Image Captioning Using CLIP & GPT Models

Image Captioning is the process of generating a textual description for given images. Image captioning can be regarded as an end-to-end Sequence to Sequence problem, as it converts images, which is regarded as a sequence of pixels to a sequence of words. Image captioning has a huge amount of application.

Our model generates descriptive captions for the given input image related to cricket domain.

This GitHub repository contains the implementation of a deep learning model capable of generating captions for images in the form of speech.

Medical image captioning and feature extraction. Deep learning pretreating task comparison.

LSTM model generates captions for images after extracting features using a CNN model.

AutoImageCaptioning🖼️ – A lightweight image captioning system using the **BLIP model**, designed for efficiency and minimal computation. Automatically generate meaningful captions for images with ease! 🚀

Transform your images into stories! This project harnesses the power of the BLIP model to generate rich short summaries for any image. Explore the fascinating intersection of computer vision and natural language processing, making your visual content more accessible and engaging. Perfect for developers, researchers, and AI enthusiasts!

DL-CNN-ImageCaptionGenerator

Simple Go API wrapper for https://www.captionbot.ai/

Joycaption optimized for windows

Este projeto utiliza recursos de IA generativa para gerar descrições de imagens e convertê-las em voz.

Автоматизированная система переименования и классификации изображений на основе их содержания с использованием глубоких нейронных сетей

Image Caption Generator using CNN and LSTM

An encoder-decoder model using Vision Transformers (ViT) for image encoding and Transformer decoder for caption generation.

A CNN based model trained on fliker8k data to generate captions from images.

An intelligent content generation pipeline that uses AI to analyze Instagram content, generate engaging captions, and post unique images generated using SD3.