This program will stylize your photos with fast neural style transfer.

Overview

Neural Style Transfer (NST) Using TensorFlow

Demo

TensorFlow

TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.

Neural Style Transfer

This program will stylize your photos with fast neural style transfer. By the way, Neural style transfer is an optimization technique used to take two images a content image and a style reference image (such as an artwork by a famous painter) and blend them together so the output image looks like the content image, but painted in the style of the style reference image.

Steps :

1 - Install libraries

The libraries used in this project are :

  • matplotlib
  • numpy
  • TensorFlow
  • tensorflow_hub
  • pillow

2 - Functions

  • Load Images
  • Visualize Images

3 - Original and Style Images

4 - Arbitrary Image Stylization

Final Step - Exporting the Result

Conclusion

Congrats! We have created a unique artwork using TensorFlow with neural network. Programming is not just about solving problems. We can also use it for fascinating and artistic projects like this one. These kinds of projects helps me a lot to practice new skills. TensorFlow is one of the best when it comes to building machine learning/deep learning projects.

© 2021 - Made with love By Ismailium

Owner
Ismail Boularbah
Cuber and Self-taught Full-stack Developer, I enjoy building responsive web apps & designs using ReactJS, Firebase, MongoDB, Restful API's..
Ismail Boularbah
Contrastive Learning Inverts the Data Generating Process

Official code to reproduce the results and data presented in the paper Contrastive Learning Inverts the Data Generating Process.

71 Nov 25, 2022
Implementation of the federated dual coordinate descent (FedDCD) method.

FedDCD.jl Implementation of the federated dual coordinate descent (FedDCD) method. Installation To install, just call Pkg.add("https://github.com/Zhen

Zhenan Fan 6 Sep 21, 2022
Simple and Robust Loss Design for Multi-Label Learning with Missing Labels

Simple and Robust Loss Design for Multi-Label Learning with Missing Labels Official PyTorch Implementation of the paper Simple and Robust Loss Design

Xinyu Huang 28 Oct 27, 2022
Learned model to estimate number of distinct values (NDV) of a population using a small sample.

Learned NDV estimator Learned model to estimate number of distinct values (NDV) of a population using a small sample. The model approximates the maxim

2 Nov 21, 2022
Keras-1D-NN-Classifier

Keras-1D-NN-Classifier This code is based on the reference codes linked below. reference 1, reference 2 This code is for 1-D array data classification

Jae-Hoon Shim 6 May 18, 2021
[CVPR 2021 Oral] ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis

ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis [arxiv|pdf|v

Yinan He 78 Dec 22, 2022
The official pytorch implementation of our paper "Is Space-Time Attention All You Need for Video Understanding?"

TimeSformer This is an official pytorch implementation of Is Space-Time Attention All You Need for Video Understanding?. In this repository, we provid

Facebook Research 1k Dec 31, 2022
OBBDetection: an oriented object detection toolbox modified from MMdetection

OBBDetection note: If you have questions or good suggestions, feel free to propose issues and contact me. introduction OBBDetection is an oriented obj

MIXIAOXIN_HO 3 Nov 11, 2022
Deep Networks with Recurrent Layer Aggregation

RLA-Net: Recurrent Layer Aggregation Recurrence along Depth: Deep Networks with Recurrent Layer Aggregation This is an implementation of RLA-Net (acce

Joy Fang 21 Aug 16, 2022
Automatic Calibration for Non-repetitive Scanning Solid-State LiDAR and Camera Systems

ACSC Automatic extrinsic calibration for non-repetitive scanning solid-state LiDAR and camera systems. System Architecture 1. Dependency Tested with U

KINO 192 Dec 13, 2022
Action Recognition for Self-Driving Cars

Action Recognition for Self-Driving Cars This repo contains the codes for the 2021 Fall semester project "Action Recognition for Self-Driving Cars" at

VITA lab at EPFL 3 Apr 07, 2022
The official PyTorch implementation of recent paper - SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

This repository is the official PyTorch implementation of SAINT. Find the paper on arxiv SAINT: Improved Neural Networks for Tabular Data via Row Atte

Gowthami Somepalli 284 Dec 21, 2022
novel deep learning research works with PaddlePaddle

Research 发布基于飞桨的前沿研究工作,包括CV、NLP、KG、STDM等领域的顶会论文和比赛冠军模型。 目录 计算机视觉(Computer Vision) 自然语言处理(Natrual Language Processing) 知识图谱(Knowledge Graph) 时空数据挖掘(Spa

1.5k Dec 29, 2022
Implementation for Paper "Inverting Generative Adversarial Renderer for Face Reconstruction"

StyleGAR TODO: add arxiv link Implementation of Inverting Generative Adversarial Renderer for Face Reconstruction TODO: for test Currently, some model

155 Oct 27, 2022
Bridging Vision and Language Model

BriVL BriVL (Bridging Vision and Language Model) 是首个中文通用图文多模态大规模预训练模型。BriVL模型在图文检索任务上有着优异的效果,超过了同期其他常见的多模态预训练模型(例如UNITER、CLIP)。 BriVL论文:WenLan: Bridgi

235 Dec 27, 2022
TriMap: Large-scale Dimensionality Reduction Using Triplets

TriMap TriMap is a dimensionality reduction method that uses triplet constraints to form a low-dimensional embedding of a set of points. The triplet c

Ehsan Amid 235 Dec 24, 2022
Code of the lileonardo team for the 2021 Emotion and Theme Recognition in Music task of MediaEval 2021

Emotion and Theme Recognition in Music The repository contains code for the submission of the lileonardo team to the 2021 Emotion and Theme Recognitio

Vincent Bour 8 Aug 02, 2022
WTTE-RNN a framework for churn and time to event prediction

WTTE-RNN Weibull Time To Event Recurrent Neural Network A less hacky machine-learning framework for churn- and time to event prediction. Forecasting p

Egil Martinsson 727 Dec 28, 2022
Collision risk estimation using stochastic motion models

collision_risk_estimation Collision risk estimation using stochastic motion models. This is a new approach, based on stochastic models, to predict the

Unmesh 7 Jun 26, 2022