Convnext-tf - Unofficial tensorflow keras implementation of ConvNeXt

Related tags

Deep Learningconvnext-tf
Overview

ConvNeXt Tensorflow

This is unofficial tensorflow keras implementation of ConvNeXt.
Its based on official PyTorch implementation.

Pre-trained Models

name resolution pretrain [email protected] #params FLOPs model
convnext_tiny_224 224x224 ImageNet-1K 82.1 28M 4.5G github
convnext_small_224 224x224 ImageNet-1K 83.1 50M 8.7G github
convnext_base_224 224x224 ImageNet-21K-1K 85.8 89M 15.4G github
convnext_base_384 384x384 ImageNet-21K-1K 86.8 89M 45.0G github
convnext_large_224 224x224 ImageNet-21K-1K 86.6 198M 34.4G github
convnext_large_384 384x384 ImageNet-21K-1K 87.5 198M 101.0G github
convnext_xlarge_224 224x224 ImageNet-21K-1K 87.0 350M 60.9G github
convnext_xlarge_384 384x384 ImageNet-21K-1K 87.8 350M 179.0G github

Note

I've ported only ImageNet-21K-1K weights for base, large and xlarge models.
If you want to convert another pretrained weight in official repo, you can refer to this script or just let me know.

Examples

import tensorflow as tf
from models.convnext_tf import create_model

x = tf.zeros((1, 224, 224, 3), dtype=tf.float32)

model = create_model('convnext_tiny_224', input_shape=(224, 224), pretrained=True)
out = model(x) # (1, 1000)

model = create_model('convnext_tiny_224', input_shape=(224, 224), num_classes=1, pretrained=True)
out = model(x) # (1, 1)

model = create_model('convnext_tiny_224', input_shape=(224, 224), include_top=False, pretrained=True)
out = model(x) # (1, 16, 16, 768)

Reference

https://github.com/facebookresearch/ConvNeXt
https://github.com/rishigami/Swin-Transformer-TF

You might also like...
Unofficial Tensorflow 2 implementation of the paper Implicit Neural Representations with Periodic Activation Functions
Unofficial Tensorflow 2 implementation of the paper Implicit Neural Representations with Periodic Activation Functions

Siren: Implicit Neural Representations with Periodic Activation Functions The unofficial Tensorflow 2 implementation of the paper Implicit Neural Repr

Seyma Yucer 2 Jun 27, 2022
Implementation of ConvMixer in TensorFlow and Keras
Implementation of ConvMixer in TensorFlow and Keras

ConvMixer ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer in that it operates directly on

Sayan Nath 8 Oct 3, 2022
Implementation of ConvMixer-Patches Are All You Need? in TensorFlow and Keras
Implementation of ConvMixer-Patches Are All You Need? in TensorFlow and Keras

Patches Are All You Need? - ConvMixer ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer in t

Sayan Nath 8 Oct 3, 2022
A Keras implementation of YOLOv4 (Tensorflow backend)
A Keras implementation of YOLOv4 (Tensorflow backend)

keras-yolo4 请使用更完善的版本: https://github.com/miemie2013/Keras-YOLOv4 Please visit here for more complete model: https://github.com/miemie2013/Keras-YOLOv

null 384 Nov 29, 2022
A tensorflow/keras implementation of StyleGAN to generate images of new Pokemon.
A tensorflow/keras implementation of StyleGAN to generate images of new Pokemon.

PokeGAN A tensorflow/keras implementation of StyleGAN to generate images of new Pokemon. Dataset The model has been trained on dataset that includes 8

null 19 Jul 26, 2022
Human head pose estimation using Keras over TensorFlow.
Human head pose estimation using Keras over TensorFlow.

RealHePoNet: a robust single-stage ConvNet for head pose estimation in the wild.

Rafael Berral Soler 71 Jan 5, 2023
Graph Neural Networks with Keras and Tensorflow 2.

Welcome to Spektral Spektral is a Python library for graph deep learning, based on the Keras API and TensorFlow 2. The main goal of this project is to

Daniele Grattarola 2.2k Jan 8, 2023
QKeras: a quantization deep learning library for Tensorflow Keras

QKeras github.com/google/qkeras QKeras 0.8 highlights: Automatic quantization using QKeras; Stochastic behavior (including stochastic rouding) is disa

Google 437 Jan 3, 2023
Hyperparameter Optimization for TensorFlow, Keras and PyTorch
Hyperparameter Optimization for TensorFlow, Keras and PyTorch

Hyperparameter Optimization for Keras Talos • Key Features • Examples • Install • Support • Docs • Issues • License • Download Talos radically changes

Autonomio 1.6k Dec 15, 2022
Comments
  • Low accuracy on ImageNet1K validation

    Low accuracy on ImageNet1K validation

    I'm using your TF-converted model (tiny) and testing on ImageNet 1K validation images, but I'm getting 78% accuracy instead of the officially published 82%.

