An Image Captioning implementation of a CNN Encoder and an RNN Decoder in PyTorch.

Image captioning of Flickr 8k dataset using Attention and Merge model

In this capstone project, we need to create a deep learning model which can explain the contents of an image in the form of speech through caption generation with an attention mechanism on Flickr8K dataset.

Image Caption Generator using Python | Flickr Dataset | Deep Learning(CNN & RNN)

The concept of the project is to generate Arabic captions from the Arabic Flickr8K dataset, the tools that were used are the pre-trained CNN (MobileNet-V2) and the LSTM model, in addition to a set of steps using the NLP. The aim of the project is to create a solid ground and very initial steps in order to help children with learning difficulties.

This Notebook Shows a Neural Image Captioning model using Merge Architecture in keras which generates captions for given image.

Image Caption Generator, a project aims to generate descriptive captions for input images using advanced predictive techniques.

Text-Image-Text is a bidirectional system that enables seamless retrieval of images based on text descriptions, and vice versa. It leverages state-of-the-art language and vision models to bridge the gap between textual and visual representations.

Caption Generation using Flickr8k dataset by @jbrownlee and image generation from caption prompt using pretrained models

Automatic image captioning with PyTorch

Karpathy Splits json files for image captioning

Image Caption Generation

"AutoImageCaption-CNNvsResNet" leverages the Flickr 8k Dataset to automate image captioning, comparing CNN+LSTM and ResNet+GRU models using BLEU scores for performance evaluation.

Image Captioning using Deep learning models in Keras.

Implementation of Image Captioning Model using CNNs and LSTMs

Comparitive analysis of image captioning model using RNN, BiLSTM and Transformer model architectures on the Flickr8K dataset and InceptionV3 for image feature extraction.

🚀 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,...

Generating Captions for images using CNN & LSTM on Flickr8K dataset.The generation of captions from images has various practical benefits, ranging from aiding the visually impaired.

Automatically generating the captions for an image.

Image Captioning is the task of describing the content of an image in words. This task lies at the intersection of computer vision and natural language processing.