PC Parts Image Classification

This project involves developing and deploying an AI model using EfficientNetV2B1 to classify and identify 14 different classes of PC parts from images.

Demo Video

Watch the demo video to see how to use the application.

Overview

We have built a model using EfficientNetV2B1 to accurately classify various PC parts from images. The model is integrated into a Flask application that provides an upload form for users to upload images and receive predictions.

Getting Started

Follow the steps below to clone the repository, install the required packages, and run the Flask server.

Clone the Repository

git clone https://github.com/kowshikdontu/TechPart-Vision.git

Install Requirements

pip install -r requirements.txt

Run the Flask Server

python -m flask --app app run --debug

Usage

• Access the Flask application at http://localhost:5000.
• Use the upload form available on the webpage to upload images of PC parts.
• The model will predict and display the class of the uploaded image.