# 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