sakthivel's repositories
video2image
Video2Images is a Python script that allows you to extract frames from a video file or multiple video files and save them as individual images. It provides a simple and convenient way to convert videos into a series of images, which can be useful for various applications such as computer vision, machine learning, data analysis, and more.
Unet_ToothSegmentation
使用Unet对CBCT牙齿数据进行二维分割
aruco-markers
Working examples/tutorial for detection and pose estimation of ArUco markers with C++, including instructions to build and install OpenCV from source.
Asynchronous_Tasks-Django-Celery-RabbitMQ-Redis
A Docker container for asynchronous processing of tasks in Django.
Awesome-Transformer-Attention
An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites
Coratia_Streaming_App
Coratia_Streaming_App
sakthivelj
Config files for my GitHub profile.
CoratiaOS
The open source platform for ROV, USV, and robotic system operation, development, and expansion.
FixCamMaskGenerator
FixCamMaskGenerator provides a set of tools and algorithms for creating accurate masks that separate objects from their backgrounds in images captured by fixed cameras.
herobiz-theme
A theme for YouTube
learnopencv
Learn OpenCV : C++ and Python Examples
Open-Full-Jaw
A dataset and python-based pipeline for "An open-access dataset and nearly-automated pipeline for generating finite element models of human jaw".
PyTorch-Computer-Vision-Cookbook
PyTorch Computer Vision Cookbook, Published by Packt
Pytorch-Medical-Segmentation
This repository is an unoffical PyTorch implementation of Medical segmentation in 2D and 3D.
seg_tooth
读入stl数据、分割单颗牙齿、把牙齿单独展示
ToothNet
This app is in development and is not done yet!
ToothSegmentation
基于Natrue Compression 论文 进行ROI 网络复现。论文名称A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images
TToth
a record for my work
Unsupervised-Pretraining-for-tooth-segmentation
Unsupervised Pre-training Improves Tooth Segmentation in 3-Dimensional Intraoral Mesh Scans (Accept at MIDL2022)