Python Deeplab-resnet Resources

💎A high level pipeline for face landmarks detection, supports training, evaluating, exporting, inference and 100+ data augmentations, compatible with torchvision and albumentations, can easily install with pip.

Pre-trained image classification models for Jax/Haiku Jax/Haiku Applications are deep learning models that are made available alongside pre-trained we

Pytorch implementation for A Novel Plug-in Module for Fine-Grained Visual Classification. fine-grained visual classification task.

Human-Segmentation-PyTorch Human segmentation models, training/inference code, and trained weights, implemented in PyTorch. Supported networks UNet: b

Resnet as representation for Reinforcement Learning (RRL) is a simple yet effective approach for training behaviors directly from visual inputs. We demonstrate that features learned by standard image classification models are general towards different task, robust to visual distractors, and when used in conjunction with standard Imitation Learning or Reinforcement Learning pipelines can efficiently acquire behaviors directly from proprioceptive inputs.

Multi-label classification of retinal disorders This is a deep learning course project. The goal is to develop a solution, using computer vision techn

Interpolation-ResNet Invited paper for WSA 2021, called 'Low Complexity Channel estimation with Neural Network Solutions'. Low complexity residual con

f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation [Paper] [PyTorch] [MXNet] [Video] This repository provides code for training

ademxapp Visual applications by the University of Adelaide In designing our Model A, we did not over-optimize its structure for efficiency unless it w

LightNet++ !!!New Repo.!!! ⇒ EfficientNet.PyTorch: Concise, Modular, Human-friendly PyTorch implementation of EfficientNet with Pre-trained Weights !!

pytorch-resnet-twitch PyTorch implementation(s) of various ResNet models from Twitch streams. Status: ResNet50 currently not working. Will update in n

🎉TensorFlow2.0-Examples🎉! "Talk is cheap, show me the code." ----- Linus Torvalds Created by YunYang1994 This tutorial was designed for easily divin

cdf_att_classification classes = {0: 'cat', 1: 'dog', 2: 'flower'} In this project we use both Resnet and Self-attention layer for cdf-Classification.

NFT-Price-Prediction-CNN - Using visual feature extraction, prices of NFTs are predicted via CNN (Alexnet and Resnet) architectures.

Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework

Image-popularity-score - A novel deep regression method for image scoring.

Weakly Supervised Segmentation by Tensorflow. Implements semantic segmentation in Simple Does It: Weakly Supervised Instance and Semantic Segmentation, by Khoreva et al. (CVPR 2017).

Self-labelling via simultaneous clustering and representation learning 🆗 🆗 🎉 NEW models (20th August 2020): Added standard SeLa pretrained torchvis

MEAL-V2 This is the official pytorch implementation of our paper: "MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without Tric

Shake-Shake regularization This repository contains the code for the paper Shake-Shake regularization. This arxiv paper is an extension of Shake-Shake

Reproduce ResNet-v2 using MXNet Requirements Install MXNet on a machine with CUDA GPU, and it's better also installed with cuDNN v5 Please fix the ran

AutoML for Image Semantic Segmentation Currently this repo contains the only working open-source implementation of Auto-Deeplab which, by the way out-

Introduction English | 简体中文 MMClassification is an open source image classification toolbox based on PyTorch. It is a part of the OpenMMLab project. D

A Higher Performance Pytorch Implementation of DeepLab V3 Plus Introduction This repo is an (re-)implementation of Encoder-Decoder with Atrous Separab

DeepLab with PyTorch This is an unofficial PyTorch implementation of DeepLab v2 [1] with a ResNet-101 backbone. COCO-Stuff dataset [2] and PASCAL VOC

Keras implementation of Deeplabv3+ This repo is not longer maintained. I won't respond to issues but will merge PR DeepLab is a state-of-art deep lear

TF-deeplab This is a Tensorflow implementation of DeepLab, compatible with Tensorflow 1.2.1. Currently it supports both training and testing the ResNe

Train DeepLab for Semantic Image Segmentation Martin Kersner, [email protected] This repository contains scripts for training DeepLab for Semantic I

Deeplab-resnet-101 Pytorch with Lovász hinge loss Train deeplab-resnet-101 with binary Jaccard loss surrogate, the Lovász hinge, as described in http:

DeepLab-ResNet-TensorFlow This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset. Up

DeepLab-ResNet-TensorFlow This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset. Fr

DeepLab Introduction DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe. It combines densely-compute

Python library with Neural Networks for Image Segmentation based on Keras and TensorFlow. The main features of this library are: High level API (just

AlbUNet-1D-2D-Tensorflow-Keras This repository contains 1D and 2D Signal Segmentation Model Builder for AlbUNet and several of its variants developed

MQBench Quantization Aware Training with PyTorch I am using MQBench(Model Quantization Benchmark)(http://mqbench.tech/) to quantize the model for depl

Brain-Image-Segmentation Segmentation of brain tissues in MRI image has a number of applications in diagnosis, surgical planning, and treatment of bra

RM Operation can equivalently convert ResNet to VGG, which is better for pruning; and can help RepVGG perform better when the depth is large.

