ArchiVision YOLO Model
YOLOv8 model trained for architectural element detection and segmentation.
Model Details
- Task: segment
- Architecture: yolov8n-seg.pt
- Framework: Ultralytics YOLOv8
- Model file: best.pt
Classes
The model detects the following architectural elements:
window, door, column, arch, balcony, roof, facade, stairs, chimney, wall
Usage
Using Ultralytics
from ultralytics import YOLO
# Load model
model = YOLO('best.pt')
# Run inference
results = model.predict('image.jpg')
# Process results
for result in results:
boxes = result.boxes
masks = result.masks
for box in boxes:
class_id = int(box.cls[0])
confidence = float(box.conf[0])
print(f"Detected: {model.names[class_id]} ({confidence:.2f})")
Using Hugging Face Inference API
import requests
API_URL = "https://api-inference.huggingface.co/models/YOUR_USERNAME/archivision-yolo"
headers = {"Authorization": f"Bearer {YOUR_HF_TOKEN}"}
def query(image_url):
response = requests.post(API_URL, headers=headers, json={"inputs": image_url})
return response.json()
output = query("https://example.com/building.jpg")
print(output)
JavaScript/TypeScript
async function detectArchitecturalElements(imageUrl: string) {
const response = await fetch(
'https://api-inference.huggingface.co/models/YOUR_USERNAME/archivision-yolo',
{
method: 'POST',
headers: {
'Authorization': `Bearer ${process.env.HUGGINGFACE_TOKEN}`,
'Content-Type': 'application/json'
},
body: JSON.stringify({ inputs: imageUrl })
}
);
const predictions = await response.json();
return predictions;
}
Training
This model was trained on architectural images with the following elements: window, door, column, arch, balcony, roof, facade, stairs, chimney, wall
Limitations
- Performance may vary on architectural styles not well-represented in training data
- Best results on clear, well-lit building photos
- May require confidence threshold tuning for specific use cases
License
MIT License
Citation
If you use this model, please cite:
@misc{archivision-yolo,
author = {ArchiVision Team},
title = {ArchiVision YOLO Model},
year = {2025},
publisher = {Hugging Face},
url = {https://huggingface.co/YOUR_USERNAME/archivision-yolo}
}
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