Deployed image captioning ML model using Flask and access via Flutter app

Image captioning model with Resnet50 encoder and LSTM decoder

Streamline the creation of supervised datasets to facilitate data augmentation for deep learning architectures focused on image captioning. The core framework leverages MiniGPT-4, complemented by the pre-trained Vicuna model, which boasts 13 billion parameters.

This is a Deep Learning model which uses Computer Vision and NLP to generate captions for images.

This project Implements a combination of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to generate descriptive captions for input images.

🚀 Image Caption Generator Project 🚀 🧠 Building Customized LSTM Neural Network Encoder model with Dropout, Dense, RepeatVector, and Bidirectional LSTM layers. Sequence feature layers with Embedding, Dropout, and Bidirectional LSTM layers. Attention mechanism using Dot product, Softmax attention scores,...

BLIP-ImageCaption

deep learning model for generate caption and Analysis Sentiment

This Streamlit app is designed for image captioning and tagging using the Google Gemini AI

An Image captioning web application combines the power of React.js for front-end, Flask and Node.js for back-end, utilizing the MERN stack. Users can upload images and instantly receive automatic captions. Authenticated users have access to extra features like translating captions and text-to-speech functionality.

CLIPxGPT Captioner is Image Captioning Model based on OpenAI's CLIP and GPT-2.

Image captioning project.

This repository contains notebooks showcasing various generative models, including DCGAN and VAE for anime face generation, an Autoencoder for converting photos to sketches, a captioning model using an attention mechanism for an image caption generator, and more.

Python-based solution for automatic image caption generation using a ResNet-50 CNN and RNN, featuring comprehensive data preprocessing, model training, and evaluation with BLEU score and Cosine Similarity metrics.

Major Project Repository

Blip 2 Captioning, Mass Captioning, Question Answering, and other tools.

Deep learning-based image captioning with Flickr8k dataset. Code includes data prep, model training, and a Streamlit app.