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.

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

This repository contains implementations and illustrative code to accompany DeepMind publications

PyTorch code and models for the DINOv2 self-supervised learning method.

Best Practices, code samples, and documentation for Computer Vision.

Using Low-rank adaptation to quickly fine-tune diffusion models.

An annotated implementation of the Transformer paper.

"Probabilistic Machine Learning" - a book series by Kevin Murphy

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

『ゼロから作る Deep Learning』(O'Reilly Japan, 2016)

Probabilistic reasoning and statistical analysis in TensorFlow

An open-source project dedicated to tracking and segmenting any objects in videos, either automatically or interactively. The primary algorithms utilized include the Segment Anything Model (SAM) fo…

Clone of COCO API - Dataset @ http://cocodataset.org/ - with changes to support Windows build and python3

My implementation of the original transformer model (Vaswani et al.). I've additionally included the playground.py file for visualizing otherwise seemingly hard concepts. Currently included IWSLT p…

A continuously updated project to track the latest progress in the field of multi-modal object tracking. This project focuses solely on single-object tracking.

Simple implementation of OpenAI CLIP model in PyTorch.

까먹으면 다시 보려고 정리합니다.

Deep Reinforcement Learning with Python, Second Edition, published by Packt

Clockwork Convnets for Video Semantic Segmenation

NOT DONE, made by wooramkang models for Image / Viedo inpatinting