Project Overview

This project is an image classification web application that allows users to upload images and get predictions using a pre-trained neural network model.

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📂 Dataset Structure

The Dataset folder contains all the data required for training, validation, and testing:

1. originalTrain – Dataset used to train the model.
2. originalValidation – Dataset used to validate the model during training.
3. originalTest – Dataset used to test the model’s performance via the Web App.

⚠️ It is recommended not to modify the Dataset folder, as it may break file path configurations.

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📝 Project Files

Here’s a breakdown of the important files and their purposes:

1. Training File – Performs image processing on the training dataset.
2. Validation File – Performs image processing on the validation dataset.
3. Neural Network File – Trains the model using processed training data and validates using processed validation data.
4. Testing File – Processes images uploaded by users through the Web App and predicts results using the trained model.
5. main.py – Main entry point connecting the Web App to the model. This is the file you should run.
6. Model Folder – Contains the trained model, which is loaded during prediction.
7. Dataset Folder – Contains all datasets (do not modify).
8. template Folder – Contains HTML templates for the Web App.
9. static Folder – Contains static files (CSS, JS, images) needed for the Web App.

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🚀 How to Run

Since the model is already trained, there is no need to run the training or validation scripts.

1. Run the main file:

python main.py

2. Copy the link provided in the console and open it in your browser.
3. Upload images and view predictions instantly!

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👨‍💻 Project Contributors

• Muhammed Luqman
• Wafiya Sohail
• Farhan Shoukat