# Petrol-Station Detection Miner — SN44 (TurboVision)

Element: `manak0_Detect-petrol-station-1-0`
Backbone: YOLO11s, NMS-baked ONNX, FP16 weights (~19.3 MB).
Classes: `petrol hose`, `petrol pump`, `price board`, `roof canopy`.

## Files
- `miner.py` — chute entrypoint (`Miner.predict_batch`).
- `best_fp16.onnx` — model weights, NMS embedded.
- `class_names.txt` — class id → name mapping.
- `chute_config.yml` — Chutes runtime spec (Pro 6000, ORT-CUDA).

## Inference
- Letterbox 1280×1280, BGR→RGB, /255, NCHW float16.
- Single ORT CUDA pass + horizontal-flip TTA, merged via per-class hard NMS.
- Per-class confidence thresholds tuned on val.