A Deep learning based streamlit web app which can tell with which bollywood celebrity your face resembles.

Overview

Project Name: Which Bollywood Celebrity You look like

A Deep learning based streamlit web app which can tell with which bollywood celebrity your face resembles.

Face recognition is the problem of identifying and verifying people in a photograph by their face. It is a task that is trivially performed by humans, even under varying light and when faces are changed by age or obstructed with accessories and facial hair. Nevertheless, it is remained a challenging computer vision problem for decades until recently.

Deep learning methods are able to leverage very large datasets of faces and learn rich and compact representations of faces, allowing modern models to first perform as-well and later to outperform the face recognition capabilities of humans.

In this project, you will discover the problem of face recognition and how deep learning methods can achieve superhuman performance to identify similar faces.

Original repo:

https://github.com/entbappy/Which-Bollywood-Celebrity-You-look-like

Demo Video:

https://www.youtube.com/watch?v=lYSsLFgFzBk&list=PLkz_y24mlSJYI78C1IZJaghNvC7dh6red&index=6

This is a methods of identifying similar faces check various aspects on pictures, including: face shape, nose, eyes and mouth; face position in the picture; skin color (including the lighting of the photo); color and hair and cosine_similarity.

Dataset has beem used:

https://www.kaggle.com/sushilyadav1998/bollywood-celeb-localized-face-dataset

Some Real Time Demo:

Web app look

workflow

Lets check some of images

workflow

workflow

This really performing good you can consider by seeing this result 😀

workflow

The fun part is I am looked like Riteish Deshmukh 😄 😁

workflow

STEPS to run this project:

You can also use others images instead of bollywood actress

STEP 01:

Clone the repository

git clone https://github.com/entbappy/Which-Bollywood-Celebrity-You-look-like.git

STEP 02:

Create an environment

conda create -n celebrity python=3.7 -y

STEP 03:

Install the requirements

pip install -r requirements.txt

STEP 04:

Download the data from the link and keep it in your project directory. Make sure all the actress folder should be in just one folder called data, like that

workflow

STEP 05:

Just execute this command one time if you are not changing the data

python run.py

STEP 06:

Now to start the webapp run the following command

streamlit run app.py

yes!! Now you can start predicting 🙂

Authors:

Author: Bappy Ahmed
Data Scientist
Email: [email protected]
Owner
BAPPY AHMED
A Data Scientist by Profession 🙂
BAPPY AHMED
Code to reproduce the experiments from our NeurIPS 2021 paper " The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective"

Code To run: python runner.py new --save SAVE_NAME --data PATH_TO_DATA_DIR --dataset DATASET --model model_name [options] --n 1000 - train - t

Geoff Pleiss 5 Dec 12, 2022
TICC is a python solver for efficiently segmenting and clustering a multivariate time series

TICC TICC is a python solver for efficiently segmenting and clustering a multivariate time series. It takes as input a T-by-n data matrix, a regulariz

406 Dec 12, 2022
CAPITAL: Optimal Subgroup Identification via Constrained Policy Tree Search

CAPITAL: Optimal Subgroup Identification via Constrained Policy Tree Search This repository is the official implementation of CAPITAL: Optimal Subgrou

Hengrui Cai 0 Oct 19, 2021
deep learning for image processing including classification and object-detection etc.

深度学习在图像处理中的应用教程 前言 本教程是对本人研究生期间的研究内容进行整理总结,总结的同时也希望能够帮助更多的小伙伴。后期如果有学习到新的知识也会与大家一起分享。 本教程会以视频的方式进行分享,教学流程如下: 1)介绍网络的结构与创新点 2)使用Pytorch进行网络的搭建与训练 3)使用Te

WuZhe 13.6k Jan 04, 2023
Adversarial Framework for (non-) Parametric Image Stylisation Mosaics

Fully Adversarial Mosaics (FAMOS) Pytorch implementation of the paper "Copy the Old or Paint Anew? An Adversarial Framework for (non-) Parametric Imag

Zalando Research 120 Dec 24, 2022
Learning Continuous Signed Distance Functions for Shape Representation

DeepSDF This is an implementation of the CVPR '19 paper "DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation" by Park et a

Meta Research 1.1k Jan 01, 2023
CNN designed for pansharpening

PROGRESSIVE BAND-SEPARATED CONVOLUTIONAL NEURAL NETWORK FOR MULTISPECTRAL PANSHARPENING This repository contains main code for the paper PROGRESSIVE B

SerendipitysX 3 Dec 29, 2021
CTRL-C: Camera calibration TRansformer with Line-Classification

CTRL-C: Camera calibration TRansformer with Line-Classification This repository contains the official code and pretrained models for CTRL-C (Camera ca

57 Nov 14, 2022
Retrieval.pytorch - The code we used in [2020 DIGIX]

Retrieval.pytorch - The code we used in [2020 DIGIX]

Guo-Hua Wang 2 Feb 07, 2022
Self-Supervised Learning with Kernel Dependence Maximization

Self-Supervised Learning with Kernel Dependence Maximization This is the code for SSL-HSIC, a self-supervised learning loss proposed in the paper Self

DeepMind 29 Dec 29, 2022
A Python package for time series augmentation

tsaug tsaug is a Python package for time series augmentation. It offers a set of augmentation methods for time series, as well as a simple API to conn

Arundo Analytics 278 Jan 01, 2023
PyTorch experiments with the Zalando fashion-mnist dataset

zalando-pytorch PyTorch experiments with the Zalando fashion-mnist dataset Project Organization ├── LICENSE ├── Makefile - Makefile with co

Federico Baldassarre 31 Sep 25, 2021
A setup script to generate ITK Python Wheels

ITK Python Package This project provides a setup.py script to build ITK Python binary packages and infrastructure to build ITK external module Python

Insight Software Consortium 59 Dec 14, 2022
PyTorch code for the paper: FeatMatch: Feature-Based Augmentation for Semi-Supervised Learning

FeatMatch: Feature-Based Augmentation for Semi-Supervised Learning This is the PyTorch implementation of our paper: FeatMatch: Feature-Based Augmentat

43 Nov 19, 2022
Reinforcement-learning - Repository of the class assignment questions for the course on reinforcement learning

DSE 314/614: Reinforcement Learning This repository containing reinforcement lea

Manav Mishra 4 Apr 15, 2022
Official Implementation for the "An Empirical Investigation of 3D Anomaly Detection and Segmentation" paper.

An Empirical Investigation of 3D Anomaly Detection and Segmentation Project | Paper Official PyTorch Implementation for the "An Empirical Investigatio

Eliahu Horwitz 55 Dec 14, 2022
Beyond Image to Depth: Improving Depth Prediction using Echoes (CVPR 2021)

Beyond Image to Depth: Improving Depth Prediction using Echoes (CVPR 2021) Kranti Kumar Parida, Siddharth Srivastava, Gaurav Sharma. We address the pr

Kranti Kumar Parida 33 Jun 27, 2022
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data

Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data arXiv This is the code base for weakly supervised NER. We provide a

Amazon 92 Jan 04, 2023
An implementation of the BADGE batch active learning algorithm.

Batch Active learning by Diverse Gradient Embeddings (BADGE) An implementation of the BADGE batch active learning algorithm. Details are provided in o

125 Dec 24, 2022