What you see is 3DGS. What you hit is LiDAR. At Greneta Corp., we turned a real industrial site into a Sim-Ready environment for Physical AI. The environment combines: • 3D Gaussian Splatting (3DGS) for photorealistic visual representation • LiDAR-based volumetric octree mapping for spatial geometry and depth sensing • Collision geometry for physical interaction A Unitree Robotics H1 can now walk through the reconstructed site in Nvidia Isaac Sim — seeing through RGB, sensing depth against the volumetric map, and physically interacting with the environment. Real → Reconstruction → Sim-Ready → Robot-Ready. Beyond digital twins — training grounds for Physical AI. P.S. For this demo, we intentionally configured a forward-facing camera and a rear-facing LiDAR. In NVIDIA Isaac Sim, sensor placement and specifications can be freely configured for different simulation scenarios. #Greneta #PhysicalAI #SimReady #RealToSim #3DGS #GaussianSplatting #IsaacSim #NVIDIA #Robotics #LiDAR #DigitalTwin | 13 comments on LinkedIn

Kotaku just posted:Get Off My Screen Dork, I’m Trying To PlayStar Wars: Zero CompanyOne Ovissian is too many in my book...https://kotaku.com/get-off-my-screen-dork-im-trying-to-playstar-wars-zero-company-2000730324#gamingNews #Kotaku

My name is Asmaa. I am 23 years old, and I am from Gaza.

Contribute to amine0110/vedo-tutorials development by creating an account on GitHub.

Contribute to amine0110/vedo-tutorials development by creating an account on GitHub.

How can an AI partner stay legible and negotiable when the primary interface is the body — not the text box?

Empower your frontline with hands-free, AI-powered error detection, procedural guidance, and QA support delivered through smart glasses.

What would it take to bring Mesa’s open source Vulkan driver for AMD GPUs to Windows? RADV’s experimental Windows port is getting closer to running real workloads, while highlighting one of the key challenges ahead: building a stable interface to AMD’s proprietary kernel driver. https://www.collabora.com/news-and-blog/news-and-events/cracking-windows-open-porting-radv-to-win32.html @vulkan@fosstodon.org #RADV #Mesa3D #OpenSourceGraphics #GPUDrivers #OpenSource

Stepping back from FreeCAD maintaining - Yorik's blog https://yorik.uncreated.net/?blog%2F2026%2F2026-002-stepping-out-of-freecad-maintaining

# Perimetric coordinate system : Eccentricity and Half-meridian Figure 1: Static 3D representation of the perimetric coordinate system. The PTVR **perimetric** coordinate system is a **spherical** coordinate system that is used extensively by vision scientists. In this coordinate system, the **3D position of a point P** is defined by 3 coordinates: – The **Half-meridian**(from 0° to 360°). – The **Eccentricity** (from 0° to 180°). – The **Radial Distance** (in meters) between Origin and P. The 3 coordinates of point P in Figure 1 are: Half-meridian: 135° Eccentricity: 20° Radial distance: any distance in meters. Figure 2: Horizontal rotation (i.e. about the Y axis) of the **perimetric** coordinate system shown in figure 1 A horizontal rotation (i.e. about the Y axis) of the **perimetric** coordinate system shown in figure 1 is shown in Figure 2. This rotation aims at providing a better mental image of 3D space. Figure 3: **Eccentricity** of point P varies from 0° to 40° while keeping Half-meridian constant at 135°. | Figure 4: **Half-meridian** of point P varies from 0° to 360° while keeping eccentricity constant at 20°. ---|--- # Flat Tangent Screen

# Perception Toolbox for Virtual Reality PTVR is a free and open-source library for creating visual perception experiments in virtual reality using high-level Python script programming. It aims at helping behavioral science researchers leverage virtual reality’s power for their research without the need to learn how virtual reality programming works. The philosophy of PTVR is thus very close to the approach of PsychoPy that has been so important and influential since 2007 for Vision Science researchers displaying stimuli on 2D monitors. --- #### Some of PTVR assets are: * Researchers can create VR experiments rapidly and succinctly thanks to clearly structured high-level python scripts. * **Serious Games** with sophisticated interactivity (pointing with handset, headset or gaze) can also be created in the same way. * The use of such scripts, along with the transparency of the PTVR open-source code, is one of the necessary components to address the ‘reproducibility crisis’ in science and foster **Open Science**. * Researchers can learn PTVR quite quickly thanks to two primary resources: * The rich online documentation with many **animated** figures in 3D to visualize 3D subtleties. * Demo scripts with didactic 3D and interactive features. * The **terminology** used in the PTVR code is familiar to vision scientists. For instance, researchers can use an intuitive “**Perimetric** ” coordinate system, allowing them to place their 3D stimuli with eccentricity and half-meridian coordinates easily. * Intuitive ways of dealing with **visual angles** in 3D. * Intuitive ways of dealing with the notorious difficulty of **rotating 3D objects**. * An implementation of “**flat screens** ” to replicate and extend standard experiments made on 2D screens of monitors. * Easy ways of **recording** experimental results. * Easy **Gaze** tracking and recording (only with HTC Vive pro Eye – in May 2025). * Easy **Head** tracking and recording. * Focus on implementing the standard and innovative **clinical tools** for visuomotor testing and visuomotor readaptation (notably for **low vision**). * Great care to create accurately controlled **text stimuli** in the spirit of the psychophysics of Reading. #### Requirements * An HTC Vive Pro Series VR system. The HTC Vive Pro EYE includes an eyetracker. * Or A QUEST 1, 2 or 3 system (starting from PTVR release 2.0.0 in May 2025) – no eyetracking. * A Windows computer with VR system already set-up. * Python >3.6. We recommend Spyder, a nice integrated development environment (IDE). #### Notes * Future PTVR versions will rely more and more on OpenXR to ensure as much as possible that PTVR will behave similarly on all conformant devices. * PTVR is built using the Unity game engine as a backend (you will however not have to install Unity yourself).

