Pet Classification

Introduction:

Binary Classification is the first step in understanding how Deep Learning works. We use a basic ConvNet followed by an FCN to classify if the Image is of a Cat or a Dog.

Steps:

1. Download the Dogs v/s Cats Dataset Dataset from Kaggle
2. Split 90% of the files for training and remaining 10% for Validation
3. Define a ConvNet with a mix of Convolution and MaxPool Layers followed by a FCN and start training
4. Test the model on your own dataset
5. Use OpenVino to convert the model to IR format and deploy it on the OpenNCC camera

Flowchart:

Output:

Check Out the Project here:

1. Google Colab
2. GitHub

References:

1. Dogs v/s Cats Dataset

Contributors:

Rushabh Dharia