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Browse files- .gitattributes +35 -0
- .github/workflows/check_file_size.yml +16 -0
- .github/workflows/sync_to_huggingface.yml +19 -0
- .gitignore +161 -0
- LICENSE +21 -0
- README.md +32 -0
- app.py +39 -0
- packages.txt +1 -0
- requirements.txt +5 -0
.gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.arrow filter=lfs diff=lfs merge=lfs -text
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*.bin filter=lfs diff=lfs merge=lfs -text
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*.bz2 filter=lfs diff=lfs merge=lfs -text
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*.ckpt filter=lfs diff=lfs merge=lfs -text
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*.model filter=lfs diff=lfs merge=lfs -text
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*.msgpack filter=lfs diff=lfs merge=lfs -text
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*.npy filter=lfs diff=lfs merge=lfs -text
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*.npz filter=lfs diff=lfs merge=lfs -text
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*.onnx filter=lfs diff=lfs merge=lfs -text
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*.ot filter=lfs diff=lfs merge=lfs -text
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*.parquet filter=lfs diff=lfs merge=lfs -text
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*.pb filter=lfs diff=lfs merge=lfs -text
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*.pickle filter=lfs diff=lfs merge=lfs -text
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*.pkl filter=lfs diff=lfs merge=lfs -text
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*.pt filter=lfs diff=lfs merge=lfs -text
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*.pth filter=lfs diff=lfs merge=lfs -text
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*.rar filter=lfs diff=lfs merge=lfs -text
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*.safetensors filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.tar.* filter=lfs diff=lfs merge=lfs -text
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*.tflite filter=lfs diff=lfs merge=lfs -text
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*.tgz filter=lfs diff=lfs merge=lfs -text
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*.wasm filter=lfs diff=lfs merge=lfs -text
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*.xz filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.jpg filter=lfs diff=lfs merge=lfs -text
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.github/workflows/check_file_size.yml
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name: Check file size
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on: # or directly `on: [push]` to run the action on every push on any branch
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pull_request:
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branches: [main]
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# to run this workflow manually from the Actions tab
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workflow_dispatch:
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jobs:
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sync-to-hub:
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runs-on: ubuntu-latest
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steps:
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- name: Check large files
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uses: ActionsDesk/lfs-warning@v2.0
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with:
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filesizelimit: 10485760 # this is 10MB so we can sync to HF Spaces
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.github/workflows/sync_to_huggingface.yml
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name: Sync to Hugging Face hub
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on:
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push:
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branches: [main]
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# to run this workflow manually from the Actions tab
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workflow_dispatch:
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jobs:
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sync-to-hub:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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with:
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fetch-depth: 0
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- name: Push to hub
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env:
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HF_TOKEN: ${{ secrets.HF_TOKEN }}
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run: git push --force https://alaaawad:$HF_TOKEN@huggingface.co/spaces/alaaawad/CLIPSeg_x_SD main
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.gitignore
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*.pth
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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cover/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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db.sqlite3-journal
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# Flask stuff:
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instance/
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.webassets-cache
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69 |
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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73 |
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docs/_build/
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# PyBuilder
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.pybuilder/
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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# For a library or package, you might want to ignore these files since the code is
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# intended to run in multiple environments; otherwise, check them in:
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# .python-version
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# pipenv
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# poetry
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99 |
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# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
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# This is especially recommended for binary packages to ensure reproducibility, and is more
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# commonly ignored for libraries.
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# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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#poetry.lock
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# pdm
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106 |
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
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107 |
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#pdm.lock
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# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
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# in version control.
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# https://pdm.fming.dev/#use-with-ide
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.pdm.toml
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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# SageMath parsed files
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*.sage.py
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# Environments
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124 |
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# pytype static type analyzer
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.pytype/
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# Cython debug symbols
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cython_debug/
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# PyCharm
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# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/
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LICENSE
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MIT License
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Copyright (c) 2022 Alaa
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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README.md
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---
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title: CLIPSeg X SD
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emoji: π
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colorFrom: yellow
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colorTo: gray
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sdk: gradio
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sdk_version: 3.12.0
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app_file: app.py
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pinned: false
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license: mit
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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It takes 3 mandatory inputs.
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Input Image URL
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Prompt of the part in the input image that you want to replace
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Output Prompt
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There are certain parameters that you can tune
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Mask Precision
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Stable Diffusion Generation Strength
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Prerequisites:
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* GPU (runs fine on Google Colab Tesla T4)
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Clipseg Model Weights - https://github.com/timojl/clipseg
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app.py
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from transformers import CLIPSegProcessor, CLIPSegForImageSegmentation
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import gradio as gr
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from PIL import Image
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import torch
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import matplotlib.pyplot as plt
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import cv2
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processor = CLIPSegProcessor.from_pretrained("CIDAS/clipseg-rd64-refined")
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model = CLIPSegForImageSegmentation.from_pretrained("CIDAS/clipseg-rd64-refined")
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def process_image(image, prompt):
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inputs = processor(text=prompt, images=image, padding="max_length", return_tensors="pt")
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# predict
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with torch.no_grad():
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outputs = model(**inputs)
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preds = outputs.logits
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filename = f"mask.png"
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plt.imsave(filename, torch.sigmoid(preds))
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return Image.open("mask.png").convert("RGB")
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title = "Interactive demo: zero-shot image segmentation with CLIPSeg"
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26 |
+
|
27 |
+
description = "Demo for using CLIPSeg, a CLIP-based model for zero- and one-shot image segmentation. To use it, simply upload an image and add a text to mask (identify in the image), or use one of the examples below and click 'submit'. Results will show up in a few seconds."
|
28 |
+
|
29 |
+
article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2112.10003'>CLIPSeg: Image Segmentation Using Text and Image Prompts</a> | <a href='https://huggingface.co/docs/transformers/main/en/model_doc/clipseg'>HuggingFace docs</a></p>"
|
30 |
+
|
31 |
+
interface = gr.Interface(fn=process_image,
|
32 |
+
inputs=[gr.Image(type="pil"), gr.Textbox(label="Please describe what you want to identify")],
|
33 |
+
outputs=gr.Image(type="pil"),
|
34 |
+
title=title,
|
35 |
+
description=description,
|
36 |
+
article=article)
|
37 |
+
|
38 |
+
interface.launch(debug=True)
|
39 |
+
|
packages.txt
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
python3-opencv
|
requirements.txt
ADDED
@@ -0,0 +1,5 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
git+https://github.com/huggingface/transformers.git
|
2 |
+
accelerate
|
3 |
+
git+https://github.com/huggingface/diffusers.git
|
4 |
+
torch
|
5 |
+
opencv-python
|