Detectron2 Instance Segmentation

Streamlit App that performs object detection and instance segmentation powered by Detectron2.

Dependencies

Running the application can be done following the instructions above:

1. To create a Python Virtual Environment (virtualenv) to run the code, type:

   python3 -m venv my-env

2. Activate the new environment:

   • Windows: my-env\Scripts\activate.bat
   • macOS and Linux: source my-env/bin/activate

3. Install all the dependencies from requirements.txt:

   pip install -r requirements.txt

Use

Within the virtual environment:

streamlit run app.py

A web application will open in the prompted URL. The user should upload an image file (jpg, jpeg, png) with the button available. Then, the image will be fed to a model which will output tehe original image with the detections drawn on it.

There's another app:

streamlit run app_discriminative.py

It behaves as the other one, but includes the following options:

• Select which classes to detect: Multiselect to choose which of the classes that the model's been trained on are going to be used in the inference.

Acknowledgments

• Detectron 2

License

This project is licensed under the MIT License - see the LICENSE.md file for details