image-captioning

LAVIS - A One-stop Library for Language-Vision Intelligence

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

InternGPT (iGPT) is an open source demo platform where you can easily showcase your AI models. Now it supports DragGAN, ChatGPT, ImageBind, multimodal chat like GPT-4, SAM, interactive image editing, etc. Try it at igpt.opengvlab.com (支持DragGAN、ChatGPT、ImageBind、SAM的在线Demo系统)

Official repository of OFA (ICML 2022). Paper: OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework

Caption-Anything is a versatile tool combining image segmentation, visual captioning, and ChatGPT, generating tailored captions with diverse controls for user preferences. https://huggingface.co/spaces/TencentARC/Caption-Anything https://huggingface.co/spaces/VIPLab/Caption-Anything

Simple Swift class to provide all the configurations you need to create custom camera view in your app

Tag manager and captioner for image datasets

👁️ + 💬 + 🎧 = 🤖 Curated list of top foundation and multimodal models! [Paper + Code + Examples + Tutorials]

Language Models Can See: Plugging Visual Controls in Text Generation

Official Code for 'RSTNet: Captioning with Adaptive Attention on Visual and Non-Visual Words' (CVPR 2021)

An offline AI-powered video analysis tool with object detection (YOLO), image captioning (BLIP), speech transcription (Whisper), audio event detection (PANNs), and AI-generated summaries (LLMs via Ollama). It ensures privacy and offline use with a user-friendly GUI.

mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections. (EMNLP 2022)

Improving Chest X-Ray Report Generation by Leveraging Warm-Starting

NAACL '24 (Best Demo Paper RunnerUp) / MlSys @ NeurIPS '23 - RedCoast: A Lightweight Tool to Automate Distributed Training and Inference

Pytorch implementation of image captioning using transformer-based model.

Combining ViT and GPT-2 for image captioning. Trained on MS-COCO. The model was implemented mostly from scratch.

This will contain the code for the 2nd edition of NLP with TensorFlow (Edition 2)

Transformer & CNN Image Captioning model in PyTorch.

An end-to-end image captioning project using a CNN encoder (ResNet-50) and LSTM decoder in PyTorch. Includes vocabulary building, preprocessing, training with BLEU evaluation, and inference. Generates natural language captions for images with saved metrics, model checkpoints, and visualization outputs.

Inverse DALL-E for Optical Character Recognition