mapboxrobosat

Name: mapbox/robosat
Author: mapbox

Robosat

Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds

Features

Computer Vision - Semantic segmentation for satellite and aerial imagery.
Computer Vision and Image Processing - Semantic segmentation for satellite imagery.
Computer Vision Libraries - Semantic segmentation for aerial and satellite imagery.
Deep Learning Frameworks - Framework for semantic segmentation of aerial and satellite imagery.
Geospatial Machine Learning - Semantic segmentation for aerial and satellite imagery.
Specialized Segmentation - Satellite imagery segmentation framework.

Open-Source-Alternativen zu Robosat

Ähnliche Open-Source-Projekte, sortiert nach der Anzahl der gemeinsamen Funktionen mit Robosat.

pytorch/vision
pytorch/vision
17,743Auf GitHub ansehen
This project is a comprehensive computer vision library for the PyTorch ecosystem, providing a standardized collection of neural network architectures, datasets, and high-performance transformation utilities. It serves as a foundational framework for building, training, and deploying deep learning models, offering a centralized model registry that allows developers to instantiate architectures with pre-trained weights for tasks such as image classification, object detection, and semantic segmentation. The library distinguishes itself through its modular approach to data and compute management
Pythoncomputer-visionmachine-learning
Auf GitHub ansehen17,743
sentinel-hub/eo-learn
sentinel-hub/eo-learn
1,235Auf GitHub ansehen
Earth observation processing framework for machine learning in Python
Python
Auf GitHub ansehen1,235
dbolya/yolact
dbolya/yolact
5,231Auf GitHub ansehen
Yolact is a computer vision framework and real-time instance segmentation model. It utilizes a fully convolutional neural network to detect objects and generate pixel-level masks for images and video feeds. The system employs prototypical mask generation to create global mask prototypes that are linearly combined for instance-specific results. It incorporates deformable convolutional layers and deformable region-of-interest pooling to adapt spatial sampling to the irregular shapes of objects. The framework covers the full model development lifecycle, including training on custom datasets, ac
Python
Auf GitHub ansehen5,231
ultralytics/yolov5
ultralytics/yolov5
57,528Auf GitHub ansehen
YOLOv5 is a comprehensive computer vision framework designed for end-to-end deep learning, specializing in real-time object detection, image classification, and instance segmentation. It provides a unified toolkit that manages the entire lifecycle of a model, from initial dataset configuration and hyperparameter tuning to high-speed inference and deployment. The framework utilizes a modular neural architecture, allowing users to swap backbone and head components to tailor models for specific visual tasks. What distinguishes this project is its focus on production-ready deployment and model ef
Pythoncoremldeep-learningios
Auf GitHub ansehen57,528

Alle 30 Alternativen zu Robosat anzeigen

Häufig gestellte Fragen

Was macht mapbox/robosat?

Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds

Was sind die Hauptfunktionen von mapbox/robosat?

Die Hauptfunktionen von mapbox/robosat sind: Computer Vision, Computer Vision and Image Processing, Computer Vision Libraries, Deep Learning Frameworks, Geospatial Machine Learning, Specialized Segmentation.

Welche Open-Source-Alternativen gibt es zu mapbox/robosat?

Open-Source-Alternativen zu mapbox/robosat sind unter anderem: sentinel-hub/eo-learn — Earth observation processing framework for machine learning in Python. ultralytics/yolov5 — YOLOv5 is a comprehensive computer vision framework designed for end-to-end deep learning, specializing in real-time… dbolya/yolact — Yolact is a computer vision framework and real-time instance segmentation model. It utilizes a fully convolutional… pytorch/vision — This project is a comprehensive computer vision library for the PyTorch ecosystem, providing a standardized collection… aleju/imgaug — imgaug is a Python library for machine learning data augmentation and computer vision dataset expansion. It provides… alexeyab/darknet — Darknet is a high-performance C-based inference engine and computer vision library designed for real-time object…

Star-Verlauf

Open-Source-Alternativen zu Robosat

Ähnliche Open-Source-Projekte, sortiert nach der Anzahl der gemeinsamen Funktionen mit Robosat.

pytorch/vision
pytorch/vision
17,743Auf GitHub ansehen
This project is a comprehensive computer vision library for the PyTorch ecosystem, providing a standardized collection of neural network architectures, datasets, and high-performance transformation utilities. It serves as a foundational framework for building, training, and deploying deep learning models, offering a centralized model registry that allows developers to instantiate architectures with pre-trained weights for tasks such as image classification, object detection, and semantic segmentation. The library distinguishes itself through its modular approach to data and compute management
Pythoncomputer-visionmachine-learning
Auf GitHub ansehen17,743
sentinel-hub/eo-learn
sentinel-hub/eo-learn
1,235Auf GitHub ansehen
Earth observation processing framework for machine learning in Python
Python
Auf GitHub ansehen1,235
dbolya/yolact
dbolya/yolact
5,231Auf GitHub ansehen
Yolact is a computer vision framework and real-time instance segmentation model. It utilizes a fully convolutional neural network to detect objects and generate pixel-level masks for images and video feeds. The system employs prototypical mask generation to create global mask prototypes that are linearly combined for instance-specific results. It incorporates deformable convolutional layers and deformable region-of-interest pooling to adapt spatial sampling to the irregular shapes of objects. The framework covers the full model development lifecycle, including training on custom datasets, ac
Python
Auf GitHub ansehen5,231
ultralytics/yolov5
ultralytics/yolov5
57,528Auf GitHub ansehen
YOLOv5 is a comprehensive computer vision framework designed for end-to-end deep learning, specializing in real-time object detection, image classification, and instance segmentation. It provides a unified toolkit that manages the entire lifecycle of a model, from initial dataset configuration and hyperparameter tuning to high-speed inference and deployment. The framework utilizes a modular neural architecture, allowing users to swap backbone and head components to tailor models for specific visual tasks. What distinguishes this project is its focus on production-ready deployment and model ef
Pythoncoremldeep-learningios
Auf GitHub ansehen57,528

Alle 30 Alternativen zu Robosat anzeigen