Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,86 @@
+---
+license: mit
+task_categories:
+  - other
+tags:
+  - 3d
+  - animation
+  - mesh
+  - objaverse
+  - 4d
+size_categories:
+  - 10K<n<100K
+---
+
+# DynamicObjaverseProcessed
+
+67,084 animated (4D) 3D meshes curated from [Objaverse-XL](https://objaverse.allenai.org/), quality-ranked by ICP-based non-rigid deformation intensity.
+
+## Overview
+
+Starting from 71,104 curated UIDs, the [processing pipeline](https://github.com/ou524u/DynamicObjaverseProcessing) downloads, unifies formats to `.glb`, and classifies meshes by animation quality:
+
+```
+71,104 curated UIDs → 67,746 downloads → 67,639 unified .glb → 67,084 true 4D meshes
+```
+
+All meshes are in binary glTF (`.glb`) format with embedded animations.
+
+## Quintile Ranking
+
+Meshes are ranked by **ICP residual** — a measure of non-rigid deformation after factoring out rigid-body motion (translation/rotation). Higher ICP = more interesting mesh deformation (e.g., character animation, cloth simulation).
+
+| Quintile | Files | ICP Range | Size | Description |
+|----------|-------|-----------|------|-------------|
+| Q1 (top) | 13,417 | 0.039 – 0.996 | 32 GB | Strongest deformation |
+| Q2 (high) | 13,417 | 0.027 – 0.039 | 44 GB | |
+| Q3 (mid) | 13,417 | 0.017 – 0.027 | 51 GB | |
+| Q4 (low) | 13,417 | 0.003 – 0.017 | 38 GB | |
+| Q5 (bottom) | 13,416 | 0.000 – 0.003 | 25 GB | Subtle / rigid-body motion |
+
+## Files
+
+- `classification.jsonl` — Full manifest with per-mesh metrics (ICP residual, amplitude, quintile, rank)
+- `quintile_1_top.tar` — Top 20% by deformation intensity (13,417 `.glb` files)
+- `quintile_2_high.tar` — High 20%
+- `quintile_3_mid.tar` — Mid 20%
+- `quintile_4_low.tar` — Low 20%
+- `quintile_5_bottom.tar` — Bottom 20%
+
+## Usage
+
+```python
+# Download and extract a specific quintile
+from huggingface_hub import hf_hub_download
+import tarfile
+
+path = hf_hub_download("littlekoyo/DynamicObjaverseProcessed", "quintile_1_top.tar", repo_type="dataset")
+with tarfile.open(path) as tar:
+    tar.extractall("./meshes")
+
+# Load the classification manifest
+import json
+path = hf_hub_download("littlekoyo/DynamicObjaverseProcessed", "classification.jsonl", repo_type="dataset")
+records = [json.loads(line) for line in open(path)]
+```
+
+### classification.jsonl fields
+
+| Field | Description |
+|-------|-------------|
+| `uid` | UUID identifier (also the filename without `.glb`) |
+| `classification` | `true_4d` / `static` / `error` |
+| `icp_residual_normalized` | Non-rigid deformation intensity (normalized by bbox diagonal) |
+| `max_displacement_normalized` | Raw vertex displacement (including rigid motion) |
+| `overall_amplitude` | Keyframe amplitude metric (supplementary) |
+| `quintile` | 1–5 (1 = most deformation, 5 = least; 0 for non-4D) |
+| `icp_rank` | Rank within true_4d (1 = highest ICP) |
+| `source_path` | Original file path in the processing pipeline |
+
+## Processing Pipeline
+
+See [DynamicObjaverseProcessing](https://github.com/ou524u/DynamicObjaverseProcessing) for the full pipeline code.
+
+## License
+
+The pipeline code is MIT licensed. Mesh data is sourced from Objaverse-XL and subject to its original licenses.