This repository is an attempt to implement the Tryondiffusion model. For more details, visit the official Tryondiffusion website.
The code was developed and tested on the following environment:
-
Operating System: Windows server 2019
-
Python Version: Python 3.10
-
GPU : NVIDIA Tesla T4 16GB
-
CUDA 11.8
To get started with training examples, first clone this repository by running the following command in your terminal:
git clone https://github.com/Mutoy-choi/Tryondiffusion
cd Tryondiffusion
This will clone the repository and navigate you into the project directory.
python -m venv venv
.\venv\Scripts\activate
These commands create and activate a virtual environment named venv. This isolates the project dependencies, making it easier to manage.
pip install -r requirements.txt
python one_shot_test_ParallelUnet.py
This file allows you to know if the model is working well or not using example data for ParallelUnet(From 128x128 to 256*256)
- update preprocessing AI-Hub data
https://aihub.or.kr/aihubdata/data/view.do?currMenu=115&topMenu=100&aihubDataSe=realm&dataSetSn=78
Deployment content and amount of data provided
Studio fashion video (model photo) 6,741,328 cases
Studio Fashion Video Model Key Points: 120,936 Cases
Studio Fashion Video Model Semantic: 120,936 cases
Fashion products and fashion video pair: 117,270 cases
Fashion product representative photos (product photos) 40,036 cases
Fashion product key points: 40,036 cases
Fashion Product Semantic: 40,036 cases