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Being towards death

Heed not to the tree-rustling and leaf-lashing rain, Why not stroll along, whistle and sing under its rein. Lighter and better suited than horses are straw sandals and a bamboo staff, Who's afraid? A palm-leaf plaited cape provides enough to misty weather in life sustain. A thorny spring breeze sobers up the spirit, I feel a slight chill, The setting sun over the mountain offers greetings still. Looking back over the bleak passage survived, The return in time Shall not be affected by windswept rain or shine.
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2 Most Powerful AI Virtual Try-on Projects (Girlfriend's Favorite)

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This post is translated from Chinese into English through AI.View Original
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OOTDiffusion focuses on combining clothing fusion and potential diffusion technology to provide a controllable solution for virtual try-on. The project is based on the VITON-HD dataset and has achieved high-definition virtual try-on effects. The project has released related models, installation, and inference guides for easy deployment and usage. It supports both upper body and full-body replacement and has reached commercial standards.

OOTDiffusion focuses on combining clothing fusion and potential diffusion technology to provide a controllable solution for virtual try-on. This project is trained based on the VITON-HD dataset and achieves high-definition virtual try-on effects. The project has released relevant models and provides complete installation and inference guides to help users easily deploy and use this technology.

The project supports partial body replacement and full body replacement, and has reached a commercial level.

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Installation

  1. Clone the repository

git clone https://github.com/levihsu/OOTDiffusion

  1. Create a conda environment and install the required packages

conda create -n ootd python==3.10
conda activate ootd
pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 numpy==1.24.4 scipy==1.10.1 scikit-image==0.21.0 opencv-python==4.7.0.72 pillow==9.4.0 diffusers==0.24.0 transformers==4.36.2 accelerate==0.26.1 matplotlib==3.7.4 tqdm==4.64.1 gradio==4.16.0 config==0.5.1 einops==0.7.0 ninja==1.10.2

Inference

  1. Partial body model

cd OOTDiffusion/run
python run_ootd.py --model_path --cloth_path --scale 2.0 --sample 4

  1. Full body model

The clothing category must be paired: 0 = upper body; 1 = lower body; 2 = dress

cd OOTDiffusion/run
python run_ootd.py --model_path --cloth_path --model_type dc --category 2 --scale 2.0 --sample 4

Trial link

https://ootd.ibot.cn/

Alibaba's Outfit Anyone achieves real-time outfit changes

Outfit Anyone is a high-quality AI virtual try-on technology that is suitable for any clothing and any person. It allows users to try different fashion styles without physically trying on clothes. It is the latest virtual try-on technology based on conditional diffusion models released by Alibaba Group's Institute of Intelligent Computing.

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To prevent personal photos from being maliciously used, the functionality is currently limited to uploading clothing images only. All displayed models are pre-set and generated using artificial intelligence models to ensure safety and privacy.

Demo link:
https://huggingface.co/spaces/HumanAIGC/OutfitAnyone (requires magic)

Project link:
https://humanaigc.github.io/outfit-anyone/

Code link:
https://github.com/HumanAIGC/OutfitAnyone

Under normal circumstances, this article should end here, but this time is an exception. Just imagine, what would happen if we combine Outfit Anyone and Animate Anyone?

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