This is a sub-project of the main project myovision. It provides a Backend for the Application developed for the convenient use and further development of the myovision project. It is a RESTful API developed with the FastAPI framework and has a designated Frontend for the user interaction myovision-app-front
With a slight modification the Backend can be generalized and used for any computer vision project concerning instance segmentation.
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Annotation Tool for collecting labeled data Video
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Inference Tool for observing model's predictions and relevant metrics Video
To setup the Application backend locally follow the steps:
- Get the model checkpoint from link
- Place it in the ./checkpoints/ directory
- Install python dependencies using:
pip install -r requirements.txt - Install redis: follow the simple instructions based on your OS link
- Copy the example .env file:
cp .env-example .env - Adjust the default variables in .env file if desired
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Start Redis: follow the simple instructions based on your OS link
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Start API:
uvicorn backend.main:app
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Start Frontend: Follow the Instructions
Finally, open the browser go to the url the frontend is running.
Both Backend and Frontend contian Dockerfile to build docker images using: docker build (docs).
it can then be conveniently managed with docker-compose: docker-compose up (docs).
{
name = "Giorgi Nozadze",
email = "[email protected]"
}