Create README.md

README.md

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+---
+license: cc-by-4.0
+pretty_name: >-
+  fidelity-data-factory/ README.md Metadata UI license   task_categories 
+  language  tags  pretty_name  size_categories
+size_categories:
+- 100K<n<1M
+task_categories:
+- reinforcement-learning
+- robotics
+- world models
+- representation-learning
+- video-understanding
+tags:
+  - egocentric
+  - robotics
+  - state-action-state
+  - world-models
+  - vla
+  - human-interaction
+  - imitation-learning
+  - offline-rl
+
+---
+
+
+# Fidelity Dynamics – Egocentric State–Action Transitions (v0)
+
+This repository contains an initial release of egocentric state–action–state′ transitions extracted from real-world worker footage by buildai.
+
+## Overview
+The dataset is constructed by enriching monocular egocentric videos into structured transitions of the form:
+
+(s_t, a_t, s_{t+1})
+
+Each transition represents a short temporal step derived from consecutive video frames.
+
+This release is intended as early infrastructure for researchers exploring:
+- World models
+- Dynamics learning
+- Vision–language–action systems
+- Representation learning from human activity
+
+## Data Contents
+- ~250,000 transitions
+- Real factory environments
+- Egocentric viewpoint (head- or chest-mounted cameras)
+
+Each transition is stored as a JSONL record.
+
+## Schema (Simplified)
+
+- `s` (state):
+  - `ego.pose`: estimated egomotion
+  - `ego.vel`: egocentric velocity
+  - `hand`: hand presence and image-space location
+  - `entities`: detected objects with bounding boxes and centers
+  - `meta`: video identifier
+
+- `a` (action):
+  - `ego_delta`
+  - `hand_delta`
+  - `grasp_delta`
+
+- `s_prime`:
+  - Same structure as `s`, representing the next timestep
+
+All values are derived from monocular video without force, torque, or privileged robot sensors.
+
+## Notes & Limitations
+- Monocular only
+- No force / torque / joint states
+- No task labels
+- Noise and estimation error are expected
+
+This is an early dataset released to support exploration and feedback.
+
+## Credits
+Original video data provided by BuildAI.
+Enrichment and processing by Fidelity Dynamics.