* Run tests
* Run tests
* Run tests
* Run tests
* Added rebuild
* Added files for e2e tests
* Added rebuild
* Added rebuild
* Added biuld TensorRT flag
* Changed to use NumPy 1.x for Jetson
* Make universal invocation
* Make Cython constans
* Changed to prepare onnx
* Changed smoke-test to wait AI conversion
* Added step for model conversion
* Changed to not run step in parallel
* Push model to docker registry
* Push model to docker registry
* Push model to docker registry
- Updated the autopilot state to reflect the current task status as in progress.
- Refactored the inference module to streamline model downloading and conversion processes, replacing the download_model method with a more efficient load_source method.
- Introduced asynchronous model building in the inference module to enhance performance during model conversion.
- Enhanced the engine factory to include a new method for building and caching models, improving error handling and logging during the upload process.
- Added calibration cache handling in the Jetson TensorRT engine for better resource management.
Made-with: Cursor
- Added a new Cython extension for the engine factory to the setup configuration.
- Updated the inference module to include additional logging for video batch processing and annotation callbacks.
- Refactored test cases to standardize the detection endpoint responses and include channel IDs in headers for better event handling.
Roman Meshko