README.md

---
license: other
task_categories:
- image-classification
language:
- en
size_categories:
- 100K<n<1M
dataset_info:
  features:
  - name: sample_id
    dtype: string
  - name: scene
    dtype: string
  - name: variant
    dtype: int32
  - name: scene_variant
    dtype: string
  - name: frame_id
    dtype: int32
  - name: image
    dtype: image
  - name: image_relpath
    dtype: string
  - name: params_relpath
    dtype: string
  - name: raw_params_json
    dtype: string
  - name: camera_json
    dtype: string
  - name: actors_json
    dtype: string
  - name: source_json
    dtype: string
  - name: actor_labels
    sequence: string
  - name: has_label_mapping
    dtype: bool
  - name: label_mapping_json
    dtype: string
  - name: label_mapping_keys
    sequence: string
  - name: label_mapping_values
    sequence: string
  - name: original_params_name
    dtype: string
  - name: upload_batch_utc
    dtype: string
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train/*.parquet
---

# turhancan97/SpaRRTa

Generated from `D:\Unreal Engine Environments\game_trial\Content\Python\unreal-scene-gen\unreal-secene-gen\dataset` on 2026-03-09T23:50:37.742993+00:00.

## Summary

- Format: parquet shards with one row per sample.
- Split: `train` only.
- Images are embedded in parquet under the `image` struct column (`bytes`, `path`).
- Full raw metadata is preserved in `raw_params_json`.

## Run Stats

- Discovered paired samples: **119502**
- New rows prepared this run: **20000**
- Skipped because already uploaded: **99502**
- Skipped broken/missing pairs or parse errors: **0**
- Parquet shards written this run: **79**

## Scene Coverage

| scene_variant | scene | variant | paired_samples | new_rows | skipped_existing | missing_pairs |
|---|---:|---:|---:|---:|---:|---:|
| `bridge` | `bridge` | `1` | 9834 | 0 | 9834 | 0 |
| `bridge_2` | `bridge` | `2` | 9834 | 0 | 9834 | 0 |
| `bridge_3` | `bridge` | `3` | 9834 | 0 | 9834 | 0 |
| `city` | `city` | `1` | 10000 | 0 | 10000 | 0 |
| `city_2` | `city` | `2` | 10000 | 0 | 10000 | 0 |
| `city_3` | `city` | `3` | 10000 | 0 | 10000 | 0 |
| `desert` | `desert` | `1` | 10000 | 0 | 10000 | 0 |
| `desert_2` | `desert` | `2` | 10000 | 0 | 10000 | 0 |
| `desert_3` | `desert` | `3` | 10000 | 0 | 10000 | 0 |
| `forest` | `forest` | `1` | 10000 | 0 | 10000 | 0 |
| `forest_2` | `forest` | `2` | 10000 | 10000 | 0 | 0 |
| `forest_3` | `forest` | `3` | 10000 | 10000 | 0 | 0 |
| `hf_upload_reports` | `hf_upload_reports` | `1` | 0 | 0 | 0 | 0 |

## Columns

- `sample_id` (string): stable unique id (`scene_variant:frame_id`)
- `scene` (string): base scene name (e.g. `bridge`)
- `variant` (int): numeric variant from folder suffix (`bridge_3` -> `3`, base folder -> `1`)
- `scene_variant` (string): source folder name
- `frame_id` (int): numeric frame id from filename
- `image` (struct): embedded image bytes + relative path
- `image_relpath` (string): relative source image path
- `params_relpath` (string): relative source JSON path
- `raw_params_json` (string): full original JSON text
- `camera_json` (string): `camera` section
- `actors_json` (string): `actors` section
- `source_json` (string): `source` section
- `actor_labels` (list[string]): unique labels found in `actors`
- `has_label_mapping` (bool): whether `source.label_mapping` exists
- `label_mapping_json` (string): full mapping JSON
- `label_mapping_keys` (list[string]): mapping keys
- `label_mapping_values` (list[string]): mapping values
- `original_params_name` (string): `source.original_params` when present
- `upload_batch_utc` (string): UTC timestamp of upload run

## Loading

```python
from datasets import load_dataset, Image

ds = load_dataset("turhancan97/SpaRRTa", split="train")
# Convert struct column to datasets Image feature if needed:
ds = ds.cast_column("image", Image())
```

## Download to Local Machine

Download the dataset repo files (parquet shards, README, manifest):

```bash
huggingface-cli download turhancan97/SpaRRTa --repo-type dataset --local-dir ./hf_SpaRRTa
```

## Rebuild Original Folder Structure

The script below reconstructs:
`<output>/<scene_variant>/img_XXXX.jpg` and `params_XXXX.json`

```python
from pathlib import Path
from datasets import load_dataset, Image

repo_id = "turhancan97/SpaRRTa"
output_root = Path("restored_position_between_objects")
output_root.mkdir(parents=True, exist_ok=True)

ds = load_dataset(repo_id, split="train")
ds = ds.cast_column("image", Image(decode=False))

for row in ds:
    mid = output_root / row["scene_variant"]
    mid.mkdir(parents=True, exist_ok=True)

    image_name = Path(row["image_relpath"]).name
    params_name = Path(row["params_relpath"]).name

    image_bytes = row["image"]["bytes"]
    if image_bytes is None:
        raise RuntimeError(f"Missing embedded image bytes for {row['sample_id']}")

    (mid / image_name).write_bytes(image_bytes)
    (mid / params_name).write_text(row["raw_params_json"], encoding="utf-8")
```