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README.md

@@ -10,46 +10,142 @@ tags:
 
 # Giga-World-1 Example Data
 
-This directory contains example assets and a small toy dataset for testing the GigaWorld-1 data pipeline, training workflow, and inference scripts.
+<p align="center">
+  <img src="../assets/main_page.png" alt="Giga-World-1 Main Page" width="100%" />
+</p>
+
+- <img src="https://github.githubassets.com/images/modules/logos_page/GitHub-Mark.png" alt="GitHub" width="18" /> **Code Repository**: `https://github.com/<TODO>` (TBD)
+- <img src="https://img.shields.io/badge/Project-Page-blue?logo=googlechrome&logoColor=white" alt="Project Page" /> **Project Page**: `https://<TODO>` (TBD)
+
+This directory provides example assets and toy datasets for testing the GigaWorld-1 inference, data pipeline, and model training workflow.
 
 ## Directory Structure
 
 ```text
 example/
-├── infer_assest/
+├── infer_assest/                # Inference / rollout assets
 │   ├── control_video.mp4
 │   └── input_image.png
-└── toy_datapipeline_dataset/
-    ├── gt/
-    │   ├── cam_high/
-    │   ├── cam_left_wrist/
-    │   └── cam_right_wrist/
-    ├── plucker/
-    └── sketch/
-        └── cam_high/
+├── toy_datapipeline_dataset/    # Raw LeRobot-format toy dataset
+│   ├── gt/
+│   ├── depth/
+│   ├── plucker/
+│   ├── sketch/
+│   └── labels/
+└── toy_train_dataset/           # Model training data
+    ├── nano/
+    │   ├── dataset_cache.pkl
+    │   └── episode_*.pt
+    └── pro/
+        ├── dataset_cache.pkl
+        └── episode_*.pt
 ```
 
 ## Contents
 
-### `infer_assest/`
+### `infer_assest/` — Inference Assets
+
+Assets used for quick testing of the image-to-video inference / rollout pipeline.
+
+- `input_image.png`: input image (used as the first frame) for image-to-video generation.
+- `control_video.mp4`: control video used by the example inference pipelines.
 
-Small inference assets used for quick testing:
+### `toy_datapipeline_dataset/` — Raw LeRobot Dataset
 
-- `input_image.png`: input image / first frame for image-to-video rollout generation.
-- `control_video.mp4`: control video used by example inference pipelines.
+A compact robot video dataset shipped in the **raw LeRobot data format**, which can be visualized directly with the [LeRobot](https://github.com/huggingface/lerobot) visualization tools.
 
-### `toy_datapipeline_dataset/`
+<p align="center">
+  <img src="../assets/data_vis.gif" alt="LeRobot visualization of toy_datapipeline_dataset" width="100%" />
+</p>
 
-A compact robot video dataset for validating the data preprocessing pipeline.
+Dataset structure:
 
-- `gt/`: ground-truth multi-view robot videos.
-  - `cam_high/`: high / third-person camera view.
-  - `cam_left_wrist/`: left wrist camera view.
-  - `cam_right_wrist/`: right wrist camera view.
-- `plucker/`: Plücker / ray-map control videos for geometric conditioning.
-- `sketch/`: sketch-style control videos.
+```text
+example/toy_datapipeline_dataset/
+├── gt/                          # RGB videos (ground truth)
+│   ├── cam_high/                # head view
+│   ├── cam_left_wrist/          # left wrist view
+│   └── cam_right_wrist/         # right wrist view
+├── depth/                       # Depth Anything V2 outputs
+│   ├── cam_high/
+│   ├── cam_left_wrist/
+│   └── cam_right_wrist/
+├── plucker/                     # Plücker coordinate control signals (left/right per view)
+│   ├── episode_000001_left_direction.mp4
+│   ├── episode_000001_left_moment.mp4
+│   ├── episode_000001_right_direction.mp4
+│   └── episode_000001_right_moment.mp4
+├── sketch/                      # sketch control signals
+│   └── cam_high/
+└── labels/
+    ├── data.pkl                 # per-episode metadata
+    └── config.json
+```
+
+Each record in `labels/data.pkl` follows this structure:
+
+```python
+{
+    "action": List[List[float]],                    # end-effector / joint actions
+    "data_index": int,
+    "episode_name": str,
+
+    "cam_high_video_path": str,
+    "cam_left_wrist_video_path": str,
+    "cam_right_wrist_video_path": str,
+
+    "cam_high_depth_path": str,
+    "cam_left_wrist_depth_path": str,
+    "cam_right_wrist_depth_path": str,
+
+    "qpos": List[List[float]],                      # current joint angles
+    "video_height": int,
+    "video_width": int,
+    "video_length": int,
+
+    "short-prompt": {                               # from meta/episodes.jsonl
+        "task1": {
+            "start_idx": "0",
+            "end_idx": "299",
+            "description": "put banana into basket"
+        }
+    },
+
+    "long-prompt": {                                # generated by Qwen3-VL on cam_high
+        "long prompt 1": {
+            "start_idx": "0",
+            "end_idx": "299",
+            "caption": "The robot arm reaches toward ..."
+        }
+    }
+}
+```
 
