Фреймворк компьютерного зрения для задач, детекции, сегментации, классификации, идентификации людей, анализа настроений и классификации действий
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Updated
Jun 12, 2024 - Python
Фреймворк компьютерного зрения для задач, детекции, сегментации, классификации, идентификации людей, анализа настроений и классификации действий
Simple-to-use scoring function for arbitrarily tokenized texts.
BIDS App for Hippunfold (automated hippocampal unfolding and subfield segmentation)
BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models
Cornerstone is a set of JavaScript libraries that can be used to build web-based medical imaging applications. It provides a framework to build radiology applications such as the OHIF Viewer.
PyTorch extensions for fast R&D prototyping and Kaggle farming
A deep-learning pipeline for segmentation of ambiguous microscopic images.
Implementation of differents algorithms for segmentation of laserscans, splitting them into subsets of beams, with a ROS2 interface.
ResPointNet++ for AutoCon journal paper.
collection of diffusion model papers categorized by their subareas
Segment Anything in 3D with NeRFs (NeurIPS 2023)
Base Computer Vision Paper Review and PyTorch Code
A curated list of awesome resources for camouflaged/concealed object detection (COD).
Desktop app for automatically translating comics - BDs, Manga, Manhwa, Fumetti and more in a variety of formats (Image, Pdf, Epub, cbr, cbz, etc) and in multiple languages.
Code for CVPR'24 Paper: Segment Any Event Streams via Weighted Adaptation of Pivotal Tokens
CVPR 2023-2024 Papers: Dive into advanced research presented at the leading computer vision conference. Keep up to date with the latest developments in computer vision and deep learning. Code included. ⭐ support visual intelligence development!
Python implementation of image segmentation algorithm of Shepherd et al (2019) Operational Large-Scale Segmentation of Imagery Based on Iterative Elimination. Remote Sensing 11(6).
A lightweight Franklin plugin for experimentation and segmentation.
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