Skip to content

Classification of dogs' breed using Convolutional Neural Networks

Notifications You must be signed in to change notification settings

Gilaine/Dog-classifier

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Dog-classifier

Classification of dogs' breed using Convolutional Neural Networks

Project Overview

Having dataset of human faces and dataset for dog images, the Network is trained to detect the human and dogs in images and gives percentage of the accuracy of the trained model in terms of how many images in the human dataset are detected to be human face and how many images in dog dataset are detected to have dogs. CNN architecture of trained model attains at least 10% accuracy on the test set

Using CNN and the trained model, another job is done which is classifying the dog's breed in each image and if a human is detected, the resembling breed shall be classified and this method is called transfer learning. CNN to Classify Dog Breeds Using Transfer Learning has accuracy more than 70%.

Dependencies

there are some libraries needed for this project including: Python 3.7, Numpy, Pandas, Matplotlib, Torchvision, PyTorch

Data sets

Download the dog dataset Download the human_dataset

Transfer Learnings

using VGG16 model

About

Classification of dogs' breed using Convolutional Neural Networks

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published