Utilities for AI - Assisted Mapping fAIr
Project description
hot_fair_utilities ( Utilities for AI Assisted Mapping fAIr )
Initially lib was developed during Open AI Challenge with Omdeena. Learn more about challenge from here
hot_fair_utilities
Installation
hot_fair_utilities is collection of utilities which contains core logic for model data prepration , training and postprocessing . It can support multiple models , Currently ramp is supported.
- Install tensorflow
2.9.2
from [here] (https://www.tensorflow.org/install/pip) According to your os
Setup Ramp :
-
Clone ramp working dir
git clone https://github.com/kshitijrajsharma/ramp-code-fAIr.git ramp-code
-
Install native bindings
-
Install Numpy
pip install numpy==1.23.5
-
Install gdal .
for eg : on Ubuntu
sudo add-apt-repository ppa:ubuntugis/ppa && sudo apt-get update sudo apt-get install gdal-bin sudo apt-get install libgdal-dev export CPLUS_INCLUDE_PATH=/usr/include/gdal export C_INCLUDE_PATH=/usr/include/gdal pip install --global-option=build_ext --global-option="-I/usr/include/gdal" GDAL==`gdal-config --version`
on conda :
conda install -c conda-forge gdal
-
Install rasterio
for eg: on ubuntu :
sudo apt-get install -y python3-rasterio
on conda :
conda install -c conda-forge rasterio
-
-
Install ramp requirements
Install necessary requirements for ramp
cd colab && make install && cd ../..
-
Install hot_fair_utilities
``` pip install -e . ```
Conda Virtual Environment
Create from env fle
```
conda env create -f environment.yml
```
Create your own
```
conda create -n fAIr python=3.8
conda activate fAIr
conda install -c conda-forge gdal
conda install -c conda-forge geopandas
pip install pyogrio rasterio tensorflow
pip install -e hot_fair_utilities
```
Test Installation and workflow
You can run package_test.ipynb
to your pc to test the installation and workflow with sample data provided
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