adithya-s-k / adithya-s-k/World-of-AI

[ML category based PROJECT PROPOSAL]

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#27 2 条评论 0 个 reaction 已指派 1 人 已被 @aman-kumar29 认领 在 GitHub 查看
assigned By Contributor Deep Learning GSSOC 23
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描述

## Project Request

Image Captioning with Deep Learning

This project aims to develop a model that automatically generates descriptive captions for images.

---

| Field | Description |
| ------ | --------------------------------- |
| About | Image Captioning with Deep Learning |
| Github | aman-kumar29 |
| Email | amankumar76814@gmail.com |
| Label | Project Request |

https://github.com/aman-kumar29
---

**Define You**

- [x] GSSOC Participant
- [x] Contributor

# Image Captioning with Deep Learning

## Description

The project involves training a deep-learning model on a dataset of images paired with corresponding captions. The model will learn to understand the visual content of images and generate meaningful and contextually relevant captions. The project will also include evaluating the model's captioning performance and the development of a user-friendly interface for image caption generation.

[Description of the project, its goals, and expected outcomes]

## Objectives
1. Real-Time Caption Generation: Develop a user interface where users can upload images, and the model generates captions in real time.
2. Content Generation: Image captioning models can be extended to generate creative and contextual captions for various applications, such as social media posts or advertising.

## Deliverables
1. Will give a trained image captioning model which should be able to take an input image and generate a relevant and contextually appropriate caption that accurately describes the visual content.
2. A user-friendly interface to interact with the model
3. comprehensive documentation will be provided, including technical documentation and user guides which will clearly describe how to use the interface and how to generate the caption.

## Timeline

Start Date: when assigned
End Date: 20 July

## Support Links

1. http://cocodataset.org/ could use this to get a dataset for the same.
2. could go through some research papers for this

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