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Thinh Nguyen
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Merge pull request #86 from kabilar/main
Update GitHub Actions and Readme
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.github/workflows/release.yaml

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name: Release
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on:
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workflow_dispatch:
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jobs:
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make_github_release:
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uses: datajoint/.github/.github/workflows/make_github_release.yaml@main
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pypi_release:
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needs: make_github_release
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uses: datajoint/.github/.github/workflows/pypi_release.yaml@main
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secrets:
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TWINE_USERNAME: ${{secrets.TWINE_USERNAME}}
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TWINE_PASSWORD: ${{secrets.TWINE_PASSWORD}}
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with:
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UPLOAD_URL: ${{needs.make_github_release.outputs.release_upload_url}}
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mkdocs_release:
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uses: datajoint/.github/.github/workflows/mkdocs_release.yaml@main
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permissions:
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contents: write

.github/workflows/test.yaml

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name: Test
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on:
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push:
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pull_request:
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workflow_dispatch:
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schedule:
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- cron: "0 8 * * 1"
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jobs:
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tests:
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runs-on: ubuntu-latest
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strategy:
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matrix:
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py_ver: ["3.9", "3.10"]
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mysql_ver: ["8.0", "5.7"]
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include:
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- py_ver: "3.8"
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mysql_ver: "5.7"
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- py_ver: "3.7"
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mysql_ver: "5.7"
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steps:
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- uses: actions/checkout@v3
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- name: Set up Python ${{matrix.py_ver}}
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uses: actions/setup-python@v4
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with:
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python-version: ${{matrix.py_ver}}
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install flake8 "black[jupyter]"
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- name: Run style tests
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run: |
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python_version=${{matrix.py_ver}}
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black element_deeplabcut --check --verbose --target-version py${python_version//.}

.github/workflows/u24_element_before_release.yaml

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.github/workflows/u24_element_release_call.yaml

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.github/workflows/u24_element_tag_to_release.yaml

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CHANGELOG.md

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Observes [Semantic Versioning](https://semver.org/spec/v2.0.0.html) standard and
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[Keep a Changelog](https://keepachangelog.com/en/1.0.0/) convention.
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## [0.2.8] - 2023-08-07
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+ Update - GitHub Actions with new reusable workflows
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+ Update - Readme instructions
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## [0.2.7] - 2023-08-04
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+ Fix - Update the project path in the pose config file to train the model
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graciously provided by the Mathis Lab.
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+ Add - Support for 2d single-animal models
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[0.2.8]: https://github.com/datajoint/element-deeplabcut/releases/tag/0.2.8
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[0.2.7]: https://github.com/datajoint/element-deeplabcut/releases/tag/0.2.7
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[0.2.6]: https://github.com/datajoint/element-deeplabcut/releases/tag/0.2.6
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[0.2.5]: https://github.com/datajoint/element-deeplabcut/releases/tag/0.2.5

README.md

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# DataJoint Element - DeepLabCut
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[![PyPI version](https://badge.fury.io/py/element-deeplabcut.svg)](http://badge.fury.io/py/element-deeplabcut)
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# DataJoint Element for Pose Estimation with DeepLabCut
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DataJoint Element for markerless pose estimation with
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[DeepLabCut](https://www.deeplabcut.org/). DataJoint Elements collectively standardize
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and automate data collection and analysis for neuroscience experiments. Each Element is
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a modular pipeline for data storage and processing with corresponding database
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tables that can be combined with other Elements to assemble a fully functional pipeline.
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![diagram](https://raw.githubusercontent.com/datajoint/element-deeplabcut/main/images/diagram_flowchart.svg)
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## Experiment Flowchart
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![flowchart](https://raw.githubusercontent.com/datajoint/element-deeplabcut/main/images/flowchart.svg)
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## Data Pipeline Diagram
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![pipeline](https://raw.githubusercontent.com/datajoint/element-deeplabcut/main/images/pipeline.svg)
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## Getting Started
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+ Install from PyPI
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```bash
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pip install element-deeplabcut
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```
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+ [Interactive tutorial](https://github.com/datajoint/workflow-deeplabcut)
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+ [Documentation](https://datajoint.com/docs/elements/element-deeplabcut)
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## Support
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Installation and usage instructions can be found at the
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[Element documentation](https://datajoint.com/docs/elements/element-deeplabcut).
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+ If you need help getting started or run into any errors, please open a GitHub Issue
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or contact our team by email at support@datajoint.com.

docs/src/concepts.md

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to upstream Elements including Lab, Animal, and Session. For more detailed
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documentation on each table, see the API docs for the respective schemas.
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![element-deeplabcut diagram](https://raw.githubusercontent.com/datajoint/element-deeplabcut/main/images/diagram_dlc.svg)
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![pipeline](https://raw.githubusercontent.com/datajoint/element-deeplabcut/main/images/pipeline.svg)
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### `lab` schema ([API docs](../api/workflow_deeplabcut/pipeline/#workflow_deeplabcut.pipeline.Device))
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docs/src/index.md

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a modular pipeline for data storage and processing with corresponding database
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tables that can be combined with other Elements to assemble a fully functional pipeline.
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![diagram](https://raw.githubusercontent.com/datajoint/element-deeplabcut/main/images/diagram_flowchart.svg)
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![flowchart](https://raw.githubusercontent.com/datajoint/element-deeplabcut/main/images/flowchart.svg)
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Element DeepLabCut runs DeepLabCut which uses image recognition machine learning models
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to generate animal position estimates from consumer grade video equipment. The Element

element_deeplabcut/model.py

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"""
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processed_dir = get_dlc_processed_data_dir()
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output_dir = cls.infer_output_dir(
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{**video_recording_key, "model_name": model_name}, relative=False, mkdir=True
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{**video_recording_key, "model_name": model_name},
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relative=False,
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mkdir=True,
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)
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if task_mode is None:

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