NIMA: Neural IMage Assessment

Overview

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

License

This project is licensed under the MIT License - see the LICENSE file for details

Acknowledgments

Owner
Kyryl Truskovskyi
Machine Learning Engineer 🇺🇦🇨🇦
Kyryl Truskovskyi
Python script that analyses the given datasets and comes up with the best polynomial regression representation with the smallest polynomial degree possible

Python script that analyses the given datasets and comes up with the best polynomial regression representation with the smallest polynomial degree possible, to be the most reliable with the least com

Nikolas B Virionis 2 Aug 01, 2022
A collection of semantic image segmentation models implemented in TensorFlow

A collection of semantic image segmentation models implemented in TensorFlow. Contains data-loaders for the generic and medical benchmark datasets.

bobby 16 Dec 06, 2019
Animation of solving the traveling salesman problem to optimality using mixed-integer programming and iteratively eliminating sub tours

tsp-streamlit Animation of solving the traveling salesman problem to optimality using mixed-integer programming and iteratively eliminating sub tours.

4 Nov 05, 2022
3ds-Ghidra-Scripts - Ghidra scripts to help with 3ds reverse engineering

3ds Ghidra Scripts These are ghidra scripts to help with 3ds reverse engineering

Zak 7 May 23, 2022
Official implementation of Rich Semantics Improve Few-Shot Learning (BMVC, 2021)

Rich Semantics Improve Few-Shot Learning Paper Link Abstract : Human learning benefits from multi-modal inputs that often appear as rich semantics (e.

Mohamed Afham 11 Jul 26, 2022
Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set (CVPRW 2019). A PyTorch implementation.

Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set —— PyTorch implementation This is an unofficial offici

Sicheng Xu 833 Dec 28, 2022
[CVPR 2021] Released code for Counterfactual Zero-Shot and Open-Set Visual Recognition

Counterfactual Zero-Shot and Open-Set Visual Recognition This project provides implementations for our CVPR 2021 paper Counterfactual Zero-S

144 Dec 24, 2022
Jarvis Project is a basic virtual assistant that uses TensorFlow for learning.

Jarvis_proyect Jarvis Project is a basic virtual assistant that uses TensorFlow for learning. Latest version 0.1 Features: Good morning protocol Tell

Anze Kovac 3 Aug 31, 2022
Physics-Aware Training (PAT) is a method to train real physical systems with backpropagation.

Physics-Aware Training (PAT) is a method to train real physical systems with backpropagation. It was introduced in Wright, Logan G. & Onodera, Tatsuhiro et al. (2021)1 to train Physical Neural Networ

McMahon Lab 230 Jan 05, 2023
Video Instance Segmentation using Inter-Frame Communication Transformers (NeurIPS 2021)

Video Instance Segmentation using Inter-Frame Communication Transformers (NeurIPS 2021) Paper Video Instance Segmentation using Inter-Frame Communicat

Sukjun Hwang 81 Dec 29, 2022
Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21

Skeletal-GNN Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21 Various deep learning techniques have been propose

37 Oct 23, 2022
It is an open dataset for object detection in remote sensing images.

RSOD-Dataset It is an open dataset for object detection in remote sensing images. The dataset includes aircraft, oiltank, playground and overpass. The

136 Dec 08, 2022
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

152 Jan 02, 2023
ServiceX Transformer that converts flat ROOT ntuples into columnwise data

ServiceX_Uproot_Transformer ServiceX Transformer that converts flat ROOT ntuples into columnwise data Usage You can invoke the transformer from the co

Vis 0 Jan 20, 2022
A PyTorch Implementation of "SINE: Scalable Incomplete Network Embedding" (ICDM 2018).

Scalable Incomplete Network Embedding ⠀⠀ A PyTorch implementation of Scalable Incomplete Network Embedding (ICDM 2018). Abstract Attributed network em

Benedek Rozemberczki 69 Sep 22, 2022
Repository of best practices for deep learning in Julia, inspired by fastai

FastAI Docs: Stable | Dev FastAI.jl is inspired by fastai, and is a repository of best practices for deep learning in Julia. Its goal is to easily ena

FluxML 532 Jan 02, 2023
Distributional Sliced-Wasserstein distance code

Distributional Sliced Wasserstein distance This is a pytorch implementation of the paper "Distributional Sliced-Wasserstein and Applications to Genera

VinAI Research 39 Jan 01, 2023
AdamW optimizer for bfloat16 models in pytorch.

Image source AdamW optimizer for bfloat16 models in pytorch. Bfloat16 is currently an optimal tradeoff between range and relative error for deep netwo

Alex Rogozhnikov 8 Nov 20, 2022
Python implementation of "Elliptic Fourier Features of a Closed Contour"

PyEFD An Python/NumPy implementation of a method for approximating a contour with a Fourier series, as described in [1]. Installation pip install pyef

Henrik Blidh 71 Dec 09, 2022
《Deep Single Portrait Image Relighting》(ICCV 2019)

Ratio Image Based Rendering for Deep Single-Image Portrait Relighting [Project Page] This is part of the Deep Portrait Relighting project. If you find

62 Dec 21, 2022