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Releases: AlbertoMarquillas/anpr-license-plate-recognition

v0.1.0 – Initial structured release

07 Sep 22:52
@AlbertoMarquillas AlbertoMarquillas
v0.1.0
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📖 Summary

First structured, portfolio-ready release of anpr-license-plate-recognition.
Includes full ANPR pipeline with YOLOv3 (OpenCV DNN) for detection and EasyOCR for text recognition, packaged in a professional repository structure.

✅ Included

  • Standard folder layout (src/, test/, docs/, data/, models/, configs/, build/).
  • MIT License and Python-focused .gitignore.
  • Source code (src/main.py, src/util.py) with CLI and PowerShell examples.
  • Configuration file (configs/default.yaml) with paths and thresholds.
  • Detailed README.md with badges, installation, and usage instructions.
  • Documentation for datasets (data/README.md) and models (models/README.md).
  • Release assets with model weights split into .rar parts.

❌ Excluded

  • Large dataset samples (place them under data/ following instructions).
  • Full model weights in repo history (provided only as Release assets).

📥 Model Weights

Download the following assets from this release and place them inside the models/ folder:

  • model.rar

Then extract using [WinRAR](https://www.win-rar.com/) or [7-Zip](https://www.7-zip.org/). The extractor will recompose the full file into:

models/weights/model.weights

🚀 Notes

  • Tested on Python 3.10+ with opencv-python, easyocr, numpy, pyyaml.

  • Requires Tesseract OCR installed and accessible in PATH.

  • Run the pipeline with:

    python .\src\main.py --save --show
Assets 3
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