-The toy dataset includes several short episodes and is intended for debugging, format verification, and small-scale demonstrations. It is not intended to represent the full training corpus.
+### `toy_train_dataset/` — Model Training Data
+
+Model training data for the GigaWorld-1 training workflow. This dataset is prepared for directly validating the model training pipeline on a small-scale example.
+
+Dataset structure:
+
+```text
+example/toy_train_dataset/
+├── nano/                        # nano-scale toy training split
+│   ├── dataset_cache.pkl        # cached dataset index / metadata for fast loading
+│   ├── episode_000000_4834c0369d_s000000_e000129_0-129_121_480_1920.pt
+│   ├── episode_000000_4834c0369d_s000129_e000258_0-129_121_480_1920.pt
+│   └── ...
+└── pro/                         # pro-scale toy training split
+    ├── dataset_cache.pkl        # cached dataset index / metadata for fast loading
+    ├── episode_000000_453e4c570c_s000000_e000129_0-129_121_480_1920.pt
+    ├── episode_000001_7473d389a6_s000000_e000129_0-129_121_480_1920.pt
+    ├── episode_000002_8436313f94_s000000_e000129_0-129_121_480_1920.pt
+    └── ...
+```
+
+- `nano/`: a smaller toy training split for quick debugging and smoke tests.
+- `pro/`: a larger toy training split for validating the full training data loader.
+- `dataset_cache.pkl`: cached metadata / dataset index used by the training pipeline.
+- `episode_*.pt`: preprocessed training samples. The filename records the source episode id, segment range, frame range, and spatial resolution.
 
 ## Usage
 
@@ -60,11 +156,36 @@ Example paths:
 ```bash
 EXAMPLE_ROOT=/path/to/example
 INFER_ASSETS=$EXAMPLE_ROOT/infer_assest
-TOY_DATASET=$EXAMPLE_ROOT/toy_datapipeline_dataset
+TOY_PIPELINE_DATASET=$EXAMPLE_ROOT/toy_datapipeline_dataset
+TOY_TRAIN_DATASET=$EXAMPLE_ROOT/toy_train_dataset
 ```
 
 Refer to the main project README for detailed commands covering data preparation, inference, visualization, and training.
 
+## Acknowledgements
+
+We sincerely thank the open-source community and the projects that make this work possible.
+
+<p align="center">
+  <a href="https://github.com/huggingface/diffusers">
+    <img src="https://img.shields.io/badge/Diffusers-Hugging%20Face-FFD21E?logo=huggingface&logoColor=black" alt="Diffusers" />
+  </a>
+  <a href="https://github.com/huggingface/lerobot">
+    <img src="https://img.shields.io/badge/LeRobot-Hugging%20Face-FFD21E?logo=huggingface&logoColor=black" alt="LeRobot" />
+  </a>
+  <a href="https://huggingface.co/">
+    <img src="https://img.shields.io/badge/Hugging%20Face-Models-FFD21E?logo=huggingface&logoColor=black" alt="Hugging Face" />
+  </a>
+  <a href="https://modelscope.cn/">
+    <img src="https://img.shields.io/badge/ModelScope-Community-624AFF" alt="ModelScope" />
+  </a>
+  <a href="https://pytorch.org/">
+    <img src="https://img.shields.io/badge/PyTorch-Framework-EE4C2C?logo=pytorch&logoColor=white" alt="PyTorch" />
+  </a>
+</p>
+
+Thanks also to many other open-source contributors for their tools, models, and community support.
+
 ## License
 
 This example data is released under the Apache License 2.0 unless otherwise specified.