26 lines
1.3 KiB
Markdown
26 lines
1.3 KiB
Markdown
## keras-yolo3 with Roboflow
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[](LICENSE)
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A Keras implementation of YOLOv3 (Tensorflow backend) inspired by [allanzelener/YAD2K](https://github.com/allanzelener/YAD2K).
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## What You Will Learn
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* How to load your custom image detection data from Roboflow
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* How set up the YOLOv3 model in keras
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* How to train the YOLOv3 model
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* How to use the model for inference
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* How to save the keras model weights for future use
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## Resources
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* [This blog post](https://blog.roboflow.ai/training-a-yolov3-object-detection-model-with-a-custom-dataset/) provides a deep dive into the tutorial
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* This notebook provides the code necessary to run the tutorial [](https://colab.research.google.com/drive/1ByRi9d6_Yzu0nrEKArmLMLuMaZjYfygO#scrollTo=WgHANbxqWJPa)
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* For reading purposes, the notebook is also saved in Tutorial.ipynb
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## About Roboflow for Data Management
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[Roboflow](https://roboflow.ai) makes managing, preprocessing, augmenting, and versioning datasets for computer vision seamless.
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Developers reduce 50% of their code when using Roboflow's workflow, automate annotation quality assurance, save training time, and increase model reproducibility.
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
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