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Datasets:
Silicon23
/
itw_pipeline_visualization

Modalities:
Image
Video
Formats:
imagefolder
Languages:
English
Size:
10K - 100K
Tags:
3d-object-detection
object-tracking
video
visualization
Libraries:
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itw_pipeline_visualization
File size: 4,261 Bytes
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---
license: cc-by-4.0
pretty_name: ITW Pipeline Visualization Assets
tags:
  - 3d-object-detection
  - object-tracking
  - video
  - visualization
language:
  - en
---

# ITW Pipeline Visualization — assets

Rendered assets for the visualization site of an in-the-wild **open-vocabulary
3D video object tracking** project. Each pipeline takes an RGB video plus a text
category label and produces a per-frame 3D bounding-box trajectory; the site
shows what each one made of the same clip.

This repository holds only the **heavy media** the site streams at runtime:
per-frame depth and colour for the browser-side point cloud, overlay renders,
and gallery previews. The site itself is static and hosted separately; it
fetches these files cross-origin.

> These are derived visualization artifacts, not training data. Every frame
> originates from a source dataset — see **Datasets and attribution**.

## Datasets and attribution

Assets are grouped by source dataset. **Each dataset's assets carry that
dataset's own licence and attribution.** More datasets will be added; this table
is the authoritative list of what is currently present.

| id | source dataset | licence | attribution |
|---|---|---|---|
| `sav` | [SA-V](https://ai.meta.com/datasets/segment-anything-video/) (Segment Anything Video, Meta AI) | CC BY 4.0 | Ravi et al., *SAM 2: Segment Anything in Images and Videos*, 2024 |

Derived overlays and depth encodings are redistributed under the licence of the
dataset they derive from. The repository-level licence tag reflects the sources
currently included and will be revisited as datasets with different terms are
added — always read the table above rather than the tag alone.

## Layout

```
assets/<dataset_id>/<video_id>/
├── preview.mp4 · poster.jpg · strip.jpg        gallery preview
└── <pipeline_id>/
    ├── manifest.json          frames, intrinsics, metric camera-to-world poses
    ├── boxes.json             per-object per-frame 3D boxes (see conventions)
    ├── visualizations.json    what overlays exist, and at what cadence
    ├── depth/000000.webp …    uint16 metric depth, packed into R and G
    ├── rgb/000000.jpg …       colour for the point cloud
    └── overlays/<name>/
        ├── video.mp4          for playback
        └── frames/NNNNNN.jpg  stills at that overlay's own cadence
```

Pipelines currently present: `wilddet3d` (prompt-and-detect). Overlays currently
present: `input` (source video with ground-truth masks), `box_prompt`,
`point_prompt`.

## Conventions

These hold across every dataset and pipeline in this repository.

**Depth.** WebP with the 16-bit value split across the red and green channels,
because no single-channel 16-bit format decodes reliably across browsers:

```
z_metres = (R * 256 + G) / 65535 * depth_max_m      # z == 0 means invalid
```

`depth_max_m` is per clip, in `manifest.json`. Depth is metric metres, camera-Z,
OpenCV axes (x right, y down, z forward).

**Boxes.** Camera frame — the detector applies no extrinsic. Multiply by the
per-frame `c2w` in `manifest.json` for world frame. Each box carries `center`,
`dims_xyz` (extents along the box's own axes), `quat_wxyz`, and `corners`.

**Corner order** is canonical and identical across pipelines:

```
0 (-,-,-)  1 (+,-,-)  2 (+,+,-)  3 (-,+,-)
4 (-,-,+)  5 (+,-,+)  6 (+,+,+)  7 (-,+,+)
```

Edges: bottom `0-1-2-3-0`, top `4-5-6-7-4`, verticals `0-4 1-5 2-6 3-7`. Corners
are validated elementwise against `center + (signs · dims/2) @ Rᵀ` before
export, because IoU is order-invariant and cannot catch an ordering mistake.

**Frame indices** are always native source-video frames, so overlays at
different cadences share one timeline. Every overlay video is encoded at the
source frame rate with its content held between updates, so all overlays for a
clip have identical duration and stay in sync under a single playback rate.

**Annotation cadence is preserved, not interpolated.** Where a source dataset
annotates below video rate — SA-V labels every 4th frame at 24 fps, giving 6 Hz
masks — the overlay holds the previous annotation rather than inventing
intermediate ground truth, and `visualizations.json` records the true cadence.