It's A ML based Web Site build with python and Django to find the breed of the dog

Overview

ML-Based-Dog-Breed-Identifier

This is a Django Based Web Site To Identify the Breed of which your DOG belogs All You Need To Do is to Follow These Steps

Home Page

Result Page

Project Maintainer/Owner


Sanskar Dwivedi

Contributors/Admin


Yash Sakre

Piyush Kumar Dewangan

Rajat Naik

Setup Discription

you need to install following libraries to run this python program in cmd

pip install tensorflow
pip install keras
pip install django
pip install numpy

Compilation Steps

Just Goto the Project Directory and Paste this Command

python manage.py runserver

How to Contribute 🤔

You can contribute by adding new scripts, improving current scripts or documentation. Here are some instructions before making a Pull Request:

  • Take a look at Contributing Guide
  • Take a look at the Existing Issues or create your own Issues!
  • Wait for the Issue to be assigned to you after which you can start working on it.
  • Fork the Repo and create a Branch for any Issue that you are working upon.
  • Create a Pull Request which will be promptly reviewed and suggestions would be added to improve it.

Steps to take to contribute 👣

  • Create an issue for making any changes to code. When the issue is approved you can make changes.
  • Pull latest change from upstream branch before starting the changing of code.
  • Add your file in a properly named directory (lowercase) with a README.md in it.Add requirements.txt if needed.

Projects links 🔗

Report a Bug 🐛

  • Help us improve scripts. Report bugs here

forthebadge forthebadge forthebadge forthebadge

Owner
Sanskar Dwivedi
Sanskar Dwivedi
NEG loss implemented in pytorch

Pytorch Negative Sampling Loss Negative Sampling Loss implemented in PyTorch. Usage neg_loss = NEG_loss(num_classes, embedding_size) optimizer =

Daniil Gavrilov 123 Sep 13, 2022
Classical OCR DCNN reproduction based on PaddlePaddle framework.

Paddle-SVHN Classical OCR DCNN reproduction based on PaddlePaddle framework. This project reproduces Multi-digit Number Recognition from Street View I

1 Nov 12, 2021
DI-HPC is an acceleration operator component for general algorithm modules in reinforcement learning algorithms

DI-HPC: Decision Intelligence - High Performance Computation DI-HPC is an acceleration operator component for general algorithm modules in reinforceme

OpenDILab 185 Dec 29, 2022
Compare neural networks by their feature similarity

PyTorch Model Compare A tiny package to compare two neural networks in PyTorch. There are many ways to compare two neural networks, but one robust and

Anand Krishnamoorthy 181 Jan 04, 2023
Code for the paper: Sketch Your Own GAN

Sketch Your Own GAN Project | Paper | Youtube | Slides Our method takes in one or a few hand-drawn sketches and customizes an off-the-shelf GAN to mat

677 Dec 28, 2022
Self-Supervised Methods for Noise-Removal

SSMNR | Self-Supervised Methods for Noise Removal Image denoising is the task of removing noise from an image, which can be formulated as the task of

1 Jan 16, 2022
Neural Dynamic Policies for End-to-End Sensorimotor Learning

This is a PyTorch based implementation for our NeurIPS 2020 paper on Neural Dynamic Policies for end-to-end sensorimotor learning.

Shikhar Bahl 47 Dec 11, 2022
NLG evaluation via Statistical Measures of Similarity: BaryScore, DepthScore, InfoLM

NLG evaluation via Statistical Measures of Similarity: BaryScore, DepthScore, InfoLM Automatic Evaluation Metric described in the papers BaryScore (EM

Pierre Colombo 28 Dec 28, 2022
Build a small, 3 domain internet using Github pages and Wikipedia and construct a crawler to crawl, render, and index.

TechSEO Crawler Build a small, 3 domain internet using Github pages and Wikipedia and construct a crawler to crawl, render, and index. Play with the r

JR Oakes 57 Nov 24, 2022
Efficient electromagnetic solver based on rigorous coupled-wave analysis for 3D and 2D multi-layered structures with in-plane periodicity

Efficient electromagnetic solver based on rigorous coupled-wave analysis for 3D and 2D multi-layered structures with in-plane periodicity, such as gratings, photonic-crystal slabs, metasurfaces, surf

Alex Song 17 Dec 19, 2022
Custom studies about block sparse attention.

Block Sparse Attention 研究总结 本人近半年来对Block Sparse Attention(块稀疏注意力)的研究总结(持续更新中)。按时间顺序,主要分为如下三部分: PyTorch 自定义 CUDA 算子——以矩阵乘法为例 基于 Triton 的 Block Sparse A

Chen Kai 2 Jan 09, 2022
PyTorch code for EMNLP 2021 paper: Don't be Contradicted with Anything! CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System

Don’t be Contradicted with Anything!CI-ToD: Towards Benchmarking Consistency for Task-oriented Dialogue System This repository contains the PyTorch im

Libo Qin 25 Sep 06, 2022
Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model

Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model Baris Gecer 1, Binod Bhattarai 1

Baris Gecer 190 Dec 29, 2022
K-FACE Analysis Project on Pytorch

Installation Setup with Conda # create a new environment conda create --name insightKface python=3.7 # or over conda activate insightKface #install t

Jung Jun Uk 7 Nov 10, 2022
SOTR: Segmenting Objects with Transformers [ICCV 2021]

SOTR: Segmenting Objects with Transformers [ICCV 2021] By Ruohao Guo, Dantong Niu, Liao Qu, Zhenbo Li Introduction This is the official implementation

186 Dec 20, 2022
Parametric Contrastive Learning (ICCV2021)

Parametric-Contrastive-Learning This repository contains the implementation code for ICCV2021 paper: Parametric Contrastive Learning (https://arxiv.or

DV Lab 156 Dec 21, 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
Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Learning with Nonignorable Nonresponses‘

Graph-based joint model with Nonignorable Missingness (GNM) This is a Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Lear

Fan Zhou 2 Apr 17, 2022
Wider-Yolo Kütüphanesi ile Yüz Tespit Uygulamanı Yap

WIDER-YOLO : Yüz Tespit Uygulaması Yap Wider-Yolo Kütüphanesinin Kullanımı 1. Wider Face Veri Setini İndir Train Dataset Val Dataset Test Dataset Not:

Kadir Nar 6 Aug 22, 2022
ParmeSan: Sanitizer-guided Greybox Fuzzing

ParmeSan: Sanitizer-guided Greybox Fuzzing ParmeSan is a sanitizer-guided greybox fuzzer based on Angora. Published Work USENIX Security 2020: ParmeSa

VUSec 158 Dec 31, 2022