2.cd to the directory where requirements.txt is located.
3.activate your virtualenv.
4.run: pip install -r requirements.txt in your shell.
5. cd into templates folder
6. run app.py in terminal
Project Motivation and Overview
Our project is designed to help identify animals using Convolutional Neural Network(CNN) classification and to serve as an alert system for people in their practices.
For eg, Farmers wanting to look after their crops, People living in bungalows looking to maintain their backyards,etc.
Dataset
Our custom dataset consists of 91 classes with 5850 images.
No. of classes for animals:90
No. of classes of humans:1
Model Description
Adding Hidden layers
We have added 5 hidden layers using "Relu" activation function and 1 Dense layer.
The output layer has "softmax" activation function.
