This repository is no longer being updated. Future development of code tools for geospatial machine learning analysis will be done at https://github.com/cosmiq/solaris.

========= cw-nets

Segmentation Nets designed for use with SpaceNet datasets and other remote sensing data

An example of the output of this tool can be found at https://cwnets-demo.netlify.com/

Installation

Using conda

Create Virtual Environment

conda create -n cw-nets python-3.6 pip cython

Install geospatial requirements

conda install --name cw-nets \
                    rtree \
                    gdal

Install Deep Learning Frameworks:

conda install pytorch torchvision cuda91 -c pytorch
conda install opencv scikit-image

Install CosmiQ tools

pip install git+https://github.com/CosmiQ/cw-tiler.git@dataset_creation
pip install git+https://github.com/CosmiQ/cw-nets.git@pytorch_generator

Example

python create_mask.py --raster_path s3://spacenet-dataset/AOI_2_Vegas/srcData/rasterData/AOI_2_Vegas_MUL-PanSharpen_Cloud.tif \ --output_name AOI_2_Vegas_v11.tif \ --data_output $OUTPUT_PATH \ --model_path weights/deepglobe_buildings.pt \ --cell_size 200 \ --stride_size 190 \ --tile_size 650

Dependencies

• cw-tiler https://github.com/CosmiQ/cw-tiler
• numpy
• tqdm
• shapely
• rasterio
• opencv
• scikit-image
• scikit-learn
• tensorflow
• keras
• torch
• torchvision

License

See LICENSE.txt <LICENSE.txt>__.

Authors

See AUTHORS.txt <AUTHORS.txt>__.

Changes

See CHANGES.txt <CHANGES.txt>__.