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

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Qiusheng Wu

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312,328 görüntüleme • 3 yıl önce •via X (Twitter)

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

Qiusheng Wu

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

Qiusheng Wu

39,570 görüntüleme • 3 yıl önce

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

Qiusheng Wu

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🚀 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 #DeepLearning
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🚀 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 #DeepLearning

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(1/) Hey #RemoteSensing folks! I'm happy to announce the first release of #cubo, a lovely #Python package for easily creating EO mini cubes from #STAC 🛰️🧊😁 gh: docs: #Geospatial #GeoPython #DataViz #EOchat #GISchat
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(1/) Hey #RemoteSensing folks! I'm happy to announce the first release of #cubo, a lovely #Python package for easily creating EO mini cubes from #STAC 🛰️🧊😁 gh: docs: #Geospatial #GeoPython #DataViz #EOchat #GISchat

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Display a video on an interactive map 🗺️ with #MapLibre and #Leafmap. Check it out: Map: GitHub: Notebook: #geospatial #opensource #dataviz #python
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Display a video on an interactive map 🗺️ with #MapLibre and #Leafmap. Check it out: Map: GitHub: Notebook: #geospatial #opensource #dataviz #python

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🚀 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 #DeepLearning
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🚀 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 #DeepLearning

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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 #python
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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 #python

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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 #tercosdelcampo
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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 #tercosdelcampo

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🚀 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 #DeepLearning
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🚀 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 #DeepLearning

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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 #python
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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 #python

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

Qiusheng Wu

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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.
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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.

Rudy Gilman

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📢Visualize hyperspectral data in 3D 🌍 with just a few lines of code using the HyperCoast #Python package . It supports popular datasets like AVIRIS, DESIS, EMIT, PACE, and NEON AOP. GitHub: Notebook: bingqing liu #geospaptial #hyperspectral #nasa #dataviz
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📢Visualize hyperspectral data in 3D 🌍 with just a few lines of code using the HyperCoast #Python package . It supports popular datasets like AVIRIS, DESIS, EMIT, PACE, and NEON AOP. GitHub: Notebook: bingqing liu #geospaptial #hyperspectral #nasa #dataviz

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🌍 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 #dataviz
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🌍 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 #dataviz

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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 ➡️
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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 ➡️

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🚀 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 #DeepLearning
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🚀 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 #DeepLearning

Qiusheng Wu

15,071 görüntüleme • 1 yıl önce

🍀Leafmap now supports interactive visualization of in-memory raster (xarray, numpy array) 🗺️This feature is very handy for exploring intermediate results interactively in your #geospatial workflow before saving them to your hard drive 💾 Video: Notebook: #leafmap #dataviz #python
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🍀Leafmap now supports interactive visualization of in-memory raster (xarray, numpy array) 🗺️This feature is very handy for exploring intermediate results interactively in your #geospatial workflow before saving them to your hard drive 💾 Video: Notebook: #leafmap #dataviz #python

Qiusheng Wu

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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 #satellite
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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 #satellite

Qiusheng Wu

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Rerun 0.20 is out! 🗺📍🎥 It adds early support for geospatial data with the new GeoPoints and GeoLineStrings archetypes and a map view. It also adds H.264 video support to the native viewer together with many performance and stability improvements for video in Rerun.
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Rerun 0.20 is out! 🗺📍🎥 It adds early support for geospatial data with the new GeoPoints and GeoLineStrings archetypes and a map view. It also adds H.264 video support to the native viewer together with many performance and stability improvements for video in Rerun.

Rerun

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