- Modified the existing-code workflow to automatically loop back to New Task after project completion without user confirmation.
- Updated the autopilot state to reflect the current step as `done` and status as `completed`.
- Clarified the deployment status report by specifying non-deployed services and their purposes.
These changes enhance the automation of task management and improve documentation clarity.
- Add TensorRT export tests with graceful skip when no GPU available
- Add AC test coverage verification step (Step 8) to implement skill
- Add test coverage gap analysis to new-task skill
- Move exported_models fixture to conftest.py as session-scoped (shared across modules)
- Reorder tests: e2e training runs first so images/labels are available for all tests
- Consolidate teardown into single session-level cleanup in conftest.py
- Fix infrastructure tests to count files dynamically instead of hardcoded 20
Made-with: Cursor
- Updated `.gitignore` to remove committed test fixture data exclusions.
- Increased batch size in `config.test.yaml` from 4 to 128 for training.
- Simplified directory structure in `config.yaml` by removing unnecessary data paths.
- Adjusted paths in `augmentation.py`, `dataset-visualiser.py`, and `exports.py` to align with the new configuration structure.
- Enhanced `annotation_queue_handler.py` to utilize the updated configuration for directory management.
- Added CSV logging of test results in `conftest.py` for better test reporting.
These changes streamline the configuration management and enhance the testing framework, ensuring better organization and clarity in the project.
- Modified `.gitignore` to include test fixture data while excluding test results.
- Updated `config.yaml` to change the model from 'yolo11m.yaml' to 'yolo26m.pt'.
- Enhanced `.cursor/rules/coderule.mdc` with additional guidelines for test environment consistency and infrastructure handling.
- Revised autopilot state management in `_docs/_autopilot_state.md` to reflect current progress and tasks.
- Removed outdated augmentation tests and adjusted dataset formation tests to align with the new structure.
These changes streamline the configuration and testing processes, ensuring better organization and clarity in the project.
- Modified `.gitignore` to reflect the new path for test results.
- Updated `docker-compose.test.yml` to mount the correct test results directory.
- Adjusted `Dockerfile.test` to set the `PYTHONPATH` and ensure test results are saved in the updated location.
- Added `boto3` and `netron` to `requirements-test.txt` to support new functionalities.
- Updated `pytest.ini` to include the new `pythonpath` for test discovery.
These changes streamline the testing process and ensure compatibility with the updated directory structure.
- Replaced module-level path variables in constants.py with a structured Pydantic Config class.
- Updated all relevant modules (train.py, augmentation.py, exports.py, dataset-visualiser.py, manual_run.py) to access paths through the new config structure.
- Fixed bugs related to image processing and model saving.
- Enhanced test infrastructure to accommodate the new configuration approach.
This refactor improves code maintainability and clarity by centralizing configuration management.