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GeoAI Made Easy: Learn the Python Package Step-by-Step (Beginner Friendly)
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GeoAI Tutorials - GeoAI Made Easy: Learn the Python Package Step-by-Step (Beginner Friendly)

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What you'll learn

This course includes

  • 20 hours of video
  • Certificate of completion
  • Access on mobile and TV

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🚀 Get started with GeoAI the easy way! In this beginner-friendly tutorial, you'll learn how to use the powerful GeoAI Python package to detect buildings and other objects from satellite imagery — step by step. Whether you're new to GeoAI or frustrated by other complex Python tools, this video breaks it down clearly and visually. 🔍 What you’ll learn: ✅ How to install the GeoAI Python package (locally or in Google Colab) ✅ How to train AI models on your own satellite data ✅ How to detect buildings, trees, pools, solar panels & more ✅ How to evaluate model performance and export results ✅ Bonus: Visualize, vectorize, and clean your outputs with ease! 🧠 No deep learning background needed — just follow along and you'll be detecting objects in no time! 📎 Download notebook & data: https://opengeoai.org/examples/train_segmentation_model 💬 Questions? Drop a comment — every question gets a reply! 0:00 - Introduction to GeoAI Python Package 0:37 - What You Can Detect with GeoAI 1:30 - Visualizing Output Results 2:01 - Installing the Package via Google Colab 3:20 - Switching to GPU Runtime in Colab 4:10 - Installing Dependencies 5:20 - Running GeoAI Locally with Conda 7:00 - Creating a Conda Environment 8:40 - Launching Jupyter Lab for GeoAI 10:12 - Importing the Package & Setup 11:06 - Downloading Sample Satellite Data 12:15 - Viewing Raster & Vector Data 13:30 - Creating Training Image Chips 15:00 - Deep Learning Setup Explained 16:40 - Model Architectures & Pretrained Weights 20:48 - Training with UNet & SegFormer Models 25:06 - Evaluating Model Performance 27:07 - Saving & Using Best Models 30:00 - Running Inference on New Imagery 33:01 - Visualizing Detection Results 35:00 - Output Probability Maps 36:40 - Setting Detection Thresholds 37:35 - Converting Raster to Vector (Polygonization) 38:44 - Calculating Geometry Properties 41:00 - Filtering Small Objects 42:11 - Comparing Results with Split Map 44:00 - Recap of the Workflow 44:45 - More Tutorials & Resources 45:32 - Final Thoughts & Q&A Invitation 📺 GeoAI Playlist: https://www.youtube.com/playlist?list=PLAxJ4-o7ZoPcvENqwaPa_QwbbkZ5sctZE 📘 Get my new Book - Introduction to GIS Programming: A Practical Python Guide to Open Source Geospatial Tools 👉 Amazon: https://amazon.com/dp/B0FFW34LL3 👉 Leanpub: https://leanpub.com/gispro 👋 Let’s Connect: YouTube: https://youtube.com/@giswqs LinkedIn: https://www.linkedin.com/in/giswqs Twitter: https://twitter.com/giswqs Facebook: https://www.facebook.com/groups/opengeos #GeoAI #PythonAI #SatelliteImagery #GeospatialAI #DeepLearning #OpenSourceGIS #RemoteSensing #AIForBeginners #ObjectDetection #GoogleColab

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