Streamlit based Automatic Number Plate Recognition 🚘🚙

A streamlit based implementation of Automatic Number Plate Recognition for cars and other vehicles using images or live camera feed.

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This work is just an extended implementation of the great work done by mftnakrsu

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Installation:

• Simply run the command pip install -r requirements.txt to install the necessary dependencies.

Usage:

1. Clone this repository and install the dependencies as mentioned above.
2. Make a directory within this cloned repository with the name .streamlit (Don't forget the dot !!).
3. Create a file config.toml in this directory (Be aware of the file extension !!).
4. Copy-Paste the following contents in this file and save :

[theme]
primaryColor="#ffb5b5"
backgroundColor="#132743"
secondaryBackgroundColor="#407088"
textColor="#ffb5b5"

5. Navigate to the root directory of this repository and simply run the command:

streamlit run app.py

Navigate to http://localhost:8501 in your web-browser.

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Results

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Output Images	Output Images

Running the Dockerized App

1. Ensure you have Docker Installed and Setup in your OS (Windows/Mac/Linux). For detailed Instructions, please refer this.
2. Navigate to the folder where you have cloned this repository ( where the Dockerfile is present ).
3. Build the Docker Image (don't forget the dot!! 😄 ):

docker build -f Dockerfile -t app:latest .

4. Run the docker:

docker run -p 8501:8501 app:latest

This will launch the dockerized app. Navigate to http://localhost:8501/ in your browser to have a look at your application. You can check the status of your all available running dockers by:

docker ps