Datasets:
Tasks:
Image Classification
Modalities:
Text
Formats:
json
Languages:
English
Size:
10K - 100K
License:
File size: 1,255 Bytes
b474786 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 | ---
license: apache-2.0
tags:
- scent-engine
- game-screenshots
- multi-label
- 6-channel-scent
task_categories:
- image-classification
language:
- en
size_categories:
- 10K<n<100K
---
# ScentEngine — Universal Training Annotations
Two-stage Gemma 4 labels (E4B primary, 31B verifier for conf ∈ [0.4, 0.7])
over public game screenshots. Each row maps an image to 6 PWM values
(0–100) in locked channel order: **Flora · Aqua · Earth · Pyric · Ozone · Civic**.
## Files
| File | Purpose |
|---|---|
| `public_games_final.jsonl` | All accepted labels (quarantine excluded) |
| `universal_train.jsonl` | 90% split for training the universal head |
| `universal_val.jsonl` | 10% split for validation / MAE eval |
## Row schema
```json
{{
"image_path": "...",
"game": "public_games",
"labels": {{"FLORA": 0, "AQUA": 0, "EARTH": 80, "PYRIC": 20, "OZONE": 0, "CIVIC": 0}},
"confidence": 0.84,
"labeler": "gemma-4-e4b-it"
}}
```
## Source pipeline
```
public game screenshots
→ scent-engine label-parallel (Gemma 4 E4B + 31B verifier)
→ quarantine + reconcile
→ scent-engine prepare-train --val-split 0.1
```
Code: https://github.com/dennishuang85/AI_model
|