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streetvision-roadwork-v2
Bittensorminingfactory/streetvision-roadwork-v2
streetvision-roadwork-v2 is a machine learning model from Bittensorminingfactory. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Binary-compatible FasterViT model for SN72 StreetVision subnet.
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.bin126 MB · 100%
At a glance
- Model type
- fastervit_binary
- Access
- Public
- Created
- Mar 1, 2026
- Updated
- Mar 4, 2026
- SHA
- 9ce48b4c
Model card
From the Hugging Face model README
StreetVision Roadwork Detection Model (Binary)
Binary-compatible FasterViT model for SN72 StreetVision subnet.
Model Details
- Architecture: FasterViT-0 with binary output wrapper
- Output: Single float [0.0, 1.0] indicating roadwork presence
- Input: 224x224 RGB images
- Classes: D00, D10, D20, D40 (internally mapped to binary)
Usage
from binary_wrapper import load_model
model = load_model("pytorch_model.bin", method="max")
score = predict(model, "image.jpg") # Returns float [0,1]
Binary Conversion
The 4-class damage detection model outputs probabilities for:
- D00: Longitudinal Crack
- D10: Transverse Crack
- D20: Alligator Crack
- D40: Pothole
Binary score = max(probabilities) across all damage classes.
- Type
- fastervit_binary
- Created
- Mar 1, 2026
- Updated
- Mar 4, 2026