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Documentation of methods, parameters, allowed values, term definitions, etc, etc #9584
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👋 Hello @jmiller-dr, thank you for your interest in YOLOv5 🚀! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution. If this is a 🐛 Bug Report, please provide screenshots and minimum viable code to reproduce your issue, otherwise we can not help you. If this is a custom training ❓ Question, please provide as much information as possible, including dataset images, training logs, screenshots, and a public link to online W&B logging if available. For business inquiries or professional support requests please visit https://ultralytics.com or email [email protected]. RequirementsPython>=3.7.0 with all requirements.txt installed including PyTorch>=1.7. To get started: git clone https://github.com/ultralytics/yolov5 # clone
cd yolov5
pip install -r requirements.txt # install EnvironmentsYOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):
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@jmiller-dr thanks for your feedback! Yes, docs are something have highlighted for improvement in our roadmap, particularly for the high level classes and functions. For custom python inference I'd recommend the PyTorch Hub tutorial, as this provides the most deployment flexibility and also offers many usage examples: Tutorials
Good luck 🍀 and let us know if you have any other questions! |
Thank you! Cheers
…On Sun, Sep 25, 2022 at 2:19 PM Glenn Jocher ***@***.***> wrote:
@jmiller-dr <https://github.com/jmiller-dr> thanks for your feedback!
Yes, docs are something have highlighted for improvement in our roadmap,
particularly for the high level classes and functions. For custom python
inference I'd recommend the PyTorch Hub tutorial
<https://docs.ultralytics.com/yolov5/tutorials/pytorch_hub_model_loading>, as this provides the
most deployment flexibility and also offers many usage examples:
Tutorials
- Train Custom Data
<https://docs.ultralytics.com/yolov5/tutorials/train_custom_data> 🚀
RECOMMENDED
- Tips for Best Training Results
<https://docs.ultralytics.com/yolov5/tutorials/tips_for_best_training_results>
☘️ RECOMMENDED
- Multi-GPU Training <https://docs.ultralytics.com/yolov5/tutorials/multi_gpu_training>
- PyTorch Hub <https://docs.ultralytics.com/yolov5/tutorials/pytorch_hub_model_loading> 🌟 NEW
- TFLite, ONNX, CoreML, TensorRT Export
<https://docs.ultralytics.com/yolov5/tutorials/model_export> 🚀
- Test-Time Augmentation (TTA)
<https://docs.ultralytics.com/yolov5/tutorials/test_time_augmentation>
- Model Ensembling <https://docs.ultralytics.com/yolov5/tutorials/model_ensembling>
- Model Pruning/Sparsity
<https://docs.ultralytics.com/yolov5/tutorials/model_pruning_and_sparsity>
- Hyperparameter Evolution
<https://docs.ultralytics.com/yolov5/tutorials/hyperparameter_evolution>
- Transfer Learning with Frozen Layers
<https://docs.ultralytics.com/yolov5/tutorials/transfer_learning_with_frozen_layers>
- Architecture Summary
<https://docs.ultralytics.com/yolov5/tutorials/architecture_description> 🌟 NEW
- Weights & Biases Logging
<https://github.com/ultralytics/yolov5/issues/1289>
- Roboflow for Datasets, Labeling, and Active Learning
<https://docs.ultralytics.com/yolov5/tutorials/roboflow_datasets_integration> 🌟 NEW
- ClearML Logging
<https://docs.ultralytics.com/yolov5/tutorials/clearml_logging_integration>
🌟 NEW
- Deci Platform
<https://github.com/ultralytics/yolov5/wiki/Deci-Platform> 🌟 NEW
- Comet Logging
<https://docs.ultralytics.com/yolov5/tutorials/comet_logging_integration>
🌟 NEW
Good luck 🍀 and let us know if you have any other questions!
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👋 Hello, this issue has been automatically marked as stale because it has not had recent activity. Please note it will be closed if no further activity occurs. Access additional YOLOv5 🚀 resources:
Access additional Ultralytics ⚡ resources:
Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed! Thank you for your contributions to YOLOv5 🚀 and Vision AI ⭐! |
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Description
There's a documentation webpage and some tutorials, but no actual documentation. Please provide documentation for each method, argument, etc.
Custom detection is particularly poorly documented and highly glossed over in the little tutorials.
Use case
No response
Additional
No response
Are you willing to submit a PR?
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