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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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Qiusheng Wu

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86,823 次观看 • 2 个月前 •via X (Twitter)

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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

Qiusheng Wu

13,738 次观看 • 1 年前

🚀 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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🚀 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

Qiusheng Wu

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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

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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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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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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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A sneak peek of a new feature in the #GeoAI Python package! 🎉 Now you can detect cars from georeferenced aerial imagery using deep learning—all with just a few lines of code. Stay tuned for an in-depth video tutorial coming soon! 🛠️ Explore the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist:
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A sneak peek of a new feature in the #GeoAI Python package! 🎉 Now you can detect cars from georeferenced aerial imagery using deep learning—all with just a few lines of code. Stay tuned for an in-depth video tutorial coming soon! 🛠️ Explore the GitHub repository: 📚 Dive into the documentation: 📺 Check out the entire YouTube playlist:

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45,624 次观看 • 1 年前

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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56,004 次观看 • 2 年前

📢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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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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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 #geoai
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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 #geoai

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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 #geoai
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So it works now! If you have Bakery, can you try getting the latest github patch and using it? Add "Bakery Light Filter" component to an object to make it act like stained glass 😋 (video from RTPreview for fanciness, but it looks the same when baked) #gamedev
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make your python endpoints reactive + auto generate ts types for models & api endpoints, releasing soon. FastAPI #python
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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
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40,463 次观看 • 3 年前

🍀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

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11,069 次观看 • 2 年前

(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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68,826 次观看 • 3 年前