Snake Classification AI

Overview

Snake Classification AI is a machine learning project designed to classify snakes as either venomous or non-venomous using image analysis. The model is trained using TensorFlow and Keras, and is wrapped in a simple web application for user interaction. This project is intended for educational and recreational purposes.

Features

• Trained ML model for snake classification (venomous vs non-venomous)
• Built with TensorFlow and Keras libraries
• Interactive web frontend with image upload and prediction functionality
• User-friendly interface for submitting images and viewing classification results
• Error handling for invalid or unsupported image file types

Setup Instructions

Prerequisites

• Python 3.x
• TensorFlow
• Keras
• Flask
• Pillow (PIL)

Installation

1. Clone the repository:

   git clone https://github.com/adhikari-pratik/snake_classification_AI.git
   cd snake_classification_AI

2. Install required packages:

   pip install -r requirements.txt

   (If requirements.txt is missing, install packages manually: pip install flask tensorflow keras pillow)

3. Ensure the trained model file (mobilenetmodel.h5) is present in the project root.

Running the Application

python app.py

Open a browser and navigate to http://localhost:5000 to access the web interface.

Usage

• Upload an image of a snake.
• Click "Predict" to see whether the snake is classified as venomous or non-venomous.

Project Structure

• app.py – Flask web server and ML inference logic
• templates/ – HTML templates for web UI
• static/ – CSS and JavaScript for styling and interactivity
• mobilenetmodel.h5 – Pre-trained TensorFlow/Keras model

Example UI

• Upload image button
• Display of uploaded image
• Predict button for classification
• Result page showing the prediction

License

This project is developed for learning and recreation. Please credit the author if you reuse code.

Author

@adhikari-pratik