segment-geospatial v0.3.0 is out - segmenting satellite imagery with... the Segment Anything Model (SAM). GitHub: Docs: Notebook: #segmentanything #deeplearning #geopython #geospatialshow more

Introducing segment-geospatial, A Python package for segmenting geospatial data... with the Segment Anything Model (SAM) GitHub: Docs: Notebook: #segmentanything #deeplearning #geopythonshow more

A sneak peak of segment-geospatial v0.4.0 - Automatically generating... object masks for satellite imagery GitHub: Notebook: #geospatial #deeplearning #segmentanythingshow more

Tree extraction from satellite imagery using segment-geospatial v0.5 and... the Segment Anything Model (SAM) - by Lucas Prado Osco LinkedIn post: Notebook: #geospatial #segmentanythingshow more

Removing clouds from satellite images with a few clicks... using That's fun. Try it out: Image source: #AI #deeplearning #geospatialshow more

🚀 Exciting news! The #GeoAI Python package now lets... you train land cover classification models with just one line of code. Leverage any PyTorch segmentation model from — with hundreds of image encoders & pretrained weights available. 📍 GitHub: 📓 Notebook: #GeoAI #Geospatial #DeepLearningshow more

🚀 A sneak peek of a new feature in... the #GeoAI Python package! Now you can train an image segmentation model for extracting features (e.g., buildings) from satellite or aerial imagery—all with just a few lines of code. 🛠️ Check out the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist: #GeoAI #geospatial #AI #Python #DeepLearningshow more

🚀 The #GeoAI Python package now supports feature segmentation... from high-resolution satellite and aerial imagery using text prompts, such as trees, buildings, etc. It efficiently processes large datasets with automatic tiling and can save results as a single image. Stay tuned for more features coming soon! 📓 Access the notebook: 🛠️ Explore the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist: #GeoAI #geospatial #AI #Python #DeepLearningshow more

Check out this 📹 step-by-step tutorial on how to... visualize and download 🛰️ satellite images of the #Morocco earthquake using the Maxar Open Data on #AWS. Video: Web App: GitHub: Notebook: #moroccoearthquake #geospatial #dataviz #pythonshow more

Digitalizando 20.000 ha de lotes agrícolas en #Turén, Venezuela... en menos de 20 minutos con segment-geospatial en python. La tecnología al servicio del agro. #remotesensing #geospatial #tercosdelcamposhow more

IBM’s watsonx․ai geospatial foundation model is now openly available... on Hugging Face. Built with NASA Earth, it’s the first-ever open-source #AI foundation model built with NASA & largest geospatial model on HuggingFace. Explore more:show more

Create Stunning Time-Series Satellite Images in Seconds! The GEE... Data Catalogs Plugin v0.5 for QGIS is now available and it's a powerful upgrade. You can now create time-series satellite imagery with just a few clicks using a simple interface. The new version also supports direct downloads to your computer, making the workflow faster and more efficient. Key Features: - Access over 80 petabytes of satellite and geospatial datasets from Google Earth Engine - Generate animated time-series imagery effortlessly - Export results directly from QGIS to your local machine Useful Links: QGIS Plugin Page: GitHub Repository: Video Tutorial: #QGIS #geospatial #EarthEngine #Python #datascience #satelliteshow more

The GeoAI Python package now supports object detection using... pre-trained models from the GeoDeep libarary ( The supported object types include cars, trees, birds, planes, aerovision, utilities, buildings, and roads. Try it out: GitHub: Notebook example: #geospatial #geoai #opensource #pythonshow more

A challenge for ML diagnosticians: The patient, Segment-Anything-Model-2 (SAM-2),... is presenting with two prominent symptoms: Symptom 1) Extremely high-magnitude tokens spread evenly across spatial dimensions.show more

Did you know we're working with environmental survey teams... to improve flood detection? Our Segment Anything Model (SAM) is being used to identify minute changes in water conditions from satellite images—we hope this faster analysis can contribute to better rapid response and keep communities safer.show more

Google just released the AlphaEarth Foundations with 64 dimensions... of satellite embeddings at 10-m resolution at the global scale! It is very interesting! Check it out Blog post: Dataset: Paper: #AI #geospatial #remotesensing #geoaishow more

Today we're releasing the Segment Anything Model (SAM) —... a step toward the first foundation model for image segmentation. SAM is capable of one-click segmentation of any object from any photo or video + zero-shot transfer to other segmentation tasks ➡️show more

🚀 I spent the entire day training image segmentation... models from scratch! I've created several pretrained models to detect features like buildings, cars, ships, solar panels, and wetlands. Video tutorials are coming soon! 🤗 Check out the pretrained models on Hugging Face: 🛠️ Check out the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist: #GeoAI #geospatial #AI #Python #DeepLearningshow more

Cloud and Cloud Shadow Detection From Satellite Imagery with... GeoAI and OmniCloudMask In this tutorial, you’ll detect clouds and cloud shadows, compute cloud statistics, clean segmentation outputs, convert raster masks to vectors, smooth boundaries, and generate a cloud-free mask for downstream remote sensing analysis. This workflow works with imagery that includes Red, Green, and NIR bands (e.g., Landsat, Sentinel-2, NAIP, and other commercial data). Notebook: Video tutorial: #geospatial #remotesensing #geoaishow more

🚨 Meta introduces Segment Anything Model 2 (SAM 2)... — the first unified model for real-time, promptable object segmentation in images & videos. 🚀SAM 2 is available today under Apache 2.0 so that anyone can use it to build their own experiences ➡️show more

🌍 Cloud-based geoprocessing with Actinia, GRASS GIS, and Leafmap!... A heartfelt 🫶 shoutout to @MarkusNeteler and the Actinia team for their invaluable contributions! Notebook: Actinia: GRASS #geospatial #opensource #gis #datavizshow more