Classification-and-Captioning-Aircraft-Damage-Using-Pretrained-Models

Introduction

In this project, I will classify aircraft damage using a pre-trained VGG16 model and generate captions using a Transformer-based pretrained model.

Project Overview

Aircraft damage detection is essential for maintaining the safety and longevity of aircraft. Traditional manual inspection methods are time-consuming and prone to human error. This project aims to automate the classification of aircraft damage into two categories: "dent" and "crack." For this, we will utilize feature extraction with a pre-trained VGG16 model to classify the damage from aircraft images. Additionally, I will use a pre-trained Transformer model to generate captions and summaries for the images.

Aim of the Project

The goal of this project is to develop an automated model that accurately classifies aircraft damage from images. By the end of the project,I will have trained and evaluated a model that utilizes feature extraction from VGG16 for damage classification. This model will be applicable in real-world damage detection within the aviation industry. Furthermore, the project will showcase how we can use a Transformer-based model to caption and summarize images, providing a detailed description of the damage.

Final Output

• A trained model capable of classifying aircraft images into "dent" and "crack" categories, enabling automated aircraft damage detection.
• A Transformer-based model that generates captions and summaries of images