https://github.com/sumanthgubbala/dog-vs-cat-classification

Dog vs Cat Classification using Transfer Learning
https://github.com/sumanthgubbala/dog-vs-cat-classification

deep-neural-networks dog-vs-cat-classification flask tensorflow tensorflowhu transfer-learning

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Dog vs Cat Classification using Transfer Learning

• Host: GitHub
• URL: https://github.com/sumanthgubbala/dog-vs-cat-classification
• Owner: sumanthgubbala
• Created: 2024-12-27T16:38:29.000Z (10 days ago)
• Default Branch: master
• Last Pushed: 2024-12-27T16:57:13.000Z (10 days ago)
• Last Synced: 2024-12-27T17:33:58.177Z (10 days ago)
• Topics: deep-neural-networks, dog-vs-cat-classification, flask, tensorflow, tensorflowhu, transfer-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 0 Bytes
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Dog vs Cat Classification

This is a simple web application built with Flask, TensorFlow, and OpenCV to classify images as either a dog or a cat. The model used for classification is a Convolutional Neural Network (CNN) trained on a dog vs cat dataset.

## Vist here

 - https://dog-vs-cat-classification.onrender.com/

## Features

- Upload an image (PNG, JPG, or JPEG format) of a dog or a cat.

- The model classifies the image as either "Dog" or "Cat".

- Flask-based web interface for user interaction.

### Tech Stack

- Backend: Flask (Python web framework)

- Machine Learning: TensorFlow, Keras

- Image Processing: OpenCV

- Deployment: Heroku (or any other preferred platform)

## Prerequisites

Before running the application, make sure you have the following installed:

- Python 3.7+

- pip (Python package installer)

## Installation

Follow these steps to run the project on your local machine:

1. Clone the repository:

  - [git clone https://github.com/your-username/dog-vs-cat-classification.git](https://github.com/sumanthgubbala/Dog-vs-cat-classification.git)

2. Navigate to the project directory:

 - cd dog-vs-cat-classification

3. Create and activate a virtual environment (optional but recommended):

 - On Windows:

    - python -m venv venv

    - .\venv\Scripts\activate

- On macOS/Linux:

    - python -m venv venv

    - source venv/bin/activate

4. Install the required dependencies:

    - pip install -r requirements.txt

## Running the Application

To run the app locally, use the following command:

   - python app.py

   - Visit http://127.0.0.1:5000 in your browser to interact with the application.

## How to Use

1. Open the application in your web browser.

2. Upload an image of a dog or a cat.

3. The model will process the image and display whether the image is a "Dog" or "Cat".

## Model Training

The model used for classification is a pre-trained Keras model (dog_vs_cat_classification.h5). If you want to retrain the model, follow these steps:

1. Gather a dataset of dog and cat images.

2. Preprocess the images (resize to 224x224 and normalize).

3. Train a Convolutional Neural Network (CNN) on the dataset using Keras/TensorFlow.

4. Save the model as dog_vs_cat_classification.h5 and place it in the project directory.