Datasets:
language:
- en
pretty_name: TEXEDO Dataset
license: other
tags:
- text-to-motion
- human-motion
- motion-generation
- amass
- claw
size_categories:
- 10K<n<100K
configs:
- config_name: default
data_files:
- split: train
path: data/train.jsonl
- split: validation
path: data/validation.jsonl
- split: test
path: data/test.jsonl
TEXEDO Dataset
TEXEDO is a text-motion dataset prepared from two sources: AMASS and CLAW. It keeps the MotionGPT-style split files while adding JSONL index files that are easier to load from the Hugging Face Hub.
Dataset Structure
TEXEDO_dataset/
README.md
train.txt
val.txt
test.txt
data/
train.jsonl
validation.jsonl
test.jsonl
all.jsonl
motions/
amass/{id_prefix}/{id}.npy
claw/{id_prefix}/{id}.npy
texts/
amass/{id_prefix}/{id}.txt
claw/{id_prefix}/{id}.txt
metadata/
dataset_summary.json
prepare_texedo_dataset.py
Each sample has one motion file and one text annotation file. Motion files are NumPy arrays with shape (num_frames, 36).
Motion Format
Each .npy motion file stores a float array with shape (T, 36), where T is the number of frames. The 36 dimensions are organized as:
| Feature slice | Size | Description |
|---|---|---|
motion[:, 0:3] |
3 | root position, (x, y, z) |
motion[:, 3:7] |
4 | root quaternion, (w, x, y, z) |
motion[:, 7:36] |
29 | joint positions / joint angles in the order below |
Joint order for motion[:, 7:36]:
| Joint index | Feature dim | Joint name |
|---|---|---|
| 0 | 7 | left_hip_pitch_joint |
| 1 | 8 | right_hip_pitch_joint |
| 2 | 9 | waist_yaw_joint |
| 3 | 10 | left_hip_roll_joint |
| 4 | 11 | right_hip_roll_joint |
| 5 | 12 | waist_roll_joint |
| 6 | 13 | left_hip_yaw_joint |
| 7 | 14 | right_hip_yaw_joint |
| 8 | 15 | waist_pitch_joint |
| 9 | 16 | left_knee_joint |
| 10 | 17 | right_knee_joint |
| 11 | 18 | left_shoulder_pitch_joint |
| 12 | 19 | right_shoulder_pitch_joint |
| 13 | 20 | left_ankle_pitch_joint |
| 14 | 21 | right_ankle_pitch_joint |
| 15 | 22 | left_shoulder_roll_joint |
| 16 | 23 | right_shoulder_roll_joint |
| 17 | 24 | left_ankle_roll_joint |
| 18 | 25 | right_ankle_roll_joint |
| 19 | 26 | left_shoulder_yaw_joint |
| 20 | 27 | right_shoulder_yaw_joint |
| 21 | 28 | left_elbow_joint |
| 22 | 29 | right_elbow_joint |
| 23 | 30 | left_wrist_roll_joint |
| 24 | 31 | right_wrist_roll_joint |
| 25 | 32 | left_wrist_pitch_joint |
| 26 | 33 | right_wrist_pitch_joint |
| 27 | 34 | left_wrist_yaw_joint |
| 28 | 35 | right_wrist_yaw_joint |
Splits
| Split | Samples |
|---|---|
| train | 18,590 |
| validation | 2,324 |
| test | 2,325 |
| total | 23,239 |
Sources
| Source | Samples |
|---|---|
| AMASS | 9,245 |
| CLAW | 13,994 |
The original textseedo source label from the preparation metadata is normalized to claw in this release.
JSONL Fields
Each row in data/*.jsonl contains:
id: six-digit sample idsplit:train,validation, ortestsource:amassorclawmotion_path: relative path to the.npymotion filetext_path: relative path to the original text annotation filenum_frames: number of motion framesmotion_dim: motion feature dimension, currently 36num_texts: number of captions in the text filecaptions: parsed caption entries withcaption,tokens,start_time, andend_time
This release intentionally does not include raw_source or original_npz fields.
Loading
from datasets import load_dataset
from huggingface_hub import snapshot_download
import numpy as np
from pathlib import Path
repo_id = "JianuoCao/TEXEDO"
repo_root = Path(snapshot_download(repo_id, repo_type="dataset"))
ds = load_dataset(
"json",
data_files={
"train": str(repo_root / "data/train.jsonl"),
"validation": str(repo_root / "data/validation.jsonl"),
"test": str(repo_root / "data/test.jsonl"),
},
)
sample = ds["train"][0]
motion = np.load(repo_root / sample["motion_path"])
captions = sample["captions"]
Upload
HF_XET_HIGH_PERFORMANCE=1 hf upload-large-folder JianuoCao/TEXEDO /home/jianuo/projects/MotionGPT/datasets/TEXEDO_dataset --repo-type=dataset --num-workers=16
Before publishing, verify that the AMASS and CLAW redistribution terms allow the chosen repository visibility and license.