygons/detectron2_assets/
existing_models/*/outputs_ap_iou/

# Per-image diagnostic renders backing docs/validation_ap_completeness.md.
# The contact sheets that the doc actually embeds are tracked; the ~286 GB of
# per-image overlays behind them (~286 MB) are not.
docs/public/validation_completeness/boxes/
docs/public/validation_completeness/polygons/
