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Datasets:
amd
/
Micro-World-Capsaicin

Tasks:
Text-to-Video
Modalities:
Video
Languages:
English
Size:
1K - 10K
Tags:
synthetic-data
video
world-model
action-conditioned-video
embodied-ai
graphics
Libraries:
Datasets
License:
Dataset card Data Studio Files
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Micro-World-Capsaicin
File size: 3,372 Bytes
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---
license: openrail
language:
  - en
task_categories:
  - text-to-video
tags:
  - synthetic-data
  - video
  - world-model
  - action-conditioned-video
  - embodied-ai
  - graphics
  - capsaicin
pretty_name: Micro-World-Capsaicin
size_categories:
  - 1K<n<10K
---

# Micro-World-Capsaicin

This dataset is part of the work [Micro-World V2](https://github.com/AMD-AGI/Micro-World). Micro-World-Capsaicin is a synthetic video dataset rendered with the open-source [AMD Capsaicin framework](https://github.com/GPUOpen-LibrariesAndSDKs/Capsaicin). It pairs rendered videos with English scene descriptions and frame-aligned control traces, making it suitable for research on action-conditioned video generation, world models, temporal prediction, and embodied-agent representation learning.

The dataset contains two sequence lengths, 200 frames and 400 frames. Every trajectory is provided in two video resolutions: a 360x640 resolution version under `video/` and a 4K version under `4k_videos/`. Files with the same basename represent the same trajectory and control sequence.

## Dataset summary

| Group | Unique trajectories | Frames per trajectory | Approximate size |
|---|---:|---:|---:|
| `200f` | 440 | 200 | 52.4 GB |
| `400f` | 374 | 400 | 88.8 GB |
| **Total** | **814** | — | **141 GB** |

The counts and sizes above describe the current `main` revision.

## Repository structure

```text
Micro-World-Capsaicin/
├── 200f/
│   ├── video/                  # 360x640 Standard-resolution MP4 files
│   ├── 4k_videos/             # 4K MP4 files
│   ├── metadata-detection/     # Frame-aligned control JSON files
│   └── video_captions_v0.csv   # Video descriptions and frame ranges
└── 400f/
    ├── video/
    ├── 4k_videos/
    ├── metadata-detection/
    └── video_captions_v0.csv
```

Within a frame group, the MP4 and JSON files are aligned by basename. For example:

```text
200f/video/allow_gallery_pitch_allow_a000_v00.mp4
200f/4k_videos/allow_gallery_pitch_allow_a000_v00.mp4
200f/metadata-detection/allow_gallery_pitch_allow_a000_v00.json
```

## Data fields

### Caption CSV

Each `video_captions_v0.csv` file contains one row per unique trajectory:

| Column | Description |
|---|---|
| `original video name` | MP4 filename used to locate both resolution variants and the corresponding JSON file. |
| `prompt` | Description of the rendered scene and its visible content. |
| `start frame index` | Inclusive first frame index. |
| `end frame index` | Inclusive final frame index. |

### Control JSON

Each file in `metadata-detection/` contains normalization factors and a dictionary of actions indexed by frame number. A shortened example is shown below:

```json
{
  "mouse_normalized_to_mc": {
    "yaw_factor": 0.06666666666666667,
    "pitch_factor": 0.06666666666666667
  },
  "actions": {
    "0": {
      "ws": 1,
      "ad": 0,
      "scs": 0,
      "pitch_delta": 0.0,
      "yaw_delta": 0.0,
      "collision": 0,
      "jump_invalid": 0
    }
  }
}
```

The action entries include encoded movement state (`ws`, `ad`, and `scs`), camera pitch and yaw changes, and collision or invalid-jump indicators. These values are pipeline-specific encodings; consumers should preserve the values as recorded and use the mapping supplied with the project code when it becomes available.