Image Classification with Flask and PyTorch

This is a Flask web application that allows users to upload images and get predictions from a pre-trained PyTorch model. Currently, this application only works with images that are of the shape (3, h, w).

Getting started

To get started, clone the repository to your local machine:

$ git clone https://github.com/PrplHrt/ImageClassificationWithFlaskAndPyTorch.git
$ cd ImageClassificationWithFlaskAndPyTorch

Prerequisites

Before you can run the Flask application, you need to install the required dependencies. You can do this using pip:

$ pip install -r requirements.txt

Running the application

To run the Flask application, you can use the following command:

$ export FLASK_APP=app.py
$ export FLASK_ENV=development
$ flask run

for Windows:

set FLASK_APP=app.py
set FLASK_ENV=development
flask run

This will start the Flask application on http://localhost:5000.

Using the application

To use the application, open your web browser and go to http://localhost:5000. This will take you to the home page, where you can upload an image file and get predictions from the pre-trained PyTorch model.

Project structure

The project has the following structure:

.
├── app.py
├── static
├── templates
│ ├── home.html
│ └── results.html
├── labels.json
├── README.md
└── requirements.txt

Here's a brief overview of each file and directory:

• app.py: This is the main Flask application file. It contains the route definitions and the view functions that handle incoming requests.
• static: This directory contains the static assets used by the web application, such as CSS and JavaScript files. (Empty for now)
• templates: This directory contains the HTML templates used by the Flask views.
• labels.json: This file contains the mapping from class indices to label names.
• README.md: This file contains the documentation for the project.
• requirements.txt: This file contains the list of Python dependencies required to run the project.

Acknowledgments

This project was inspired by the PyTorch Image Classification tutorial at https://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html. The pre-trained model weights were downloaded from the PyTorch model zoo at https://pytorch.org/docs/stable/torchvision/models.html.