thalos-powerline-safety-v1

Thalos Powerline Safety Detection – v1.0 (Roboflow → HuggingFace export)

This repository contains the Powerline Safety Detection model used in the Thalos Safety Intelligence platform.

It identifies hazards associated with overhead energized lines and electrical distribution infrastructure, including:

• overhead power lines
• poles / energized lines
• unsafe equipment proximity
• vehicle or crane boom clearance issues
• elevated work near energized conductors
• potential electrical strike hazards

This model was originally trained in Roboflow (Object Detection Large / YOLOv8-derived)
and exported as a PyTorch .pt file.
It is now hosted on HuggingFace for independent, cost-controlled inference inside the Thalos YOLO service.

---

🚀 Usage (Python)

from ultralytics import YOLO

model = YOLO("thalostech2025/thalos-powerline-safety-v1/powerline_safety_weights.pt")

results = model("example.jpg")
results.show()


⸻

🔗 Load From URL (Used by the Thalos YOLO Service)

import torch
import requests
from io import BytesIO

HF_URL = "https://huggingface.co/thalostech2025/thalos-powerline-safety-v1/resolve/main/powerline_safety_weights.pt"

response = requests.get(HF_URL)
model = torch.load(BytesIO(response.content), map_location="cpu")


⸻

🏷️ Labels / Classes

The following classes are included (based on the Roboflow v1.0 dataset):

powerline
pole
equipment_near_powerline
vehicle_near_powerline
boom_near_powerline
high_risk_proximity

(Class names may vary slightly depending on dataset version.)

⸻

📄 License

This model is distributed under the AGPL-3.0 license, consistent with Roboflow export requirements.

⸻

🔒 Important Notes
	•	This repository contains only the model weights, not training data.
	•	Thalos uses this model via server-side inference through the YOLO microservice.
	•	Future versions (v2.0+) may introduce risk scoring based on measured distances to energized lines.
	•	This migration eliminates cost exposure associated with Roboflow cloud inference.

⸻

👤 Maintainer

Thalos Tech (2025)
Safety Intelligence & Hazard Detection Platform