Datasets:
File size: 2,592 Bytes
bccf4cc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 | ---
configs:
- config_name: default
data_files:
- split: full
path: data/full-*
- split: curated_10
path: data/curated_10-*
- split: thumbnail_3
path: data/thumbnail_3-*
task_categories:
- image-to-image
pretty_name: Triangle Reconstruction Benchmark
size_categories:
- n<1K
---
# Triangle Reconstruction Benchmark
A small, diverse dataset curated manually from existing datasets and images found online, with item-level rights and provenance information.
The purpose of this dataset is to evaluate the quality of algorithms for approximating images using sets of coloured triangles, such as [Genetic Algorithms](https://www.rogeralsing.com/2008/12/07/genetic-programming-evolution-of-mona-lisa/) or greedy ones such as [Geometrize](https://www.geometrize.co.uk/).
## Composition
The benchmark set consists of 75 images, all rendered and post-processed to RGB PNG with a 1024-pixel longest edge. Aspect ratio is preserved. Exact source files are retained under `originals/`.
Each image has a stable integer `index` from 1 to 75 for convenient reference (for example, “sample 23”), as well as a content-stable hexadecimal `id`. The same image retains its full-set index in every subset.
There are three sets:
- `full`: the entire 75-image collection,
- `curated_10`: a 10-image development subset useful when iterating on new algorithms, and
- `thumbnail_3`: three visually distinct headline images selected for thumbnails and quick comparisons. This includes the Mona Lisa, a target famously used by projects such as [EvoLisa](https://www.rogeralsing.com/2008/12/07/genetic-programming-evolution-of-mona-lisa/).
## Rights and attribution
This dataset contains images from multiple sources. No new or collective license is asserted over the source images; each image remains subject to its original license or rights status. Source, rights, and attribution information is provided at the item level. Canonical images have been resized and/or rasterized for evaluation.
See `THIRD_PARTY_NOTICES.md`, `third_party_licenses/`, and the Parquet metadata columns. In particular, DIV2K is described by its publisher as academic-research-only, Kodak has no first-party license file in the acquired mirror, and logos may remain subject to trademark rights.
## Loading
```python
from datasets import load_dataset
dataset = load_dataset("benchislett/TrianglePaintBench")
```
When working from a local clone, use `load_dataset("path/to/triangle_reconstruction_hf")` instead.
Integrity hashes for the original and canonical image files are in `checksums.sha256`.
|