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--- |
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license: cc-by-nc-sa-4.0 |
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dataset_info: |
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features: |
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- name: image |
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dtype: image |
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- name: text |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 1363424468 |
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num_examples: 14904 |
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download_size: 1328309729 |
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dataset_size: 1363424468 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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task_categories: |
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- text-to-image |
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language: |
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- en |
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size_categories: |
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- 10K<n<100K |
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images_reference: |
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- KREAM (https://kream.co.kr/) |
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pretty_name: KREAM Product Blip Capitions |
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tags: |
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- fashion |
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- cloth |
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- computer-vision |
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--- |
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## KREAM Product Blip Captions Dataset Information |
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![gif](./examples.gif) |
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**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. |
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This dataset consists of 'image' and 'text' key pairs. |
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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)'. |
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You can easily construct this dataset and finetune stable diffusion from scratch using [easy-finetuning-stable-diffusion](https://github.com/hahminlew/easy-finetuning-stable-diffusion). |
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## Usage |
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``` |
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from datasets import load_dataset |
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dataset = load_dataset("hahminlew/kream-product-blip-captions", split="train") |
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sample = dataset[0] |
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display(sample["image"].resize((256, 256))) |
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print(sample["text"]) |
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``` |
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![img_0](./outer_00000.png) |
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``` |
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outer, The North Face 1996 Eco Nuptse Jacket Black, a photography of the north face black down jacket |
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``` |
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## Citation |
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If you use KREAM Product Dataset in your research or projects, please cite it as: |
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``` |
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@misc{lew2023kream, |
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author = {Lew, Hah Min}, |
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title = {KREAM Product BLIP Captions}, |
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year={2023}, |
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howpublished= {\url{https://huggingface.co/datasets/hahminlew/kream-product-blip-captions/}} |
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} |
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``` |