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A latent text-to-image diffusion model
Examples and guides for using the OpenAI API
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Google Research
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
Audiocraft is a library for audio processing and generation with deep learning. It features the state-of-the-art EnCodec audio compressor / tokenizer, along with MusicGen, a simple and controllable…
A guidance language for controlling large language models.
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
This repository contains the source code for the paper First Order Motion Model for Image Animation
High-Resolution Image Synthesis with Latent Diffusion Models
强化学习中文教程（蘑菇书🍄），在线阅读地址：https://datawhalechina.github.io/easy-rl/
Code samples used on cloud.google.com
Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
Inpaint anything using Segment Anything and inpainting models.
Using Low-rank adaptation to quickly fine-tune diffusion models.
A unified framework for 3D content generation.
Accepted as [NeurIPS 2024] Spotlight Presentation Paper
Taming Transformers for High-Resolution Image Synthesis
COCO API - Dataset @ http://cocodataset.org/
PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft
Segment Anything in High Quality [NeurIPS 2023]
Text recognition (optical character recognition) with deep learning methods, ICCV 2019
Python-based tools for document analysis and OCR
This is the repo for our new project Highly Accurate Dichotomous Image Segmentation
EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything