How to Implement Neural Image Assessment with PyTorch

PyTorch NIMA: Neural IMage Assessment

PyTorch implementation of Neural IMage Assessment by Hossein Talebi and Peyman Milanfar. You can learn more from this post at Google Research Blog.

Installing

Docker

docker run -it truskovskiyk/nima:latest /bin/bash

PYPI package (In Progress)

pip install nima

VirtualEnv

git clone https://github.com/truskovskiyk/nima.pytorch.git
cd nima.pytorch
virtualenv -p python3.7 env
source ./env/bin/activate

Dataset

The model was trained on the AVA (Aesthetic Visual Analysis) dataset You can get it from here Here are some examples of images with theire scores result1

Pre-train model (In Progress)


Deployment (In progress)


Usage

nima-cli

Usage: cli.py [OPTIONS] COMMAND [ARGS]...

Options:
  --help  Show this message and exit.

Commands:
  get_image_score  Get image scores
  prepare_dataset  Parse, clean and split dataset
  run_web_api      Start server for model serving
  train_model      Train model
  validate_model   Validate model

Previous version of this project is still valid and works

you can find here

Contributing

Contributing are welcome

Acknowledgments


Download Details:

Author: truskovskiyk
Source Code: https://github.com/truskovskiyk/nima.pytorch 
License: MIT license

#machinelearning #python #pytorch #deeplearning 

How to Implement Neural Image Assessment with PyTorch
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