Bringing Computer Vision and Flutter together , to build an awesome app !!

Overview
Banner

Logo

Bringing Computer Vision and Flutter together , to build an awesome app !!

Explore the Directories

Flutter · Machine Learning

Table of Contents
  1. About The Project
  2. Getting Started
  3. Roadmap
  4. Contributing
  5. Contact

About The Project

This project is an app for recreating the beauty captured by your mobile device through the eyes of the greatest artists of the world !! We are using GAN models to create filters that can reconstruct the artistic style of the great painters !!

Link to APK : https://drive.google.com/file/d/1q5FWZqEMPLAJkh9COB6UFDOF7KHqi5kU/view?usp=sharing

Built With

Technologies used are : dart flutter tf keras

App View

Original Output Original Output

Getting Started

This project has been categorized into two parts - Machine Learning and Flutter.

  • Machine Learning - This part deals with Computer Vision and GANs.
  • Flutter - This part deals with developing the app using flutter framework.

Roadmap

See the open issues for a list of Projects you can work on (and learn).

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated. Your contributions would help other beginners !!

  1. Fork the Project
  2. In the command terminal, run the following commands:
    $ git clone https://github.com/{your username}/Illicit-Illustrations
    $ cd Illicit_Illustrations/
  1. Make the changes and add the features to the domains you want to work on
  2. Commit your Changes ( git commit -m 'Add the Project' )
  3. Push to the Branch ( git push --all )
  4. Open a Pull Request

Contact

Mail us at - gmail

Owner
Padmanabha Banerjee
I am deeply into learning !
Padmanabha Banerjee
G-NIA model from "Single Node Injection Attack against Graph Neural Networks" (CIKM 2021)

Single Node Injection Attack against Graph Neural Networks This repository is our Pytorch implementation of our paper: Single Node Injection Attack ag

Shuchang Tao 18 Nov 21, 2022
Safe Bayesian Optimization

SafeOpt - Safe Bayesian Optimization This code implements an adapted version of the safe, Bayesian optimization algorithm, SafeOpt [1], [2]. It also p

Felix Berkenkamp 111 Dec 11, 2022
[NeurIPS'21] Shape As Points: A Differentiable Poisson Solver

Shape As Points (SAP) Paper | Project Page | Short Video (6 min) | Long Video (12 min) This repository contains the implementation of the paper: Shape

394 Dec 30, 2022
Simple machine learning library / 簡單易用的機器學習套件

FukuML Simple machine learning library / 簡單易用的機器學習套件 Installation $ pip install FukuML Tutorial Lesson 1: Perceptron Binary Classification Learning Al

Fukuball Lin 279 Sep 15, 2022
This is the reference implementation for "Coresets via Bilevel Optimization for Continual Learning and Streaming"

Coresets via Bilevel Optimization This is the reference implementation for "Coresets via Bilevel Optimization for Continual Learning and Streaming" ht

Zalán Borsos 51 Dec 30, 2022
Fully convolutional deep neural network to remove transparent overlays from images

Fully convolutional deep neural network to remove transparent overlays from images

Marc Belmont 1.1k Jan 06, 2023
Transfer Reinforcement Learning for Differing Action Spaces via Q-Network Representations

Transfer-Learning-in-Reinforcement-Learning Transfer Reinforcement Learning for Differing Action Spaces via Q-Network Representations Final Report Tra

Trung Hieu Tran 4 Oct 17, 2022
基于Paddle框架的fcanet复现

fcanet-Paddle 基于Paddle框架的fcanet复现 fcanet 本项目基于paddlepaddle框架复现fcanet,并参加百度第三届论文复现赛,将在2021年5月15日比赛完后提供AIStudio链接~敬请期待 参考项目: frazerlin-fcanet 数据准备 本项目已挂

QuanHao Guo 7 Mar 07, 2022
The open source code of SA-UNet: Spatial Attention U-Net for Retinal Vessel Segmentation.

SA-UNet: Spatial Attention U-Net for Retinal Vessel Segmentation(ICPR 2020) Overview This code is for the paper: Spatial Attention U-Net for Retinal V

Changlu Guo 151 Dec 28, 2022
This is a five-step framework for the development of intrusion detection systems (IDS) using machine learning (ML) considering model realization, and performance evaluation.

AB-TRAP: building invisibility shields to protect network devices The AB-TRAP framework is applicable to the development of Network Intrusion Detectio

Lab-C2DC - Laboratory of Command and Control and Cyber-security 17 Jan 04, 2023
ViDT: An Efficient and Effective Fully Transformer-based Object Detector

ViDT: An Efficient and Effective Fully Transformer-based Object Detector by Hwanjun Song1, Deqing Sun2, Sanghyuk Chun1, Varun Jampani2, Dongyoon Han1,

NAVER AI 262 Dec 27, 2022
2021-AIAC-QQ-Browser-Hyperparameter-Optimization-Rank6

2021-AIAC-QQ-Browser-Hyperparameter-Optimization-Rank6

Aigege 8 Mar 31, 2022
Bagua is a flexible and performant distributed training algorithm development framework.

Bagua is a flexible and performant distributed training algorithm development framework.

786 Dec 17, 2022
KDD CUP 2020 Automatic Graph Representation Learning: 1st Place Solution

KDD CUP 2020: AutoGraph Team: aister Members: Jianqiang Huang, Xingyuan Tang, Mingjian Chen, Jin Xu, Bohang Zheng, Yi Qi, Ke Hu, Jun Lei Team Introduc

96 May 30, 2022
NR-GAN: Noise Robust Generative Adversarial Networks

Lexicon Enhanced Chinese Sequence Labeling Using BERT Adapter Code and checkpoints for the ACL2021 paper "Lexicon Enhanced Chinese Sequence Labelling

Takuhiro Kaneko 59 Dec 11, 2022
MOOSE (Multi-organ objective segmentation) a data-centric AI solution that generates multilabel organ segmentations to facilitate systemic TB whole-person research

MOOSE (Multi-organ objective segmentation) a data-centric AI solution that generates multilabel organ segmentations to facilitate systemic TB whole-person research.The pipeline is based on nn-UNet an

QIMP team 30 Jan 01, 2023
Machine learning and Deep learning models, deploy on telegram (the best social media)

Semi Intelligent BOT The project involves : Classifying fake news Classifying objects such as aeroplane, automobile, bird, cat, deer, dog, frog, horse

MohammadReza Norouzi 5 Mar 06, 2022
Methods to get the probability of a changepoint in a time series.

Bayesian Changepoint Detection Methods to get the probability of a changepoint in a time series. Both online and offline methods are available. Read t

Johannes Kulick 554 Dec 30, 2022
TensorFlow Tutorials with YouTube Videos

TensorFlow Tutorials Original repository on GitHub Original author is Magnus Erik Hvass Pedersen Introduction These tutorials are intended for beginne

9.1k Jan 02, 2023
Code for the paper "Improved Techniques for Training GANs"

Status: Archive (code is provided as-is, no updates expected) improved-gan code for the paper "Improved Techniques for Training GANs" MNIST, SVHN, CIF

OpenAI 2.2k Jan 01, 2023