---
license: agpl-3.0
library_name: tf-lite
tags:
  - object-detection
  - yolov8
  - billiards
  - tflite
  - cuedetat
---

# CueDetat MASTER_POOL_MODEL — Pool Table / Ball Detector

The TFLite detector used by the CueDetat Android app for pocket/table and ball/cue detection.
YOLOv8n, 640×640 input, FP16, NMS in-graph.

## Files
- `MASTER_POOL_MODEL.tflite` — a single binary that **concatenates four sub-models**.
- `MASTER_POOL_MODEL.tflite.meta` — byte offsets/lengths for each segment (required to load):
  `MODEL_i_OFFSET` / `MODEL_i_LENGTH`. The app maps each segment to its own interpreter.
- `metadata.yaml` — Ultralytics export metadata (classes, imgsz, stride).

## Segments the app actually runs
- Segment 0 — pocket/table detector. Output: `[1, N, 6]` rows `(y1, x1, y2, x2, score, classId)`.
- Segment 2 — pool ball / cue detector. Same row layout.
- (Segments 1 and 3 exist in the file but are unused by the app.)

## Classes (from `metadata.yaml`)
`0: pool-table  1: pool-table-hole  2: pool-table-side`
(plus ball/cue classes used by the pool head: ball, cue).

## Notes
- Input image normalized to [0,1], RGB, 640×640.
- License: AGPL-3.0 (Ultralytics-derived).