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@@ -47,9 +47,9 @@ $ pip install -U -r requirements.txt |
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## Tutorials |
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* <a href="https://colab.research.google.com/github/ultralytics/yolov5/blob/master/tutorial.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> |
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* [Train Custom Data](https://github.com/ultralytics/yolov5/wiki/Train-Custom-Data) |
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* [Google Colab Notebook](https://colab.research.google.com/github/ultralytics/yolov5/blob/master/tutorial.ipynb) with training, testing and testing examples |
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* [GCP Quickstart](https://github.com/ultralytics/yolov5/wiki/GCP-Quickstart) |
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* [Google Cloud Quickstart Guide](https://github.com/ultralytics/yolov5/wiki/GCP-Quickstart) |
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* [Docker Quickstart Guide](https://github.com/ultralytics/yolov5/wiki/Docker-Quickstart) |
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@@ -97,10 +97,8 @@ $ python train.py --data coco.yaml --cfg yolov5s.yaml --weights '' --batch-size |
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To access an up-to-date working environment (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled), consider a: |
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- **GCP** Deep Learning VM with $300 free credit offer: See our [GCP Quickstart Guide](https://github.com/ultralytics/yolov5/wiki/GCP-Quickstart) |
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- **Google Colab Notebook** with 12 hours of free GPU time: [Google Colab Notebook](https://colab.sandbox.google.com/github/ultralytics/yolov5/blob/master/tutorial.ipynb) |
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- **Docker Image** from https://hub.docker.com/r/ultralytics/yolov5. See [Docker Quickstart Guide](https://github.com/ultralytics/yolov5/wiki/Docker-Quickstart) |
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- **Google Colab Notebook** with 12 hours of free GPU time. <a href="https://colab.research.google.com/github/ultralytics/yolov5/blob/master/tutorial.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> |
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- **Docker Image** https://hub.docker.com/r/ultralytics/yolov5. See [Docker Quickstart Guide](https://github.com/ultralytics/yolov5/wiki/Docker-Quickstart) |
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## Citation |
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[![DOI](https://zenodo.org/badge/146165888.svg)](https://zenodo.org/badge/latestdoi/146165888) |