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.github/ISSUE_TEMPLATE/bug_report.yml

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attributes:
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label: DeepLabCut version
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description: What version of DLC are you using? Please check with `import deeplabcut`, `deeplabcut.__version__`
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placeholder: 3.0.0rc8
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placeholder: 3.0.0rc9
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validations:
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required: true
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- type: dropdown

README.md

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_toc.yml

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- file: docs/installation
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- file: docs/recipes/installTips
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- file: docs/docker
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- caption: Main User Guides
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chapters:
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- file: docs/standardDeepLabCut_UserGuide
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- file: docs/maDLC_UserGuide
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- file: docs/Overviewof3D
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- file: docs/HelperFunctions
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- caption: Graphical User Interfaces (GUIs)
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chapters:
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- file: docs/gui/PROJECT_GUI
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- file: docs/beginner-guides/labeling
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- file: docs/beginner-guides/Training-Evaluation
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- file: docs/beginner-guides/video-analysis
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- caption: Hardware Tips
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- caption: 🚀 Main Demo Notebooks
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chapters:
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- file: docs/recipes/TechHardware
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- caption: DeepLabCut-Live!
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- file: examples/COLAB/COLAB_DEMO_SuperAnimal
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- file: examples/COLAB/COLAB_DEMO_mouse_openfield
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- file: examples/COLAB/COLAB_3miceDemo
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- file: examples/COLAB/COLAB_HumanPose_with_RTMPose
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- caption: 🚀 Notebooks For Your Data
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chapters:
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- file: docs/deeplabcutlive
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- caption: 🦄 DeepLabCut Model Zoo
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- file: examples/COLAB/COLAB_YOURDATA_SuperAnimal
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- file: examples/COLAB/COLAB_YOURDATA_TrainNetwork_VideoAnalysis
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- file: examples/COLAB/COLAB_YOURDATA_maDLC_TrainNetwork_VideoAnalysis
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- caption: 🚀 Special Feature Demos
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chapters:
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- file: docs/ModelZoo
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- file: docs/recipes/UsingModelZooPupil
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- file: examples/COLAB/COLAB_transformer_reID
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- file: examples/COLAB/COLAB_BUCTD_and_CTD_tracking
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- file: examples/JUPYTER/Demo_3D_DeepLabCut
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- file: examples/COLAB/COLAB_DLC_ModelZoo
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- caption: 🧑‍🍳 Cookbook (detailed helper guides)
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chapters:
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- file: docs/convert_maDLC
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- file: docs/recipes/flip_and_rotate
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- file: docs/recipes/pose_cfg_file_breakdown
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- file: docs/recipes/publishing_notebooks_into_the_DLC_main_cookbook
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- caption: Hardware Tips
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chapters:
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- file: docs/recipes/TechHardware
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- caption: DeepLabCut-Live!
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chapters:
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- file: docs/deeplabcutlive
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- caption: 🦄 DeepLabCut Model Zoo
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chapters:
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- file: docs/ModelZoo
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- file: docs/recipes/UsingModelZooPupil
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- caption: DeepLabCut Benchmarking
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chapters:
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- file: docs/benchmark
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- file: docs/pytorch/Benchmarking_shuffle_guide
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- caption: Mission & Contribute
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chapters:
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- file: docs/MISSION_AND_VALUES
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- file: docs/roadmap
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- file: docs/Governance
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- file: CONTRIBUTING
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- caption: Citations for DeepLabCut
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- file: docs/citation

conda-environments/DEEPLABCUT.yaml

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- pip:
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- torch
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- torchvision
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- deeplabcut[gui,modelzoo,wandb]==3.0.0rc8
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- deeplabcut[gui,modelzoo,wandb]==3.0.0rc9

conda-environments/README.md

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### Please head over to [Installation](/docs/installation.md) to see how to utilize our supplied conda envs!
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# Please head over to [Installation](/docs/installation.md) to see how to utilize our supplied conda envs!

deeplabcut/__init__.py

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)
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from deeplabcut.modelzoo.video_inference import video_inference_superanimal
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from deeplabcut.pose_estimation_pytorch.modelzoo.superanimal_humanbody_video_inference import analyze_videos_superanimal_humanbody
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from deeplabcut.utils import (
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create_labeled_video,

deeplabcut/compat.py

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Change batch size for inference; if given overwrites value in ``pose_cfg.yaml``.
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cropping: list or None, optional, default=None
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Currently not supported by the PyTorch engine.
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List of cropping coordinates as [x1, x2, y1, y2].
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Note that the same cropping parameters will then be used for all videos.
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If different video crops are desired, run ``analyze_videos`` on individual

deeplabcut/core/metrics/bbox.py

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from unittest.mock import Mock, patch
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from datetime import datetime
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import numpy as np
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try:
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coco.dataset["annotations"] = []
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coco.dataset["categories"] = [{"id": 1, "name": "animals", "supercategory": "obj"}]
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coco.dataset["images"] = []
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coco.dataset['info'] = {"description": "Generated by DeepLabCut","year": datetime.now().year,"date_created": datetime.now().strftime("%Y-%m-%d")}
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predictions = []
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for idx, (img, gt) in enumerate(ground_truth.items()):
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img_id = idx + 1

deeplabcut/create_project/modelzoo.py

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net_name: str | None = None,
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detector_name: str | None = None,
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):
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"""
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r"""
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Creates a new project directory, sub-directories and a basic configuration file.
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Change its parameters to your projects need.
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net_name: str | None = None,
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detector_name: str | None = None,
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):
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"""
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r"""
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Method used specifically for Pytorch-based ModelZoo models.
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createlabeledvideo: bool = True,
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trainFraction: float | None = None,
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):
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"""
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r"""
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Method used specifically for Tensorflow-based ModelZoo models.
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Creates a new project directory, sub-directories and a basic configuration file.

deeplabcut/create_project/new_3d.py

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def create_new_project_3d(project, experimenter, num_cameras=2, working_directory=None):
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"""Creates a new project directory, sub-directories and a basic configuration file for 3d project.
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r"""Creates a new project directory, sub-directories and a basic configuration file for 3d project.
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The configuration file is loaded with the default values. Adjust the parameters to your project's needs.
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>>> deeplabcut.create_new_project('reaching-task','Bill',2)
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Users must format paths with either: r'C:\ OR 'C:\\ <- i.e. a double backslash \ \ )
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Users must format paths with either: r'C:\ OR 'C:\\ <- i.e. a double backslash \\ )
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"""
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from datetime import datetime as dt

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