3D Tutorials to Learn 3D Data Processing.
I create 3D tutorials to help you develop 3D Data Processing Skills. These guides are all open-access and take on various shapes (articles, code, notebooks, videos, datasets). Feel free to email me directly through my 3D newsletter if you have any recommendations, questions, or want to join the sharing force. π«Ά
3D Learning Resources: Top 5 Picks π
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3D Geospatial Data Integration with Python: The Ultimate Guide (incl. π» code, π data and πΌοΈ visuals)
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The Blender Handbook for 3D Point Cloud Visualization and Rendering (incl. π» code, π data and πΌοΈ visuals)
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3D Deep Learning Essentials: Ressources, Roadmaps and Systems (incl. π» code, π data and πΌοΈ visuals)
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Segment Anything 3D for Point Clouds: Complete Guide (SAM 3D) (incl. π» code, π data and πΌοΈ visuals)
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3D Point Cloud Shape Detection for Indoor Modelling (incl. π» code, π data and πΌοΈ visuals)
3D Tutorials: Latest Releases (Weekly) π
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3D Reconstruction from a Single Image: Tutorial
This tutorial targets Monocular Depth Estimation for 3D Reconstruction (Point Cloud, 3D Mesh). In the end, you will be able […]
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3D Deep Learning Essentials: Ressources, Roadmaps and Systems
Dive into the fascinating world of 3D with deep learning, where objects come alive and possibilities are beyond 2DΒ pixels. Few […]
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Point Cloud Feature Extraction: Complete Guide
This tutorial targets 3D Point Cloud Feature Extraction for developing an interactive Python Segmentation App. The goal is to develop […]
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3D Modelling: Point Cloud to 3D Mesh
3D Modelling: Point Cloud to 3D Mesh In this 3D Tutorial, we learn how to create stunning 3D meshes from […]
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Vectorization of 3D Point Cloud for LiDAR City Models
3D Point Cloud Vectorization for LiDAR City Models This hands-on approach is standalone and covers the process of LiDAR Vectorization. […]
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3D Roadmap Recommendations for 2024
3D Roadmap Recommendations for 2024 In this episode, I am showing you my 3D Roadmap Recommendation for 2024. We are […]
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3D Shape Detection for Indoor Modelling
A 10-step Python Guide to Automate 3D Shape Detection, Segmentation, Clustering, and Voxelization for Space Occupancy 3D Modeling of Indoor […]
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3D Data Processing: Video Tutorials
Below, you will find the latest video tutorials that are shared openly. Feel free to explore the YouTube channel as well!
3D Point Cloud Unsupervised Clustering with Python
I share a hands-on Python approach to Automate 3D Shape Detection, Segmentation, Clustering, and Voxelization for Point Cloud Datasets. In this case, we study an example of an indoor dataset. By the end, you’ll have a solid understanding of how to work with 3D point cloud datasets and perform advanced 3D shape recognition tasks using Python. π
Materials and 3D Tutorial Resources
π3D Dataset: Google Drive Folder
πHands-on Guide: Medium Article
My 3D Recommendation π
Having the ability to detect shapes and segment 3D point clouds is adds a lot of value to any workflow. Specifically, this permits to label 3D datasets with more efficiency, have unsupervised segmentation approaches, and extract information in an autonomous fashion. If you want to push this concept to its limit, I recommend the 3D Segmentation Deck that dives deep in 3D Object Recognition and Segmentation: 3D Segmentation Deck.
3D Point Cloud Processing Starter Pack
I share a hands-on Python approach to Automate 3D Shape Detection, Segmentation, Clustering, and Voxelization for Point Cloud Datasets. In this case, we study an example of an indoor dataset. By the end, you’ll have a solid understanding of how to work with 3D point cloud datasets and perform advanced 3D shape recognition tasks using Python. π
Materials and 3D Tutorial Resources
π3D Dataset: Access Open Data Portals (E.g. OpenTopography)
My 3D Recommendation π
Whenever you are starting a 3D Data Project that involves Point Clouds, it is nice to know you have an optimized setup. Once this is the case, the next logical step is to develop end-to-end point cloud workflows, as shown in the course: 3D Point Cloud Processor.
3D Point Clouds to Blender
In this 3D tutorial, you’ll learn how to integrate and process 3D Point Clouds in Blender. We address the complete workflow from point data I/O to scene setup and rendering in Blender. I illustrate the case of an Indoor Extraction Scenario where you would need to create a stunning rendering to show off the best route to take to gather a dangerous artifact. β£οΈ
Materials and 3D Tutorial Resources
π3D Dataset: Google Drive Folder
πHands-on Guide: Medium Article (Coming soon)
My 3D Recommendation π
The ability to adapt visuals and renderings of 3D Point Clouds is really empowering. Indeed, it means that you could cut down on heavy 3D Modelling workflow or quickly go from on-site data acquisition to visual presentation to stakeholders. This perfectly fits within the boundaries of 3D Point Cloud Workflows. They are covered in depth in the course: 3D Point Cloud Processor. I encourage you to unlock that if you want to extend your reach and value to your team/vision.