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MilitaryConvoy-YOLO11L
MuayThaiLegz/MilitaryConvoy-YOLO11L
MilitaryConvoy-YOLO11L is a object detection model from MuayThaiLegz. Use it when you need objects located in an image. It is set up for ultralytics. The card lists the license as mit.
Part of OmniSense / MediaSense / DeSense — Connectivia Labs' defense AI platform.
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At a glance
- Task
- Object Detection
- Library
- ultralytics
- License
- mit
- Access
- Public
- Created
- Apr 5, 2026
- Updated
- Apr 5, 2026
- SHA
- fd4c0dd4
Model card
From the Hugging Face model README
MilitaryConvoy-YOLO11L — Military Vehicle & Convoy Detection
Part of OmniSense / MediaSense / DeSense — Connectivia Labs' defense AI platform.
Performance
| Metric | Value |
|---|---|
| [email protected] | 50.0% |
| [email protected]:0.95 | 30.4% |
| Precision | 57.0% |
| Recall | 47.7% |
| Architecture | YOLO11L |
| Input size | 640×640 |
| Training date | 2026-04-05 |
Classes (15 total)
Aerial/civilian (VisDrone): pedestrian · person · bicycle · car · van · truck · tricycle · awning-tricycle · bus · motor
Military (DeSense): military-vehicle · tank · apc · afv · artillery
Training
- Base: YOLO11L (COCO pretrained)
- Dataset: VisDrone2019-DET + MilitaryVehicleRecognition v7 (~9,300 images merged)
- Epochs: 75 | Batch: 32 | Imgsz: 640 | Optimizer: AdamW + cosine LR
- Augmentation: mosaic, mixup, copy-paste, flips, scale
Usage
from ultralytics import YOLO
model = YOLO('MuayThaiLegz/MilitaryConvoy-YOLO11L')
results = model('aerial_frame.jpg')
# Filter military classes only (indices 10-14)
mil = [b for b in results[0].boxes if int(b.cls) >= 10]
print(f'Military vehicles: {len(mil)}')
DeSense Pipeline
Camera/Satellite → MilitaryConvoy-YOLO11L → ByteTrack
→ DBSCAN convoy clustering → Stone Soup fusion → Geofence alert
OmniSense · Pillars: MediaSense · DeSense · Connectivia Labs 🔒
- Task
- Object Detection
- Library
- ultralytics
- License
- mit
- Created
- Apr 5, 2026
- Updated
- Apr 5, 2026