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nq-fvg-detector
ibtsam/nq-fvg-detector
nq-fvg-detector is a object detection model from ibtsam. Use it when you need objects located in an image. It is set up for ultralytics. The card lists the license as agpl-3.0.
YOLOv26m model trained to detect Bullish and Bearish Fair Value Gaps (FVGs) on NQ Micro E-mini Nasdaq-100 Futures charts.
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At a glance
- Task
- Object Detection
- Library
- ultralytics
- License
- agpl-3.0
- Access
- Public
- Created
- Jun 19, 2026
- Updated
- Jun 20, 2026
- SHA
- 45d52629
Model card
From the Hugging Face model README
NQ Fair Value Gap (FVG) Detector (try it out )
YOLOv26m model trained to detect Bullish and Bearish Fair Value Gaps (FVGs) on NQ Micro E-mini Nasdaq-100 Futures charts.
Test Set Results
| Metric | Score |
|---|---|
| mAP@50 | 92.3% |
| mAP@50-95 | 58.2% |
| Precision | 83.9% |
| Recall | 89.4% |
| F1 | 86.6% |
Usage
from ultralytics import YOLO
model = YOLO("ibtsam/nq-fvg-detector")
results = model("chart.png", conf=0.25)
results[0].show()
Classes
bullish_fvg: gap created during upward impulse movebearish_fvg: gap created during downward impulse move
Dataset
Details
- Instrument: NQ1! Futures
- Timeframes: 1m, 5m
- Input size: 640x640
- Framework: Ultralytics YOLOv26m
Limitations
Trained on white background TradingView charts only. Not financial advice.
Author
Ibtsam Sadiq — GitHub · LinkedIn
- Task
- Object Detection
- Library
- ultralytics
- License
- agpl-3.0
- Created
- Jun 19, 2026
- Updated
- Jun 20, 2026