Object Detection
ultralytics
yolo
drone-detection
aerial
OmniSense
MediaSense
ConnectiviaLabs
deprecated
Instructions to use MuayThaiLegz/DroneDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use MuayThaiLegz/DroneDetection with ultralytics:
from huggingface_hub import hf_hub_download from ultralytics import YOLO # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("MuayThaiLegz/DroneDetection", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
DroneDetection (v1) — ⚠️ Deprecated
This model is superseded by DroneDetectionV.2.
Kept for archival reference only.
Part of OmniSense / MediaSense — Connectivia Labs' industrial AI platform.
Performance
| Metric | Value |
|---|---|
| mAP@0.5 | 98.9% |
| Architecture | YOLO (v1 training run) |
| Input size | 640×640 |
Classes
drone · uav
Training Notes
- First training iteration for drone/UAV detection
- Superseded by v2 with improved dataset and augmentation pipeline
- Hardware: NVIDIA GPU (GCP)
Status
🔒 Private — archived. Use DroneDetectionV.2 for all active deployments.
Platform
OmniSense — Multi-agent industrial AI platform
Pillar: MediaSense (Computer Vision)
Connectivia Labs — Internal use only
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