Implement-ml-model-in-android-app

Implement Dog vs Cat Prediction Model in Android app

This project aims to classify the input image as either a dog or a cat image. The image input which you give to the system will be analyzed and the predicted result will be given as output. Machine learning algorithm [Convolutional Neural Networks] is used to classify the image. The model thus implemented can be extended to a mobile device or any website as per the developer’s need.

Conceptual Framework:

The project is entirely implemented using Python3. The Conceptual Framework involved is mainly:

• OpenCV – Used to handle image operations

• Keras – Tensorflow backend

Step 1: Getting the Dataset

getting dataset form this repo

Step 2: Installing Required Packages [Python 3.6]

• OpenCV —> ‘3.4.0’ [ Used to handle image operations like reading the image, resizing, reshaping]
• numpy —> ‘1.14.4’ [ Image that is read will be stored in an numpy array ]
• TensorFlow —> ‘1.8.0’ [ Tensorflow is the backend for Keras ]
• Keras —> ‘2.1.6’ [ Keras is used to implement the CNN ]

Step 3: How the Model Works ??

The dataset contains a lot of images of cats and dogs. Our aim is to make the model learn the distinguishing features between the cat and dog. Once the model has learned, i.e once the model got trained, it will be able to classify the input image as either cat or a dog.

Requirements

• Android studio installed in your computer
• Jupyter notebook

Authors

• @Aditya664

Demo

Thanks