Data Science | Machine Learning with Python for Researchers
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The Data Science and Python channel is for researchers and advanced programmers

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โšก๏ธ UDiffText: A Unified Framework for High-quality Text Synthesis in Arbitrary Images via Character-aware Diffusion Models โœ’ Colab ๐Ÿฅณ

๐Ÿ–ฅ code: https://github.com/ZYM-PKU/UDiffText

โšก๏ธpage: https://udifftext.github.io

๐Ÿ“š paper: https://arxiv.org/abs/2312.04884

๐Ÿ”ฅcolab: https://github.com/camenduru/UDiffText-colab
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๐Ÿ“ฒ CogAgent: A Visual Language Model for GUI Agents

A state-of-the-art-level open visual language model.


๐Ÿ–ฅ code: https://github.com/thudm/cogvlm

๐Ÿ“š paper: https://arxiv.org/abs/2312.08914v1

๐Ÿ”ฅdataset: https://paperswithcode.com/dataset/ok-vqa
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๐Ÿ” FIND: Interface Foundation Models' Embeddings

๐Ÿ–ฅ Code: https://github.com/UX-Decoder/FIND

๐ŸŽ“ Demo: https://find.xyzou.net/

๐Ÿ”ฎ Project Page: https://x-decoder-vl.github.io

๐Ÿฅฉ Demo: https://find.xyzou.net

๐Ÿ“š ArXiv: https://arxiv.org/pdf/2312.07532.pdf
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PIA: Your Personalized Image Animator via Plug-and-Play Modules in Text-to-Image Models ๐ŸŽ„ ๐ŸŽ ๐ŸŽ… Colab ๐Ÿฅณ

๐ŸŽ“ page: https://pi-animator.github.io

๐Ÿ“š paper: https://arxiv.org/abs/2312.13964

๐Ÿ–ฅ code: https://github.com/open-mmlab/PIA
๐Ÿฅฉ OpenXLab: https://openxlab.org.cn/apps/detail/zhangyiming/PiaPia

๐Ÿฅฉ colab: https://github.com/camenduru/PIA-colab

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Repaint123: Fast and High-quality One Image to 3D Generation with Progressive Controllable 2D Repainting

๐Ÿ–ฅ Github: https://github.com/junwuzhang19/repaint123

๐Ÿ“• Paper: https://arxiv.org/pdf/2312.13271v1.pdf

๐Ÿ”ฅ Dataset: https://paperswithcode.com/dataset/nerf

https://t.iss.one/DataScienceT
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๐ŸŒ AnyDoor: Zero-shot Object-level Image Customization

pip install git+https://github.com/cocodataset/panopticapi.git

pip install pycocotools -i https://pypi.douban.com/simple

pip install lvis


๐Ÿ–ฅ Code: https://github.com/damo-vilab/AnyDoor

๐ŸŽ“ HF: https://huggingface.co/spaces/xichenhku/AnyDoor-online

๐Ÿ”ฎ Project Page: https://damo-vilab.github.io/AnyDoor-Page/

๐Ÿ“š ArXiv: https://arxiv.org/abs/2307.09481

https://t.iss.one/DataScienceT
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