As the organizer of this campaign, I am reaching out on behalf of Mohamed, a remarkable 15-year-old boy from Gaza whose childhood has been overshadowed by hardship, loss, and responsibility far beyond his years.

80 Level just posted: Full-Body, Hand & Facial Motion Capture From Any Video In Blender BlendCap is completely local and offline. https://80.lv/articles/full-body-hand-facial-motion-capture-from-any-video-in-blender/ #gamingNews #80Level

# Perception Toolbox for Virtual Reality PTVR is a free and open-source library for creating visual perception experiments in virtual reality using high-level Python script programming. It aims at helping behavioral science researchers leverage virtual reality’s power for their research without the need to learn how virtual reality programming works. The philosophy of PTVR is thus very close to the approach of PsychoPy that has been so important and influential since 2007 for Vision Science researchers displaying stimuli on 2D monitors. --- #### Some of PTVR assets are: * Researchers can create VR experiments rapidly and succinctly thanks to clearly structured high-level python scripts. * **Serious Games** with sophisticated interactivity (pointing with handset, headset or gaze) can also be created in the same way. * The use of such scripts, along with the transparency of the PTVR open-source code, is one of the necessary components to address the ‘reproducibility crisis’ in science and foster **Open Science**. * Researchers can learn PTVR quite quickly thanks to two primary resources: * The rich online documentation with many **animated** figures in 3D to visualize 3D subtleties. * Demo scripts with didactic 3D and interactive features. * The **terminology** used in the PTVR code is familiar to vision scientists. For instance, researchers can use an intuitive “**Perimetric** ” coordinate system, allowing them to place their 3D stimuli with eccentricity and half-meridian coordinates easily. * Intuitive ways of dealing with **visual angles** in 3D. * Intuitive ways of dealing with the notorious difficulty of **rotating 3D objects**. * An implementation of “**flat screens** ” to replicate and extend standard experiments made on 2D screens of monitors. * Easy ways of **recording** experimental results. * Easy **Gaze** tracking and recording (only with HTC Vive pro Eye – in May 2025). * Easy **Head** tracking and recording. * Focus on implementing the standard and innovative **clinical tools** for visuomotor testing and visuomotor readaptation (notably for **low vision**). * Great care to create accurately controlled **text stimuli** in the spirit of the psychophysics of Reading. #### Requirements * An HTC Vive Pro Series VR system. The HTC Vive Pro EYE includes an eyetracker. * Or A QUEST 1, 2 or 3 system (starting from PTVR release 2.0.0 in May 2025) – no eyetracking. * A Windows computer with VR system already set-up. * Python >3.6. We recommend Spyder, a nice integrated development environment (IDE). #### Notes * Future PTVR versions will rely more and more on OpenXR to ensure as much as possible that PTVR will behave similarly on all conformant devices. * PTVR is built using the Unity game engine as a backend (you will however not have to install Unity yourself).

Start by installing the necessary libraries. You will need to have Python and pip (the package installer for Python) installed on your…

Best Libraries for Geospatial Data Visualisation in Python | Towards Data Science https://towardsdatascience.com/best-libraries-for-geospatial-data-visualisation-in-python-d23834173b35/

12 Python Libraries for Geospatial Data Analysis | Geoapify https://www.geoapify.com/python-geospatial-data-analysis/

15 Python Libraries for GIS and Mapping - GIS Geography https://gisgeography.com/python-libraries-gis-mapping/

scikit-learn: machine learning in Python — scikit-learn 1.9.0 documentation https://scikit-learn.org/stable/index.html

Best Libraries for Geospatial Data Visualisation in Python https://readmedium.com/best-libraries-for-geospatial-data-visualisation-in-python-d23834173b35

kepler.gl https://kepler.gl/

GitHub - keplergl/kepler.gl: Kepler.gl is a powerful open source geospatial analysis tool for large-scale data sets. · GitHub https://github.com/keplergl/kepler.gl

kepler.gl/docs/user-guides/c-types-of-layers/p-3d-tile-layer.md at master · keplergl/kepler.gl · GitHub https://github.com/keplergl/kepler.gl/blob/master/docs/user-guides/c-types-of-layers/p-3d-tile-layer.md

Kepler.gl https://harshithsai91.github.io/kepler/ "Kepler.gl is a WebGL-powered, open-source tool for displaying massive amounts of geographical data."

Learn how to Visualize Geospatial Data using kepler.gl https://www.analyticsvidhya.com/blog/2020/06/learn-visualize-geospatial-data-jupyter-kepler/

The ArcGIS Pro Python reference contains detailed information about every ArcPy module, function, and class provided with ArcGIS Pro; working with Python; and working with, and creating your own, geoprocessing tools in Python.

The ArcGIS Pro geoprocessing tool reference contains detailed information about every geoprocessing tool provided with ArcGIS Pro.

Capcom channel the energy of the PlayStation 3 era in this top notch third person title that isn’t a sequel or a remake - just a really good video game.

Home page for a World-Help site: How to create more Non-Zero-Sum Games for a brighter future.