| # Third-party model descriptor for MIRA benchmarking. | |
| # | |
| # To benchmark a third-party model: | |
| # 1. Place the model file in models/detection/ | |
| # 2. Create a YAML descriptor like this one | |
| # 3. Run: mira benchmark --models <model_name> --dataset datasets/mira_all | |
| # | |
| # Supported types: yolo_pt, yolo_tflite, tflite, onnx, keras | |
| # | |
| # Ultralytics-compatible models (.pt, .tflite) work out of the box — | |
| # the adapter will load them via `ultralytics.YOLO()` automatically. | |
| # Non-ultralytics models (e.g. raw keras/tf SavedModel) need a custom | |
| # adapter subclass that overrides load() and predict() in models.py. | |
| name: "Example Third-Party Model" | |
| type: tflite | |
| model_file: example_third_party.tflite | |
| imgsz: 320 | |
| class_names: [glass, metal, paper, plastic, trash] | |
| preprocessing: null | |