Skip to content

Latest commit

 

History

History
72 lines (42 loc) · 3.54 KB

README.md

File metadata and controls

72 lines (42 loc) · 3.54 KB
Raw

[TEAM Z] S-DL

CloZ의 딥러닝 Inference용 API 서버 코드입니다.

CloZ is a clothing design system facilitated by natural language prompts. Cloz supports two main functions; 1) generating clothing images via natural language prompting. 2) editing generated images by replacing keywords from previous prompts.

Inspired by FACAD [1], we first built the nordstrom96568 dataset, which consists of 96568 (prompt, clothing image) pairs. Then we trained stable diffusion [2] 2.1 with our dataset to generate clothing images using prompts. The editing function was implemented by CycleDiffusion [3]. Also, we designed the CloZ's web-based interface based on guidelines of prior research [4].

프로젝트에서 사용한 기술

  • FastAPI, S3
  • Diffusers, Stable Diffusion, Cycle Diffusion, PyTorch

Dev Server 실행 방법

모델을 새로 학습해야 하므로 Dev Server는 실행이 불가능합니다

Production 배포 방법

uvicorn app:app --port=포트 --reload --host=0.0.0.0

환경 변수 및 시크릿

config.py를 구현해야함. NEXT_PUBLIC_S3_ACCESS_KEY_ID=string NEXT_PUBLIC_S3_SECRET_ACCESS_KEY=string NEXT_PUBLIC_S3_REGION=string NEXT_PUBLIC_S3_BUCKET=string DEVICE_ID = int NUM_IMAGES_PER_PROMPT= 6 NUM_INFERENCE_STEPS = 50 S3_URL = string DIFFUSION_PATH = string MODEL_PATH=string

CloZ: Natural Language Guided Clothing Design System

Abstract

CloZ is a clothing design system facilitated by natural language prompts. Cloz supports two main functions; 1) generating clothing images via natural language prompting. 2) editing generated images by replacing keywords from previous prompts.

Inspired by FACAD [1], we first built the nordstrom96568 dataset, which consists of 96568 (prompt, clothing image) pairs. Then we trained stable diffusion [2] 2.1 with our dataset to generate clothing images using prompts. The editing function was implemented by CycleDiffusion [3]. Also, we designed the CloZ's web-based interface based on guidelines of prior research [4].

To the best of our knowledge, CloZ is the first clothing design system using natural language guidance.

Requirements

# Please setup CUDA, torch first. 

pip install requirements.txt

Development

TBA

References

[1] Yang, X., Zhang, H., Jin, D., Liu, Y., Wu, C. H., Tan, J., ... & Wang, X. (2020). Fashion captioning: Towards generating accurate descriptions with semantic rewards. In Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XIII 16 (pp. 1-17). Springer International Publishing.

[2] Rombach, R., Blattmann, A., Lorenz, D., Esser, P., & Ommer, B. (2022). High-resolution image synthesis with latent diffusion models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 10684-10695).

[3] Wu, C. H., & De la Torre, F. (2022). Unifying Diffusion Models' Latent Space, with Applications to CycleDiffusion and Guidance. arXiv preprint arXiv:2210.05559.

[4] Ko, H. K., Park, G., Jeon, H., Jo, J., Kim, J., & Seo, J. (2022). Large-scale Text-to-Image Generation Models for Visual Artists' Creative Works. arXiv preprint arXiv:2210.08477.