    Do you think that a 4 percent drop could be because of Torch/Tensorflow difference? Another converted model (https://github.com/sayakpaul/ConvNeXt-TF) attains 81% and the only difference between you and sayakpaul is the implementation of depthwise convolution. Have you tested your model on validation and if so, can you share the steps so that I could figure out the problem?

    opened by app2scale 2
Owner
GitHub Repository
A pytorch-based real-time segmentation model for autonomous driving

CFPNet: Channel-Wise Feature Pyramid for Real-Time Semantic Segmentation This project contains the Pytorch implementation for the proposed CFPNet: pap

342 Dec 22, 2022
Mixed Transformer UNet for Medical Image Segmentation

MT-UNet Update 2022/01/05 By another round of training based on previous weights, our model also achieved a better performance on ACDC (91.61% DSC). W

dotman 92 Dec 25, 2022
A PyTorch implementation of "TokenLearner: What Can 8 Learned Tokens Do for Images and Videos?"

TokenLearner: What Can 8 Learned Tokens Do for Images and Videos? Source: Improving Vision Transformer Efficiency and Accuracy by Learning to Tokenize

Caiyong Wang 14 Sep 20, 2022
Deep Learning Visuals contains 215 unique images divided in 23 categories

Deep Learning Visuals contains 215 unique images divided in 23 categories (some images may appear in more than one category). All the images were originally published in my book "Deep Learning with P

Daniel Voigt Godoy 1.3k Dec 28, 2022
Neural HMMs are all you need (for high-quality attention-free TTS)

Neural HMMs are all you need (for high-quality attention-free TTS) Shivam Mehta, Éva Székely, Jonas Beskow, and Gustav Eje Henter This is the official

Shivam Mehta 0 Oct 28, 2022
Accuracy Aligned. Concise Implementation of Swin Transformer

Accuracy Aligned. Concise Implementation of Swin Transformer This repository contains the implementation of Swin Transformer, and the training codes o

FengWang 77 Dec 16, 2022
A short and easy PyTorch implementation of E(n) Equivariant Graph Neural Networks

Simple implementation of Equivariant GNN A short implementation of E(n) Equivariant Graph Neural Networks for HOMO energy prediction. Just 50 lines of

Arsenii Senya Ashukha 97 Dec 23, 2022
Genetic Programming in Python, with a scikit-learn inspired API

Welcome to gplearn! gplearn implements Genetic Programming in Python, with a scikit-learn inspired and compatible API. While Genetic Programming (GP)

Trevor Stephens 1.3k Jan 03, 2023
Bunch of different tools which helps visualizing and annotating images for semantic/instance segmentation tasks

Data Framework for Semantic/Instance Segmentation Bunch of different tools which helps visualizing, transforming and annotating images for semantic/in

Bruno Fernandes Carvalho 5 Dec 21, 2022
Context-Aware Image Matting for Simultaneous Foreground and Alpha Estimation

Context-Aware Image Matting for Simultaneous Foreground and Alpha Estimation This is the inference codes of Context-Aware Image Matting for Simultaneo

Qiqi Hou 125 Oct 22, 2022
A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography

A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography

ICT.MIRACLE lab 75 Dec 26, 2022
SphereFace: Deep Hypersphere Embedding for Face Recognition

SphereFace: Deep Hypersphere Embedding for Face Recognition By Weiyang Liu, Yandong Wen, Zhiding Yu, Ming Li, Bhiksha Raj and Le Song License SphereFa

Weiyang Liu 1.5k Dec 29, 2022
Official PyTorch implementation of the paper: Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting.

Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting Official PyTorch implementation of the paper: Improving Graph Neural Net

Giorgos Bouritsas 58 Dec 31, 2022
A Python library created to assist programmers with complex mathematical functions

libmaths libmaths was created not only as a learning experience for me, but as a way to make mathematical models in seconds for Python users using mat

Simple 73 Oct 02, 2022
Agile SVG maker for python

Agile SVG Maker Need to draw hundreds of frames for a GIF? Need to change the style of all pictures in a PPT? Need to draw similar images with differe

SemiWaker 4 Sep 25, 2022
Speeding-Up Back-Propagation in DNN: Approximate Outer Product with Memory

Approximate Outer Product Gradient Descent with Memory Code for the numerical experiment of the paper Speeding-Up Back-Propagation in DNN: Approximate

2 Mar 02, 2022
Unofficial Tensorflow-Keras implementation of Fastformer based on paper [Fastformer: Additive Attention Can Be All You Need](https://arxiv.org/abs/2108.09084).

Fastformer-Keras Unofficial Tensorflow-Keras implementation of Fastformer based on paper Fastformer: Additive Attention Can Be All You Need. Tensorflo

Yam Peleg 10 Jan 30, 2022
[CVPR 2021] 'Searching by Generating: Flexible and Efficient One-Shot NAS with Architecture Generator'

[CVPR2021] Searching by Generating: Flexible and Efficient One-Shot NAS with Architecture Generator Overview This is the entire codebase for the paper

35 Dec 01, 2022
Powerful unsupervised domain adaptation method for dense retrieval.

Powerful unsupervised domain adaptation method for dense retrieval

Ubiquitous Knowledge Processing Lab 191 Dec 28, 2022
[CVPR'21] DeepSurfels: Learning Online Appearance Fusion

DeepSurfels: Learning Online Appearance Fusion Paper | Video | Project Page This is the official implementation of the CVPR 2021 submission DeepSurfel

Online Reconstruction 52 Nov 14, 2022