Image Classifier Web Application using Flask This GitHub repository hosts the code for an image classifier web application developed using Flask, a lightweight Python web framework, and PyTorch, a powerful deep learning library. The application leverages a pre-trained ResNet18 model for efficient and accurate image classification tasks.

Key Features:

User-friendly Interface: Experience seamless image uploads and receive real-time predictions via the intuitive web interface. State-of-the-Art Model: Benefit from the advanced capabilities of a ResNet18 model, meticulously trained on extensive datasets, ensuring top-tier image classification accuracy. Efficient Deployment: Easily deploy the application on local machines or cloud platforms for swift testing and deployment, ensuring hassle-free integration into your workflow. How to Use:

Clone the Repository: Begin by cloning the repository to your local machine. Install Dependencies: Utilize pip install -r requirements.txt to effortlessly install the necessary dependencies. Run the Flask Application: Execute python app.py to launch the Flask application. Access the Web Interface: Navigate to your preferred web browser and access the web interface to upload an image for classification. Dependencies:

Flask PyTorch torchvision NumPy Pillow Contributing:

Contributions are highly encouraged and welcomed! Whether it's bug reports, feature requests, or pull requests, your input is invaluable in enhancing this project.

Dataset Link:

Access the dataset here.https://drive.google.com/drive/folders/1mQux3ny6jRC5mm4MTh-Q5ntRaUg6t67f?usp=drive_link

License:

This project is licensed under the MIT License. Refer to the LICENSE file for more details.