A library that includes Keras3 layers, blocks and models with pretrained weights, providing support for transfer learning, feature extraction, and more.

PyTorch implementation of 'ViViT' (Arnab et al., 2021) from scratch.

💡💡💡awesome compute vision app in gradio

Image search engine

UNetFormer: A UNet-like transformer for efficient semantic segmentation of remote sensing urban scene imagery, ISPRS. Also, including other vision transformers and CNNs for satellite, aerial image and UAV image segmentation.

Extract video features from raw videos using multiple GPUs. We support RAFT flow frames as well as S3D, I3D, R(2+1)D, VGGish, CLIP, and TIMM models.

building a multitask training platform based on Pytorch

A framework to accelerate AI/ML development 🚀

This repository is the implementation of the paper: ViT2 - Pre-training Vision Transformers for Visual Times Series Forecasting. ViT2 is a framework designed to address generalization & transfer learning limitations of Time-Series-based forecasting models by encoding the time-series to images using GAF and a modified ViT architecture.

Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models

Jax/Flax implementation of DeiT and DeiT-III (ViT)

HAT (Hard Attention to the Task) Modules for Continual Learning

Engage in a semantic segmentation challenge for land cover description using multimodal remote sensing earth observation data, delving into real-world scenarios with a dataset comprising 70,000+ aerial imagery patches and 50,000 Sentinel-2 satellite acquisitions.

An easy classification implement to explain how triton work

Attribution methods that explain image classification models, implemented in PyTorch, and support batch input and GPU.

PyTorch Volume Models for 3D data

Develope a robust and high-performance model utilizing computer vision techniques to classify images as either fraudulent or non-fraudulent within the context of insurance claims

Classification models with pretrained backbones. PyTorch. Easy to use baseline to train your models