src/converter/README.md

YOLO26n model converter

The converter turns a compatible YOLO26n PyTorch checkpoint into the model.bin and manifest.json files consumed by the native runtime. It uses the Python 3.13 standard library and does not import Torch or Ultralytics.

Export and validate a checkpoint from the yolo26-raspberry-pi-5/ runtime directory:

make model RESOLUTION=640 CHECKPOINT=/absolute/yolo26n.pt
make model-check RESOLUTION=640 CHECKPOINT=/absolute/yolo26n.pt

Supported resolutions are 320, 480, 640, 800, 960, and 1280. Each converted model has one static input resolution. The same native runtime library can execute models at any supported resolution.

Conversion pipeline

1. checkpoint_decoder reads the supported Torch archive without importing executable model code.
2. model_validation validates the model type, operator topology, routing, tensor inventory, class labels, and detection-head geometry required by the fixed runtime.
3. weight_lowering folds BatchNorm, converts convolution layouts, and creates the split projections used by the runtime.
4. model_format serializes the named weight slots, resolution, and class metadata to model.bin.
5. export_yolo26n publishes model.bin and manifest.json together.