---
title: Visual Chronometer
description: "TACO PhyFPS predictor over arbitrary videos. All consistency metrics are lower-is-better. WorldFoundry shares the runtime with PhyFPS-Bench-Gen; it does not invent a board."
---

Visual Chronometer (TACO Group, Texas A&M) predicts **Physical Frames Per Second (PhyFPS)** — the temporal scale implied by visual motion — ignoring container metadata. It is trained with controlled temporal resampling and physics-grounded augmentations (motion blur, rolling shutter). As a WorldFoundry benchmark it scores a **directory of arbitrary videos** (not a fixed prompt suite) with mean PhyFPS plus intra- / inter-video coefficients of variation. **Lower values mean steadier temporal behavior.**

Sibling generation audit: [PhyFPS-Bench-Gen](/docs/evaluation/benchmark-hub/phyfps-bench-gen) (100-prompt Meta-vs-PhyFPS).

Code: [taco-group/Visual_Chronometer](https://github.com/taco-group/Visual_Chronometer). Checkpoint: [`xiangbog/Visual_Chronometer`](https://huggingface.co/xiangbog/Visual_Chronometer) (`vc_common_10_60fps.ckpt`, 10–60 FPS).

WorldFoundry runs `predict.py` in-process through the shared PhyFPS-Bench-Gen wrapper, or imports `results.csv`. Runtime / normalizer surfaces exist; **no release-verified full official run is claimed**.

<BenchmarkPageSections id="visual-chronometer" locale="en" />

## How to run

```bash
worldfoundry-eval zoo benchmark-run \
  --benchmark-id visual-chronometer \
  --mode official-validation \
  --official-results-path <results.csv> \
  --generated-artifact-dir <generated_videos> \
  --output-dir tmp/visual-chronometer/official-validation \
  --json
```

`--generated-artifact-dir` plus `WORLDFOUNDRY_VISUAL_CHRONOMETER_PREDICT_BACKEND` selects local prediction. Env: `WORLDFOUNDRY_VISUAL_CHRONOMETER_RESULTS_PATH`, `WORLDFOUNDRY_VISUAL_CHRONOMETER_ROOT`.

In-tree pointers: `worldfoundry/data/benchmarks/tasks/external/visual-chronometer.yaml`, `worldfoundry/evaluation/tasks/execution/runners/phyfps_bench_gen/runtime/visual_chronometer`.

Outputs include `scorecard.json` (primary `visual_chronometer_average`) and `results.csv`.

[← Benchmark Hub](/docs/evaluation/benchmark-hub)