{"id":42647439,"url":"https://github.com/p0is0n/spot-perceptio","last_synced_at":"2026-01-29T07:03:55.418Z","repository":{"id":329301353,"uuid":"1077299557","full_name":"p0is0n/spot-perceptio","owner":"p0is0n","description":"A lightweight image perception service based on Python, FastAPI, UltraLytics and 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backend systems.\n\nThe project follows **Domain-Driven Design (DDD)** principles to ensure strict domain boundaries, modularity, testability, and long-term maintainability.\n\n## Architecture Overview\n\nThe project is structured according to Domain-Driven Design principles.\n\nThis architecture provides:\n- clear separation of domain, application, and infrastructure layers\n- easy plug-and-play ML backends\n- predictable extension points for new vision tasks\n- high testability and isolation of domain logic\n- a consistent and scalable development workflow\n\n## Installation\n\n### Create .env file or pass variables to your environment\n\n```sh\ntouch .env\n```\n\n\u003cdetails\u003e\n\u003csummary\u003eSupported env variables\u003c/summary\u003e\n\n```sh\nAPP_DEBUG=False\nAPP_LOG_LEVEL=trace\nAPP_HOST=0.0.0.0\nAPP_PORT=8001\n\nYOLO_VERBOSE=False\n\nML_YOLO_MODEL_DEVICE=cpu\n\nML_VEHICLE_IDENTIFIERS=yolo\nML_VEHICLE_IDENTIFIER_YOLO_MODEL_PATH=\nML_VEHICLE_IDENTIFIER_YOLO_THRESHOLD=0.80\n\nML_PLATE_IDENTIFIERS=hyperlpr,yolo\nML_PLATE_IDENTIFIER_YOLO_MODEL_PATH=\nML_PLATE_IDENTIFIER_YOLO_THRESHOLD=0.10\nML_PLATE_IDENTIFIER_HYPERLPR_THRESHOLD=0.90\n```\n\u003c/details\u003e\n\n### Prepare models\n\n```sh\nmkdir -p models/ul\n```\n\nVehicles identifier model:\n```sh\ncurl -L https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo12s.pt -o models/ul/yolo12s.pt\n```\n\nPlates identifier model:\n```sh\ncurl -L https://github.com/ultralytics/assets/releases/download/v8.3.0/yolo12s.pt -o models/ul/yolo12s.pt\n```\n\n\u003cdetails\u003e\n\u003csummary\u003eUnstable docker image build (main branch)\u003c/summary\u003e\n\n```sh\ndocker run -d \\\n\t\t--name spot-perceptio \\\n\t\t--restart=always \\\n\t\t--env-file .env \\\n\t\t-p 8001:8001 \\\n\t\t-v ./models:/app/models:ro \\\n\t\tghcr.io/p0is0n/spot-perceptio:main\n```\n\n```sh\ndocker logs -f spot-perceptio\n```\n\u003c/details\u003e\n\n\u003cdetails\u003e\n\u003csummary\u003eBuild docker image from source\u003c/summary\u003e\n\n#### Clone the repository:\n\n```sh\ngit clone git@github.com:p0is0n/spot-perceptio.git\n```\n\n#### Build and run:\n```sh\nmake build-container\n```\n\n```sh\nmake start-container\n```\n\u003c/details\u003e\n\n## API\n\nREST API is available at `http://127.0.0.1:8001/docs`.\n\n## Development\n\nThe repository includes everything required to start development.\nVS Code is the recommended environment.\n\nDevelopment features:\n- Development via devcontainer\n- Application source code located in /src\n- Tests located in /tests\n- Multiple Dockerfiles:\n- - Dockerfile - production image\n- - Dockerfile.dev - development environment\n- - Dockerfile.test - test execution\n- CI/CD pipelines powered by GitHub Actions\n\n## Third-Party Licenses\n\nThis project depends on third-party open source libraries and models, including:\n\n- Ultralytics YOLO - licensed under the AGPL-3.0\n- HyperLPR - licensed under Apache-2.0\n\nThese dependencies are used as external runtime components and are not\ndistributed as part of this repository's source code.\n\n## License\n\nThis project is licensed under the MIT License.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fp0is0n%2Fspot-perceptio","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fp0is0n%2Fspot-perceptio","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fp0is0n%2Fspot-perceptio/lists"}