Keras model to generate HTML code from hand-drawn website mockups. Implements an image captioning architecture to drawn source images.

Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome

Simple image captioning model

Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch

JoyCaption is an image captioning Visual Language Model (VLM) being built from the ground up as a free, open, and uncensored model for the community to use in training Diffusion models.

Hybrid RAG system combining vector search, knowledge graph (LightRAG), and cross-encoder reranking — with Docling document parsing, visual intelligence (image/table captioning), agentic streaming chat, and inline citations. Powered by Gemini or local Ollama models.

Joy Caption is a ComfyUI node using the LLaVA model to generate stylized image captions, supporting batch processing and GGUF models.

Automatic image captioning model based on Caffe, using features from bottom-up attention.

Datasets for remote sensing images (Paper:Exploring Models and Data for Remote Sensing Image Caption Generation)

An image viewer and AI-assisted editing/captioning/masking tool that helps with curating datasets for generative AI models, finetunes and LoRA.

A custom ComfyUI node for MiniCPM vision-language models, supporting v4, v4.5, and v4 GGUF formats, enabling high-quality image captioning and visual analysis.

[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow

Deep Learning workshop including image classification, face recognition, Object detection, language modelling, image captioning and neural machine translation.

Four-in-one deep network: image search, image captioning, similar words and similar images using a single model

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

Official DINO-X Model Context Protocol (MCP) server that empowers LLMs with real-world visual perception through image object detection, localization, and captioning APIs.

Image Captioning based on Bottom-Up and Top-Down Attention model

Image captioning ready-to-go inference: show and tell model compatible with Tensorflow r1.9

[CVPR 2025] BIOMEDICA: An Open Biomedical Image-Caption Archive, Dataset, and Vision-Language Models Derived from Scientific Literature

ZerolanCore integrates many open-source, locally deployable AI models, and aims to integrate a series of AI models such as large language model (LLM), automatic speech recognition (ASR), text-to-speech (TTS), image captioning, optical character recognition (OCR), video captioning, etc.

The LSTM model generates captions for the input images after extracting features from pre-trained VGG-16 model. (Computer Vision, NLP, Deep Learning, Python)

IBM Code Model Asset Exchange: Show and Tell Image Caption Generator

generate captions for images using a CNN-RNN model that is trained on the Microsoft Common Objects in COntext (MS COCO) dataset

[IEEE GRSL 2024 🔥] RSCaMa: Remote Sensing Image Change Captioning with State Space Model

VideoCC is a dataset containing (video-URL, caption) pairs for training video-text machine learning models. It is created using an automatic pipeline starting from the Conceptual Captions Image-Captioning Dataset.

A length-controllable and non-autoregressive image captioning model.

Implementation of 'End-to-End Transformer Based Model for Image Captioning' [AAAI 2022]

Pytorch implementation of image captioning using transformer-based model.

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

FuseCap: Leveraging Large Language Models for Enriched Fused Image Captions