PyTorch implementation of UNet++ (Nested U-Net).

Related tags

Deep Learningpytorchimage-segmentationunet
Overview

PyTorch implementation of UNet++ (Nested U-Net)

MIT License

This repository contains code for a image segmentation model based on UNet++: A Nested U-Net Architecture for Medical Image Segmentation implemented in PyTorch.

[NEW] Add support for multi-class segmentation dataset.

[NEW] Add support for PyTorch 1.x.

Requirements

  • PyTorch 1.x or 0.41

Installation

  1. Create an anaconda environment.
conda create -n=<env_name> python=3.6 anaconda
conda activate <env_name>
  1. Install PyTorch.
conda install pytorch torchvision cudatoolkit=10.1 -c pytorch
  1. Install pip packages.
pip install -r requirements.txt

Training on 2018 Data Science Bowl dataset

  1. Download dataset from here to inputs/ and unzip. The file structure is the following:
inputs
└── data-science-bowl-2018
    ├── stage1_train
    |   ├── 00ae65...
    │   │   ├── images
    │   │   │   └── 00ae65...
    │   │   └── masks
    │   │       └── 00ae65...            
    │   ├── ...
    |
    ...
  1. Preprocess.
python preprocess_dsb2018.py
  1. Train the model.
python train.py --dataset dsb2018_96 --arch NestedUNet
  1. Evaluate.
python val.py --name dsb2018_96_NestedUNet_woDS

(Optional) Using LovaszHingeLoss

  1. Clone LovaszSoftmax from bermanmaxim/LovaszSoftmax.
git clone https://github.com/bermanmaxim/LovaszSoftmax.git
  1. Train the model with LovaszHingeLoss.
python train.py --dataset dsb2018_96 --arch NestedUNet --loss LovaszHingeLoss

Training on original dataset

Make sure to put the files as the following structure (e.g. the number of classes is 2):

inputs
└── <dataset name>
    ├── images
    |   ├── 0a7e06.jpg
    │   ├── 0aab0a.jpg
    │   ├── 0b1761.jpg
    │   ├── ...
    |
    └── masks
        ├── 0
        |   ├── 0a7e06.png
        |   ├── 0aab0a.png
        |   ├── 0b1761.png
        |   ├── ...
        |
        └── 1
            ├── 0a7e06.png
            ├── 0aab0a.png
            ├── 0b1761.png
            ├── ...
  1. Train the model.
python train.py --dataset <dataset name> --arch NestedUNet --img_ext .jpg --mask_ext .png
  1. Evaluate.
python val.py --name <dataset name>_NestedUNet_woDS

Results

DSB2018 (96x96)

Here is the results on DSB2018 dataset (96x96) with LovaszHingeLoss.

Model IoU Loss
U-Net 0.839 0.365
Nested U-Net 0.842 0.354
Nested U-Net w/ Deepsupervision 0.843 0.362
Owner
4ui_iurz1
4ui_iurz1
GitHub Repository
Object detection using yolo-tiny model and opencv used as backend

Object detection Algorithm used : Yolo algorithm Backend : opencv Library required: opencv = 4.5.4-dev' Quick Overview about structure 1) main.py Load

2 Jul 06, 2022
Revealing and Protecting Labels in Distributed Training

Revealing and Protecting Labels in Distributed Training

Google Interns 0 Nov 09, 2022
Predict Breast Cancer Wisconsin (Diagnostic) using Naive Bayes

Naive-Bayes Predict Breast Cancer Wisconsin (Diagnostic) using Naive Bayes Downloading Data Set Use our Breast Cancer Wisconsin Data Set Also you can

Faeze Habibi 0 Apr 06, 2022
🤖 Project template for your next awesome AI project. 🦾

🤖 AI Awesome Project Template 👋 Template author You may want to adjust badge links in a README.md file. 💎 Installation with pip Installation is as

Wiktor Łazarski 18 Nov 23, 2022
GAN encoders in PyTorch that could match PGGAN, StyleGAN v1/v2, and BigGAN. Code also integrates the implementation of these GANs.

