thalos-ladder-safety-v1

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

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

It identifies ladder-related safety hazards such as:

• unsafe ladder positioning
• workers on ladders
• ladders near edges
• unstable ladder placement
• extension ladders
• step ladders
• ladder misuse or near-miss conditions

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.

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🚀 Usage (Python)

from ultralytics import YOLO

model = YOLO("thalostech2025/thalos-ladder-safety-v1/ladder_safety_weights.pt")

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


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

import torch
import requests
from io import BytesIO

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

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


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🏷️ Labels / Classes

ladder
worker_on_ladder
unsafe_ladder_position
extension_ladder
step_ladder
ladder_misuse

(Class names may vary slightly based on the v1.0 Roboflow dataset.)

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📄 License

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

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🔒 Important Notes
	•	This repository contains the weights only, not the training images.
	•	Thalos uses this model via server-side inference in the YOLO microservice.
	•	A future v2.0 may include multi-angle augmentation and hazard-specific subclasses.

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👤 Maintainer

Thalos Tech (2025)
Safety Intelligence & Hazard Detection Platform