hot-fair-utilities 1.0.43

Utilities for AI - Assisted Mapping fAIr

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.

1. To get started clone this repo first :

   git clone https://github.com/hotosm/fAIr-utilities.git
   

2. Setup your virtualenv with python 3.8 ( Ramp is tested with python 3.8 )

3. Install tensorflow 2.9.2 from [here] (https://www.tensorflow.org/install/pip) According to your os

Setup Ramp :

4. Copy your basemodel : Basemodel is derived from ramp basemodel

   git clone https://github.com/radiantearth/model_ramp_baseline.git
   

5. Clone ramp working dir

   git clone https://github.com/kshitijrajsharma/ramp-code-fAIr.git ramp-code
   

6. Copy base model to ramp-code

   cp -r model_ramp_baseline/data/input/checkpoint.tf ramp-code/ramp/checkpoint.tf
   

7. 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
     

8. Install ramp requirements

   Install necessary requirements for ramp and hot_fair_utilites

   cd ramp-code && cd colab && make install  && cd ../.. && 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