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

PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

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)

Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning

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

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

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

The implementation of "Prismer: A Vision-Language Model with Multi-Task Experts".

Oscar and VinVL

X-modaler is a versatile and high-performance codebase for cross-modal analytics(e.g., image captioning, video captioning, vision-language pre-training, visual question answering, visual commonsense reasoning, and cross-modal retrieval).

Unofficial pytorch implementation for Self-critical Sequence Training for Image Captioning. and others.

TensorFlow Implementation of "Show, Attend and Tell"

Tag manager and captioner for image datasets

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

[CVPR 2021] VirTex: Learning Visual Representations from Textual Annotations

PyTorch source code for "Stacked Cross Attention for Image-Text Matching" (ECCV 2018)

Meshed-Memory Transformer for Image Captioning. CVPR 2020

Official Pytorch implementation of "OmniNet: A unified architecture for multi-modal multi-task learning" | Authors: Subhojeet Pramanik, Priyanka Agrawal, Aman Hussain

Custom ComfyUI nodes for Vision Language Models, Large Language Models, Image to Music, Text to Music, Consistent and Random Creative Prompt Generation