zhengzangw/DoPrompt
Official implementation of PCS in essay "Prompt Vision Transformer for Domain Generalization"
This project offers a method to train computer vision models that perform well across different visual environments or datasets, even if they haven't seen data from all those environments during training. It takes in various image datasets from different "domains" (like different lighting conditions or art styles) and produces a robust image classification model. This is for machine learning researchers and practitioners who build and deploy computer vision systems.
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Use this if you need to develop an image classification model that maintains high accuracy when applied to new, unseen visual environments or data distributions.
Not ideal if you are looking for a pre-trained, ready-to-use model or a solution for tasks other than image classification, or if you don't work with deep learning frameworks like PyTorch.
Stars
50
Forks
4
Language
Python
License
MIT
Category
Last pushed
Jan 29, 2023
Commits (30d)
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