File size: 2,452 Bytes
b28ba43 5efa014 35b4129 b28ba43 5efa014 35b4129 5efa014 35b4129 5efa014 | 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 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 | ---
license: cc-by-4.0
task_categories:
- text-to-image
- image-to-image
language:
- en
tags:
- 3d-animation
- cinematic
- stylized
- synthetic
- image-captioning
- lora
- solricks
pretty_name: 3D Animation Style
size_categories:
- n<1K
configs:
- config_name: default
data_files:
- split: train
path: data/train-00000-of-00001.parquet
---
# 3D Animation Style
A curated collection of **54 high-resolution synthetic images** by **SOLRICKS**, designed around a warm, cinematic 3D animation aesthetic. The dataset combines richly lit environments, fantasy interiors, stylized animal characters and expressive human characters.
## Dataset details
- **Images:** 54 PNG files
- **Resolution:** 50 images at 1254×1254 and 4 images at 1536×1024
- **Captions:** English, manually curated
- **Trigger token:** `3dsrx`
- **Columns:** `image`, `text`
- **Content:** environments, interiors, animal characters and human characters
- **Data origin:** synthetically generated and curated by SOLRICKS
## Repository structure
```text
3D-Animation-Style/
├── README.md
├── data/
│ └── train-00000-of-00001.parquet
├── metadata.csv
└── train.zip
├── 0001.png
└── ... 0054.png
```
The Image Parquet file powers the Dataset Viewer with compact thumbnails and visible `text` captions. The `train.zip` and `metadata.csv` files provide the same source dataset in ImageFolder format for direct download and LoRA training workflows.
## Loading the dataset
```python
from datasets import load_dataset
dataset = load_dataset("SOLRICKS/3D-Animation-Style", split="train")
print(dataset[0]["image"])
print(dataset[0]["text"])
```
## Intended uses
- Training or fine-tuning 3D animation style LoRAs
- Text-to-image and image-to-image experimentation
- Image-captioning and visual style research
- Creative concept development and reference-driven workflows
## Limitations
This is a small, curated synthetic dataset and does not represent the full diversity of real-world subjects or visual styles. Generated scenes may contain minor stylization artifacts, simplified anatomy or imperfect decorative text. Human characters are fictional and are not intended to represent real people.
## License
Released under the [Creative Commons Attribution 4.0 International License](https://creativecommons.org/licenses/by/4.0/). Attribution to **SOLRICKS** is required when redistributing or adapting the dataset.
|