Upgrade Gradio to 6.1.0 for huggingface-hub>=0.30 compatibility.

Remove invalid pyaudioop dep; Python 3.12 has audioop built in.

Fix HF Space startup on Python 3.13 and add local run guide.

Shorten Space description to satisfy HF metadata limit.

Merge HF Space scaffold and resolve README for endpoint labeler deploy.

initial commit

Prepare endpoint labeler for Robometer HF Space deploy.

Step 6: Add success/failure trajectory filtering from metadata

Step 5: Add pattern analysis with full metrics (mean, median, std, min, max, 90th percentile)

Step 4: Add labeling interface with CSV export and navigation

Step 3: Add dataset loading from HuggingFace

Step 2: Add video player and frame navigation

Try with launch() call

Fresh start: Absolute minimal Gradio app

Pin huggingface-hub==0.19.4 to fix HfFolder import

Reset to minimal app - build from scratch

Add demo.queue() for HuggingFace Spaces async processing

Refactor: Consolidate everything into single app.py file

Use Gradio 4.44.1 with huggingface-hub==0.19.4 (has HfFolder)

Reorder requirements - install huggingface-hub first to pin version

Pin huggingface-hub<0.20.0 to fix HfFolder import issue with Gradio 5.0

Upgrade to Gradio 5.0.0 for compatibility with newer huggingface_hub

Upgrade Gradio to 4.44.1 in both README and requirements

Add error handling with print statements to debug initialization issue

Minimal app.py - import and create demo at module level

Simplify app.py - ensure demo is always a Blocks object

Add extensive debugging to app.py

Add error handling to app.py for better debugging

Fix numpy/opencv conflict: use opencv-python-headless<4.12.0 compatible with numpy 1.x (Gradio 4.0.0 requirement)

Upgrade Gradio to 4.44.1 to fix security vulnerabilities and numpy compatibility

Fix numpy version conflict with opencv-python

Fix app.py for HuggingFace Spaces - module level demo

initial push

Initial commit: Trajectory End Point Labeler

initial commit