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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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Qiusheng Wu

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207,094 görüntüleme • 3 yıl önce •via X (Twitter)

#segmentanything#deeplearning#geopython#geospatial
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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

Qiusheng Wu

312,328 görüntüleme • 3 yıl önce

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

39,571 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

40,463 görüntüleme • 3 yıl önce

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

103,400 görüntüleme • 3 yıl önce

🚀 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

Qiusheng Wu

16,150 görüntüleme • 11 ay önce

🚀 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

11,284 görüntüleme • 1 yıl önce

🚀 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 görüntüleme • 1 yıl önce

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

Qiusheng Wu

56,004 görüntüleme • 2 yıl önce

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

Keiver Nuñez

28,717 görüntüleme • 2 yıl önce

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:
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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:

IBM News

759,160 görüntüleme • 2 yıl önce

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

14,019 görüntüleme • 4 ay önce

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

Qiusheng Wu

86,855 görüntüleme • 2 ay önce

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

25,936 görüntüleme • 1 yıl önce

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.
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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.

Meta

133,434 görüntüleme • 3 ay önce

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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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

Qiusheng Wu

47,006 görüntüleme • 10 ay önce

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 ➡️

AI at Meta

3,570,231 görüntüleme • 3 yıl önce

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

Qiusheng Wu

11,429 görüntüleme • 2 ay önce

🚀 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

🚨 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 ➡️
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🚨 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 ➡️

Zhengzhong Tu

181,288 görüntüleme • 1 yıl önce

🌍 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

Qiusheng Wu

11,173 görüntüleme • 2 yıl önce