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Built with YOLOv3 and PyQt. + FLASK \n### Setup\nInstall [Python](https://www.python.org/downloads/) Use Python 3.8.\n\nClone this repository, cd to its directory and run the following commands:\n```\n# Create and activate a new virtual environment\n$ python -m venv env\n\n## Windows\n$ ./env/Scripts/activate\n## Linux\n$ source ./env/bin/activate\n\n# Install the project's requirements\n$ pip install -r ./requirements.txt\n```\n\nBefore running the project, you will need the trained weights. Considering the size of the weights and that Git LFS has a monthly limit on bandwidth, you will have to download the latest [release](https://github.com/HamzaEzzRa/MLPDR/releases/tag/v1.0.0-beta) and copy the weights folder to the cloned project.\n\n```\n# Run the project\n$ python ./main.py\n$ python ./api.py # to run the API\n$ python ./client.py # client side code to send the picture \n```\n\n### Screenshots\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://i.imgur.com/f7evHhw.png\" /\u003e  \n\u003c/p\u003e\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"https://thumbs2.imgbox.com/d9/5f/uvjtaIeO_t.png\" /\u003e\n  \n\u003c/p\u003e\n\n### Dataset\nThe network has been trained on the Moroccan license plate dataset: [https://msda.um6p.ma/msda_datasets](https://msda.um6p.ma/msda_datasets).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhamzaezzra%2Fmlpdr","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhamzaezzra%2Fmlpdr","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhamzaezzra%2Fmlpdr/lists"}