Datasets:
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---
license: cc-by-nc-sa-4.0
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 1363424468
num_examples: 14904
download_size: 1328309729
dataset_size: 1363424468
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
task_categories:
- text-to-image
language:
- en
size_categories:
- 10K<n<100K
images_reference:
- KREAM (https://kream.co.kr/)
pretty_name: KREAM Product Blip Capitions
tags:
- fashion
- cloth
- computer-vision
---
## KREAM Product Blip Captions Dataset Information
**KREAM Product Blip Captions Dataset** is a dataset card for finetuning a text-to-image generative model collected from [KREAM](https://kream.co.kr/), one of the best online-resell market in Korea.
This dataset consists of 'image' and 'text' key pairs.
The format of 'text' is 'category (e.g. outer), product original name (e.g. The North Face 1996 Eco Nuptse Jacket Black), blip captions (e.g. a photography of the north face black down jacket)'.
You can easily construct this dataset and finetune stable diffusion from scratch using [fashion-product-generator](https://github.com/hahminlew/fashion-product-generator).
## Usage
```
from datasets import load_dataset
dataset = load_dataset("hahminlew/kream-product-blip-captions", split="train")
sample = dataset[0]
display(sample["image"].resize((256, 256)))
print(sample["text"])
```
```
outer, The North Face 1996 Eco Nuptse Jacket Black, a photography of the north face black down jacket
```
## Application
You can inference the finetuned Stable Diffusion XL with LoRA based on the dataset here: [hahminlew/sdxl-kream-model-lora-2.0](https://huggingface.co/hahminlew/sdxl-kream-model-lora-2.0)
## Citation
If you use KREAM Product Dataset in your research or projects, please cite it as:
```
@misc{lew2023kream,
author = {Lew, Hah Min},
title = {KREAM Product BLIP Captions},
year={2023},
howpublished= {\url{https://huggingface.co/datasets/hahminlew/kream-product-blip-captions/}}
}
``` |