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---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': train
- name: text
dtype: string
splits:
- name: train
num_bytes: 796865621.92
num_examples: 1030
download_size: 792357206
dataset_size: 796865621.92
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Stable Diffusion Dataset For 3D images generation
This is a set of 1.030 pairs prompt-image filtered and extracted from the 3D dataset [Objaverse](https://objaverse.allenai.org/)
This Dataset was used to finetune [Stable Diffusion 2](https://huggingface.co/stabilityai/stable-diffusion-2) in order to generate good (isolated, full object ...) images to feed an image to 3D model after that (like [Triposr](https://github.com/VAST-AI-Research/TripoSR) or [CRM](https://huggingface.co/Zhengyi/CRM)).
The issue we faced here was to chose which image to keep as most Objaverse objects had no title, no description or an inadequate one (for instance : School Project n°45). Thus the images have been sorted manually and by keeping around 20% of them we managed to build a 1000 big image dataset.
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