Datasets:

hivamoh
/

wan22-physics-videos

Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 249, in _split_generators
                  raise ValueError(
              ValueError: `file_name` or `*_file_name` must be present as dictionary key (with type string) in metadata files
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                         ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

Wan2.2 Physics Video Generation Dataset

A dataset of AI-generated physics simulation videos with intermediate denoising latent tensors, created using the Wan2.2 T2V-A14B text-to-video model.

Dataset Summary

480 videos (.mp4) generated from 60 unique physics prompts (8 random seeds each)
Intermediate latent tensors (.pt) saved at every 2 denoising steps (10 snapshots per video)
Physics categories: ball bouncing, pendulum motion, objects sliding on inclined planes, sledding

Generation Parameters

Parameter	Value
Model	Wan2.2 T2V-A14B
Resolution	832x480
Sampling Steps	20
Solver	UniPC
Save Interval	Every 2 steps
GPU	NVIDIA H100 NVL 80GB

Dataset Structure

videos/           # 480 final .mp4 videos
latents/          # 480 directories, each with 10 .pt latent tensors
metadata.csv      # Per-video metadata (prompt, seed, file paths)
prompts.json      # Original prompt configs

Loading Latent Tensors

import torch

latent = torch.load("latents/001_..._intermediates/step_010.pt")
print(latent.shape)  # (16, 21, 60, 104) = (C, T, H, W) in latent space

Usage

from datasets import load_dataset
ds = load_dataset("hivamoh/wan22-physics-videos", data_files="metadata.csv")

Downloads last month: 30