README.md

metadata

license: other
license_name: mixed-per-source
license_link: >-
  https://huggingface.co/datasets/diffusion-gif/trick-prediction-simulation-data/blob/main/LICENSES/README.md
language:
  - en
tags:
  - robotics
  - trajectory-prediction
  - simulation
  - privacy-minimized
  - multiple-licenses
task_categories:
  - other
configs:
  - config_name: trajectories
    default: true
    data_files:
      - split: train
        path: data/train.jsonl
      - split: heldout
        path: data/heldout.jsonl
  - config_name: public-rationales
    data_files:
      - split: train
        path: data/public_rationales.jsonl

Public simulation observations, EEF trajectories and teacher rationale drafts

17,421 prepared simulation records with actual eight-frame observations: 14,253 train / 3,168 heldout, from RoboTwin2.0 (five robot bodies) and DexMimicGen (bimanual simulation). This is a usable visual subset of a frozen research collection, not its complete 356.85GB original-media export and not a mirror of the complete upstream HDF5/asset datasets.

The 6,219 accompanying public teacher rationales include 3,465 machine-screened weak-supervision drafts and 2,754 held-for-review replies. Human-approved gold count is zero; faithfulness and robot-policy/paper accuracy are not verified. No model inference/training or new teacher API calls were performed here.

Contents and protocol

• data/train.jsonl, data/heldout.jsonl: anonymous IDs, public task/body/source labels, split, coordinate arrays and tar/member references.
• data/archives/*.tar: NPZ observations, each with f0 ... f7 containing the original prepared JPEG byte arrays. All frames are observed-history frames, not future footage or model predictions. No resizing/re-encoding.
• data/public_rationales.jsonl: only published rationale text, anonymous sample ID and explicit draft/review status; no raw API/account metadata.
• MEDIA_MANIFEST.jsonl, SHARDS.json, PUBLIC_RELEASE_MANIFEST.json and CHECKSUMS.sha256: per-member/per-frame/whole-file checksums.
• tools/: export, schema validation and a minimal CPU sample reader.

Coordinates are normalized-1000 image-grid XY. history and future_delta are arm-first [forecast_arm_count][8][2]; anchor is the last observed XY. Absolute future XY = anchor + future_delta. Each forecast arm has exactly one fixed local EEF origin (left_eef_origin or right_eef_origin), not five legacy body points. The source split and prepared projection protocol are retained and are not asserted to be the official upstream benchmark split. Source episode-group IDs are pseudonymized and remain separate across splits.

The published legacy SFT step900 / GRPO step250 model weights were not trained on this newer joint/fixed-EEF release. Reproducing those historical weights requires their original mix6 prompt/multi-point data protocol; do not silently substitute this data or claim new model results.

Download and read (no HF login required)

from huggingface_hub import snapshot_download
root = snapshot_download(
    "diffusion-gif/trick-prediction-simulation-data", repo_type="dataset",
    local_dir="./trick-prediction-simulation-data"
)

pip install -r requirements.txt
python tools/validate_release.py --root /your/downloaded/repository
python tools/load_sample.py --root /your/downloaded/repository --split train --index 0
# Optional observed-history GIF; never overwrites an existing output:
python tools/load_sample.py --root /your/downloaded/repository --index 0 --gif sample.gif

Use local_dir for a physical download folder rather than cache symlinks. Known local HF download-cache metadata are ignored by the offline validator; they are not part of the published payload. Dataset Viewer/load_dataset users can select trajectories or public-rationales explicitly to avoid mixing the two different JSON schemas.

Observed simulation examples (not predictions)

Six observed-history GIFs and their anonymous record references are listed in previews/manifest.json. They show simulation observations, not real people, real-world camera footage, ground-truth future videos or model predictions.

Privacy/release boundary

Source record/episode identifiers, original filenames, absolute machine paths, source timestamps, raw caption/instruction fields, credentials, HMAC key/ID mapping, account/API response IDs/usage/cost metadata, audio, logs and model weights are excluded. Every frame was decoded and checked for EXIF and other non-allowlisted image metadata. NPZ and tar metadata are rebuilt deterministically.

This is a simulation-only, field-minimized release. It is not a claim that all original real-world datasets/videos have been anonymized, nor a guarantee against source-scene matching for pixels that originate in public simulations.

Ego-Exo4D, FSD and ShareRobot original media remain outside this release pending separate redistribution permission and full visual/privacy review. Downloadable source data and model licenses do not automatically grant rehosting rights.

Licensing and quality

Use the per-record license and LICENSES/README.md: RoboTwin records retain MIT and upstream attribution; DexMimicGen records retain CC-BY-NC-SA-4.0 restrictions. These are source licenses, not a new universal license grant for all research data. Checksums/schema validity do not demonstrate rationale correctness, causal faithfulness, policy safety or reproduced model/paper performance.