Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
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Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking
TranslatedChinese word segmentation, part-of-speech tagging, named entity recognition, dependency parsing, constituency parsing, semantic dependency parsing, semantic role labeling, coreference resolution, style transfer, semantic similarity, new word discovery, keyword and keyphrase extraction, automatic summarization, text classification and clustering, pinyin and Simplified/Traditional Chinese conversion, natural language processing
Label Studio is a multi-type data labeling and annotation tool with standardized output format
📊 Cube Core is open-source semantic layer for AI, BI and embedded analytics
CVAT is a leading data annotation platform for image, video, audio, and 3D datasets. It offers open-source, cloud, and enterprise products, as well as labeling services, with AI-assisted labeling, quality assurance, team collaboration, analytics, and developer APIs.
Image annotation with Python. Supports polygon, rectangle, circle, line, point, and AI-assisted annotation.
A very simple framework for state-of-the-art Natural Language Processing (NLP)
Easy-to-use and powerful LLM and SLM library with awesome model zoo.
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
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pySLAM is a hybrid Python/C++ Visual SLAM pipeline supporting monocular, stereo, and RGB-D cameras. It provides a broad set of modern local and global feature extractors, multiple loop-closure strategies, a volumetric reconstruction module, integrated depth-prediction models, and semantic segmentation capabilities for enhanced scene understanding.
An open source library and framework for deep learning on satellite and aerial imagery.
Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app.
Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds
Web labeling tool for bitmap images and point clouds
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Fast, modular reference implementation and easy training of Semantic Segmentation algorithms in PyTorch.
Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs
TensorFlow Implementation for Computing a Semantically Segmented Bird's Eye View (BEV) Image Given the Images of Multiple Vehicle-Mounted Cameras.
The open source Meme Search Engine and Finder. Free and built to self-host locally with Python, Ruby, and Docker.
A simple deep learning library for estimating a set of tags and extracting semantic feature vectors from given illustrations.
LEDNet: A Lightweight Encoder-Decoder Network for Real-time Semantic Segmentation
Selected Machine Learning algorithms for natural language processing and semantic analysis in Golang