RMNet: Equivalently Removing Residual Connection from Networks This repository is the official implementation of "RMNet: Equivalently Removing Residua

Python library with Neural Networks for Image Segmentation based on PyTorch. The main features of this library are: High level API (just two lines to

octconv.pytorch PyTorch implementation of Octave Convolution in Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octa

PyTorch Image Models Sponsors What's New Introduction Models Features Results Getting Started (Documentation) Train, Validation, Inference Scripts Awe

A Brain Tumor Detection and Classification Model built using RESNET50 architecture. The model is also deployed as a web application using Flask framework.

Deep Residual Networks with 1K Layers By Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. Microsoft Research Asia (MSRA). Table of Contents Introduc

A 3D multi-modal medical image segmentation library in PyTorch We strongly believe in open and reproducible deep learning research. Our goal is to imp

neural-dream This is a PyTorch implementation of DeepDream. The code is based on neural-style-pt. Here we DeepDream a photograph of the Golden Gate Br

TensorNets High level network definitions with pre-trained weights in TensorFlow (tested with 2.1.0 = TF = 1.4.0). Guiding principles Applicability.

pytorch-deeplab-resnet DeepLab resnet v2 model implementation in pytorch. The architecture of deepLab-ResNet has been replicated exactly as it is from

ResNeXt.pytorch Reproduces ResNet-V3 (Aggregated Residual Transformations for Deep Neural Networks) with pytorch. Tried on pytorch 1.6 Trains on Cifar

Wide Residual Networks (WideResNets) in PyTorch WideResNets for CIFAR10/100 implemented in PyTorch. This implementation requires less GPU memory than

Leibniz is a python package which provide facilities to express learnable partial differential equations with PyTorch

sssegmentation is a general framework for our research on strongly supervised semantic segmentation.

This is a playground for pytorch beginners, which contains predefined models on popular dataset. Currently we support mnist, svhn cifar10, cifar100 st

Visual Question Answering in pytorch /!\ New version of pytorch for VQA available here: https://github.com/Cadene/block.bootstrap.pytorch This repo wa

MoCo v3 for Self-supervised ResNet and ViT Introduction This is a PyTorch implementation of MoCo v3 for self-supervised ResNet and ViT. The original M

Image Classification Using Deep Learning Learning and Building Convolutional Neural Networks using PyTorch. Models, selected are based on number of ci

FunMatch-Distillation TF2 implementation of knowledge distillation using the "function matching" hypothesis from the paper Knowledge distillation: A g

A PyTorch implementation for PyramidNets (Deep Pyramidal Residual Networks) This repository contains a PyTorch implementation for the paper: Deep Pyra

R2Plus1D-PyTorch PyTorch implementation of the R2Plus1D convolution based ResNet architecture described in the paper "A Closer Look at Spatiotemporal

Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks (SDPoint) This repository contains the cod

CLIP-ViL In our paper "How Much Can CLIP Benefit Vision-and-Language Tasks?", we show the improvement of CLIP features over the traditional resnet fea

Pretrained models for Jax/Flax: StyleGAN2, GPT2, VGG, ResNet.

The dataTap Python library is the primary interface for using dataTap's rich data management tools. Create datasets, stream annotations, and analyze model performance all with one library.

Face Recognition Using Pytorch Python 3.7 3.6 3.5 Status This is a repository for Inception Resnet (V1) models in pytorch, pretrained on VGGFace2 and

Image Classification Project Killer in PyTorch This repo is designed for those who want to start their experiments two days before the deadline and ki

Activity Recognition TensorRT Perform video classification using 3D ResNets trained on Kinetics-400 dataset and accelerated with TensorRT P.S Click on

Pretrained models for Pytorch (Work in progress) The goal of this repo is: to help to reproduce research papers results (transfer learning setups for

OpenVINO Inference API This is a repository for an object detection inference API using the OpenVINO. It's supported on both Windows and Linux Operati

numpy-ml Ever wish you had an inefficient but somewhat legible collection of machine learning algorithms implemented exclusively in NumPy? No? Install

neural-dream This is a PyTorch implementation of DeepDream. The code is based on neural-style-pt. Here we DeepDream a photograph of the Golden Gate Br