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
Installing all libraries could be pain so we suggest you to use docker , If you like to do it bare , You can follow .github/build.yml
Clone repo
git clone https://github.com/hotosm/fAIr-utilities.git
Navigate to fAIr-utilities
cd fAIr-utilities
Build Docker
docker build --tag fairutils .
Run Container with default Jupyter Notebook , Or add bash at end to see terminal
docker run -it --rm --gpus=all -p 8888:8888 fairutils
[Optional] If you have downloaded RAMP already , By Default tf is set as Ramp_Home , You can change that by attaching your ramp-home volume to container as tf
if not you can skip this step , Ramp code will be downloaded on package_test.ipynb
-v /home/hotosm/fAIr-utilities:/tf
Test inside Docker Container
docker run -it --rm --gpus=all -p 8888:8888 fairutils bash
python test_app.py
Test Installation and workflow
You can run package_test.ipynb on your notebook from docker to test the installation and workflow with sample data provided , Or open with collab and connect your runtime locally
Get started with development
Now you can play with your data , use your own data , use different models for testing and also Help me Improve me !
Version Control
Follow Version Control Docs to publish and maintain new version
Release history Release notifications | RSS feed
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