Robopipe Studio is an open-source software designed for capturing and processing image data, labeling images, and training and deploying machine learning models. It provides a user-friendly interface for managing image datasets, annotating images, and building computer vision applications.
To learn more about Robopipe Studio, please visit the Robopipe Documentation.
- Docker
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Clone the repository:
git clone https://github.com/Robopipe/Studio.git
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Build the Docker image:
cd Studio docker build -t robopipe-studio .
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Run the Docker container:
docker run -p 8000:8000 robopipe-studio
- Python 3.8 or higher
- Git
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Clone the repository:
git clone https://github.com/Robopipe/Studio.git
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Navigate to the project directory:
cd Studio -
Install the required dependencies:
a) Install dependencies for API:
python3 -m venv .venv source .venv/bin/activate python3 -m pip install poetry poetry install python3 label_studio/manage.py collectstatic(optional) Install base NN models:
python3 label_studio/manage.py installmodels --all
b) Install dependencies for Frontend:
cd web yarn install -
Build the frontend:
yarn ls:build
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Run the application:
cd .. python3 label_studio/manage.py runserver
Robopipe values all your feedback. If you encounter any problems with the app, please open a GitHub issue for anything related to this app - bugs, improvement suggestions, documentation, developer experience, etc.
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