rishikksh20/CrossViT-pytorch

Implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification

40
/ 100
Emerging

This helps deep learning engineers classify images more accurately by using a multi-scale vision transformer architecture. It takes raw image data as input and outputs a classification for each image. This is primarily used by machine learning practitioners who are building and deploying image classification models.

208 stars. No commits in the last 6 months.

Use this if you are a deep learning engineer looking to implement a Cross-Attention Multi-Scale Vision Transformer for image classification tasks in PyTorch.

Not ideal if you are not a developer or prefer a low-code/no-code solution for image classification.

deep-learning-engineering image-classification computer-vision pytorch-development machine-learning-model-building
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 14 / 25

How are scores calculated?

Stars

208

Forks

19

Language

Python

License

MIT

Last pushed

Apr 07, 2021

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/transformers/rishikksh20/CrossViT-pytorch"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.