README.md

metadata

title: AnyTraverse Studio 🚜
emoji: 🚜
colorFrom: slate
colorTo: blue
sdk: gradio
sdk_version: 6.22.0
app_file: app.py
pinned: false
python_version: '3.12'
short_description: >-
  Live off-road traversability evaluation dashboard with Human-in-the-Loop
  (AnyTraverse)
tags:
  - computer-vision
  - robotics
  - segmentation
  - vlm

🚜 AnyTraverse Studio — Live Evaluation & HITL Dashboard

A live Gradio dashboard for evaluating the AnyTraverse zero-shot off-road traversability framework (paper, PyPI).

Workflow

1. Upload a video of an off-road scene.
2. Set the traversability preferences (τ), scene-similarity threshold, ROI-uncertainty threshold, ROI bounds and the VLM inference frame skip.
3. Press ▶️ Go / Reset.
4. Watch per frame:
   • raw image + ROI box · traversability map · uncertainty map · ROI crop
   • attention maps for all prompts (live, not in the exported video)
   • live dual-metric ROI traversability + uncertainty line plot
   • horizontal 0–1 gauge bars for the two ROI scores
   • the traversal state (ok / unknown_scene / unknown_object)
5. The run halts whenever traversal_state != OK. Provide an operator update like mud: -0.7; gravel: 0.6 (or just ok) and press Resume.

Thresholds and ROI bounds can be edited live during a run — they are applied directly to the running pipeline.

Notes

• The VLM weights (CLIPSeg + CLIP) download on first run and are cached.
• The composed analysis video is exported as an H.264 .mp4 (bundled imageio-ffmpeg, no system ffmpeg required).
• GPU is recommended; the space is configured for a T4 accelerator.