This script runs neural style transfer against the provided content image.

Overview

Neural Style Transfer

Content Style Output

Description:

This script runs neural style transfer against the provided content image. The content image must be present in the src/data/content directory. All style images, that are in the directory src/data/style will be applied against it. The outputs will be saved in generated/ directory as .png files. By default, the input images (both style and content images, as they must be of the same dimensionality) will be transformed to the 512x512 size for the algorithm, and output image will be of size 512x512 as well. To change that, please use additional script arguments.

The neural networks architecture is based on the documentation provided by PyTorch, which itself uses Neural-Style algorithm developed by Leon A. Gatys, Alexander S. Ecker and Matthias Bethge.

Usage examples:

./main.py -i 
   
   
    
    
./main.py --image 
    
    
     
     
python3 main.py -i 
     
     
      
      
python3 main.py --image 
      
      
       
       

./main.py -i 
       
       
         -he 1024 -wi 1024 ./main.py --image 
        
          -height 1024 -width 1024 
         
       
      
      
     
     
    
    
   
   

Script arguments:

Required arguments:
  -i IMAGE, --image IMAGE
                        Content image to be taken as input. The file must be present in src/data/content.

Optional arguments:
  -h, --help            Show help message and exit.
  -he HEIGHT, --height HEIGHT
                        Sets the height of the input and output images. The default value is 512.
  -wi WIDTH, --width WIDTH
                        Sets the width of the input and output images. The default value is 512.

Setup

Python 3.9 must be installed on the operating system. To install the needed python dependencies run:

pip3 install -r requirements.txt

To run the script as ./main.py -i or to run the linter script, one might need to give executable permissions:

chmod -x main.py
chmod -x ./scripts/lint.sh

To run the black formatter and pylint linter, please run:

./scripts/lint.sh

The script ./scripts/lint_check.sh will be run as GitHub action, and will fail if any possible changes are detected.

Owner
Martynas Subonis
Full-Stack Software Engineer
Martynas Subonis
Supervised 3D Pre-training on Large-scale 2D Natural Image Datasets for 3D Medical Image Analysis

Introduction This is an implementation of our paper Supervised 3D Pre-training on Large-scale 2D Natural Image Datasets for 3D Medical Image Analysis.

24 Dec 06, 2022
RETRO-pytorch - Implementation of RETRO, Deepmind's Retrieval based Attention net, in Pytorch

RETRO - Pytorch (wip) Implementation of RETRO, Deepmind's Retrieval based Attent

Phil Wang 556 Jan 04, 2023
PyTorch Kafka Dataset: A definition of a dataset to get training data from Kafka.

PyTorch Kafka Dataset: A definition of a dataset to get training data from Kafka.

ERTIS Research Group 7 Aug 01, 2022
Deep Learning & 3D Convolutional Neural Networks for Speaker Verification

TensorFlow implementation of 3D Convolutional Neural Networks for Speaker Verification - Official Project Page - Pytorch Implementation This repositor

Amirsina Torfi 753 Dec 17, 2022
[MICCAI'20] AlignShift: Bridging the Gap of Imaging Thickness in 3D Anisotropic Volumes

AlignShift NEW: Code for our new MICCAI'21 paper "Asymmetric 3D Context Fusion for Universal Lesion Detection" will also be pushed to this repository

Medical 3D Vision 42 Jan 06, 2023
Machine Learning Framework for Operating Systems - Brings ML to Linux kernel

KML: A Machine Learning Framework for Operating Systems & Storage Systems Storage systems and their OS components are designed to accommodate a wide v

File systems and Storage Lab (FSL) 186 Nov 24, 2022
Reinforcement Learning for finance

Reinforcement Learning for Finance We apply reinforcement learning for stock trading. Fetch Data Example import utils # fetch symbols from yahoo fina

Tomoaki Fujii 159 Jan 03, 2023
Trafffic prediction analysis using hybrid models - Machine Learning

Hybrid Machine learning Model Clone the Repository Create a new Directory as assests and download the model from the below link Model Link To Start th

1 Feb 08, 2022
Official PyTorch implementation of "BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation" (NeurIPS 2021)

BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation Official PyTorch implementation of the NeurIPS 2021 paper Mingcong Liu, Qiang

onion 462 Dec 29, 2022
Employee-Managment - Company employee registration software in the face recognition system

Employee-Managment Company employee registration software in the face recognitio

Alireza Kiaeipour 7 Jul 10, 2022
On Effective Scheduling of Model-based Reinforcement Learning

On Effective Scheduling of Model-based Reinforcement Learning Code to reproduce the experiments in On Effective Scheduling of Model-based Reinforcemen

laihang 8 Oct 07, 2022
Code for the AI lab course 2021/2022 of the University of Verona

AI-Lab Code for the AI lab course 2021/2022 of the University of Verona Set-Up the environment for the curse Download Anaconda for your System. Instal

Davide Corsi 5 Oct 19, 2022
Generating Videos with Scene Dynamics

Generating Videos with Scene Dynamics This repository contains an implementation of Generating Videos with Scene Dynamics by Carl Vondrick, Hamed Pirs

Carl Vondrick 706 Jan 04, 2023
A graph neural network (GNN) model to predict protein-protein interactions (PPI) with no sample features

A graph neural network (GNN) model to predict protein-protein interactions (PPI) with no sample features

2 Jul 25, 2022
Detectron2-FC a fast construction platform of neural network algorithm based on detectron2

What is Detectron2-FC Detectron2-FC a fast construction platform of neural network algorithm based on detectron2. We have been working hard in two dir

董晋宗 9 Jun 06, 2022
Interpolation-based reduced-order models

Interpolation-reduced-order-models Interpolation-based reduced-order models High-fidelity computational fluid dynamics (CFD) solutions are time consum

Donovan Blais 1 Jan 10, 2022
Face recognition project by matching the features extracted using SIFT.

MV_FaceDetectionWithSIFT Face recognition project by matching the features extracted using SIFT. By : Aria Radmehr Professor : Ali Amiri Dependencies

Aria Radmehr 4 May 31, 2022
Art Project "Schrödinger's Game of Life"

Repo of the project "Team Creative Quantum AI: Schrödinger's Game of Life" Installation new conda env: conda create --name qcml python=3.8 conda activ

ℍ◮ℕℕ◭ℍ ℝ∈ᛔ∈ℝ 2 Sep 15, 2022
[CVPRW 2022] Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network

Attention Helps CNN See Better: Hybrid Image Quality Assessment Network [CVPRW 2022] Code for Hybrid Image Quality Assessment Network [paper] [code] T

IIGROUP 49 Dec 11, 2022
PyTorch implementation of a Real-ESRGAN model trained on custom dataset

Real-ESRGAN PyTorch implementation of a Real-ESRGAN model trained on custom dataset. This model shows better results on faces compared to the original

Sber AI 160 Jan 04, 2023