MTV-TSA: Adaptable GAN Encoders for Image Reconstruction via Multi-type Latent Vectors with Two-scale Attentions. This is the official code release fo

owl 37 Dec 24, 2022
Immortal tracker

Immortal_tracker Prerequisite Our code is tested for Python 3.6. To install required liabraries: pip install -r requirements.txt Waymo Open Dataset P

74 Dec 03, 2022
The Most Efficient Temporal Difference Learning Framework for 2048

moporgic/TDL2048+ TDL2048+ is a highly optimized temporal difference (TD) learning framework for 2048. Features Many common methods related to 2048 ar

Hung Guei 5 Nov 23, 2022
The open source code of SA-UNet: Spatial Attention U-Net for Retinal Vessel Segmentation.

SA-UNet: Spatial Attention U-Net for Retinal Vessel Segmentation(ICPR 2020) Overview This code is for the paper: Spatial Attention U-Net for Retinal V

Changlu Guo 151 Dec 28, 2022
A Python library for Deep Graph Networks

PyDGN Wiki Description This is a Python library to easily experiment with Deep Graph Networks (DGNs). It provides automatic management of data splitti

Federico Errica 194 Dec 22, 2022
This is code to fit per-pixel environment map with spherical Gaussian lobes, using LBFGS optimization

Spherical Gaussian Optimization This is code to fit per-pixel environment map with spherical Gaussian lobes, using LBFGS optimization. This code has b

41 Dec 14, 2022
Hunt down social media accounts by username across social networks

Hunt down social media accounts by username across social networks Installation | Usage | Docker Notes | Contributing Installation # clone the repo $

1 Dec 14, 2021
Part-aware Measurement for Robust Multi-View Multi-Human 3D Pose Estimation and Tracking

Part-aware Measurement for Robust Multi-View Multi-Human 3D Pose Estimation and Tracking Part-Aware Measurement for Robust Multi-View Multi-Human 3D P

19 Oct 27, 2022
An intelligent, flexible grammar of machine learning.

An english representation of machine learning. Modify what you want, let us handle the rest. Overview Nylon is a python library that lets you customiz

Palash Shah 79 Dec 02, 2022
1st place solution to the Satellite Image Change Detection Challenge hosted by SenseTime

1st place solution to the Satellite Image Change Detection Challenge hosted by SenseTime

Lihe Yang 209 Jan 01, 2023
PyTorch implementation of NeurIPS 2021 paper: "CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration"

CoFiNet: Reliable Coarse-to-fine Correspondences for Robust Point Cloud Registration (NeurIPS 2021) PyTorch implementation of the paper: CoFiNet: Reli

76 Jan 03, 2023
RL-driven agent playing tic-tac-toe on starknet against challengers.

tictactoe-on-starknet RL-driven agent playing tic-tac-toe on starknet against challengers. GUI reference: https://pythonguides.com/create-a-game-using

21 Jul 30, 2022
3D position tracking for soccer players with multi-camera videos

This repo contains a full pipeline to support 3D position tracking of soccer players, with multi-view calibrated moving/fixed video sequences as inputs.

Yuchang Jiang 72 Dec 27, 2022
Face-Recognition-based-Attendance-System - An implementation of Attendance System in python.

Face-Recognition-based-Attendance-System A real time implementation of Attendance System in python. Pre-requisites To understand the implentation of F

Muhammad Zain Ul Haque 1 Dec 31, 2021
PyTorch implementation of EGVSR: Efficcient & Generic Video Super-Resolution (VSR)

This is a PyTorch implementation of EGVSR: Efficcient & Generic Video Super-Resolution (VSR), using subpixel convolution to optimize the inference speed of TecoGAN VSR model. Please refer to the offi

789 Jan 04, 2023
ICML 21 - Voice2Series: Reprogramming Acoustic Models for Time Series Classification

Voice2Series-Reprogramming Voice2Series: Reprogramming Acoustic Models for Time Series Classification International Conference on Machine Learning (IC

49 Jan 03, 2023