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@ -22,3 +22,17 @@ The dataset is proposed for super-resolution tasks. We use the dataset for HQ fi
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[HD-VG-130M](https://github.com/daooshee/HD-VG-130M?tab=readme-ov-file) comprises 130M text-video pairs.
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The caption is generated by BLIP-2.
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We find the scene and the text quality are relatively poor. For OpenSora 1.0, we only use ~350K samples from this dataset.
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## Midjourney-v5-1.7M
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[Midjourney-v5-1.7M](https://huggingface.co/datasets/wanng/midjourney-v5-202304-clean) includes 1.7M image-text pairs.
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In detail, this dataset introduces two subsets: original and upscale.
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This dataset is proposed for exploring the relationship of prompts and high-quality images.
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## Midjourney-kaggle-clean
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[Midjourney-kaggle-clean](https://huggingface.co/datasets/wanng/midjourney-kaggle-clean) is a reconstructed version of [Midjourney User Prompts & Generated Images (250k)](https://www.kaggle.com/datasets/succinctlyai/midjourney-texttoimage?select=general-01_2022_06_20.json%5D), which is cleaned by rules.
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Moreover, this dataset is divided into two subsets: original and upscale.
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This dataset is proposed for enabling research on text-to-image model prompting.
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## upsplash-lite
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The [Unsplash-lite](https://github.com/unsplash/datasets) Dataset comprises 25k nature-themed Unsplash photos, 25k keywords, and 1M searches.
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This dataset covers a vast range of uses and contexts. Its extensive scope in intent and semantics opens new avenues for research and learning.
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