Image segmentation with private İstanbul Dataset

Related tags

Deep Learning Image-Segmentation
Overview

Image Segmentation

This repo was created for academic research and test result. Repo will update after academic article online.

This repo contains weights of Unet++ model with SE-ResNeXt101 encoder trained with our private Istanbul dataset and Inria and Massachusetts datasets seperately. Trainings have been realized using PyTorch and segmentation models library. We also provide an inference notebook to run prediction on GeoTiff images. This notebook also outputs prediction images as GeoTiff.

Weights Files

You can use the following links to download weights files:
  • Unet++ trained with Istanbul Dataset: Download
  • Unet++ trained with Inria Dataset: Download
  • Unet++ trained with Massachusetts Dataset: Download
  • Unet++ with InceptionResNetv2 encoder: Download
  • Unet++ with EfficientNet-b6 encoder: Download
  • UNet with SE-ResNeXt101 encoder: Download
  • UNet with InceptionResNetv2 encoder: Download
  • UNet with EfficientNet-b6 encoder: Download
  • DeepLabv3+ with SE-ResNeXt101 encoder:Download

Stack and Requirements

To run the notebook, following libraries are required:
  • torch == 1.7.1
  • segmentation-models-pytorch == 0.1.3
  • scikit-image = 0.18.1
  • GDAL == 3.2.1
  • tifffile == 2021.2.1
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