The Model_Trainer.ipynb file in the root directory provides a template for training the deepsdf model
It's best to run this in google colab with GPU activated
Python and Conda must be installed in order to run the application. The easiest way to get these is to install https://docs.conda.io/en/latest/miniconda.html
##INSTALLATION##
From the anaconda prompt run:
gets the code:
git clone https://github.com/antmillar/latentSDF.git
cd latentSDF
creates a conda environment and installs all the required libraries:
conda env create -f latentsdf.yml
conda activate latentsdf
##RUNNING##
python app.py
Once the app is running you should see the following:
* Serving Flask app "app" (lazy loading)
* Environment: production
WARNING: This is a development server. Do not use it in a production deployment.
Use a production WSGI server instead.
* Debug mode: off
* Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)
Open this address in a browser to load the application. The application is optimised to firefox, but should work in other browsers though the layout might not be optimal.
Notes:
conda may need to be manually added to your PATH if a conda not a recognized command error is returned.
Pre-prepared model zips can be found in /static/models/torch. The upload model button should target this directory by default.