a2o
By openpower-cores
librealsense
Intel® RealSense™ SDK (by IntelRealSense)
| a2o | librealsense | |
|---|---|---|
| 2 | 39 | |
| 123 | 7,300 | |
| - | 0.7% | |
| 0.9 | 9.9 | |
| about 2 years ago | 3 days ago | |
| Verilog | C++ | |
| GNU General Public License v3.0 or later | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
a2o
Posts with mentions or reviews of a2o.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-01-22.
librealsense
Posts with mentions or reviews of librealsense.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-18.
- 3D visualization of geospatial data using Unity
-
Help trying to install librealsense
from, https://github.com/IntelRealSense/librealsense/blob/master/doc/installation_jetson.md
- RealSense D435 Camera Integration with Unreal Engine
-
Pico 4 through the lenses (in mixed reality mode)
I think it is more along the lines of the Intel Realsense camera. It may even be from Intel.
-
LNK2019 error when using external library
Hello, Im trying to run this program: https://github.com/IntelRealSense/librealsense/tree/master/examples/save-to-disk
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coloring point cloud
My elegant, state of the art solution, is a modification of the code found here https://github.com/IntelRealSense/librealsense/blob/development/wrappers/python/examples/opencv_pointcloud_viewer.py Some time before line 295 I use open cv to open the video device and poll the frames, then on line 296 I swap color_image with my new frame.... It kindof works, now I need to align the image and depth
- What’s the most comparable device to the iPhones TrueDepth camera?
-
Help a newbie out
Not sure if you have sorted it now but did a quick search up on the internet. Their github page has some installation instructions and as others have said you forgot to add the public server key. (source: https://github.com/IntelRealSense/librealsense/blob/master/doc/distribution_linux.md)
-
Green Chili and how to find them?
ok folks, I got an answer from the guy from intel and he pointed to me a github discussion. That post mostly answer my question. D435 was able to pick up small thin object in 3d point cloud so i am going for D435 for my chili.
- META open sources VRS file format — optimized to record and playback streams of sensor data for virtual and augmented reality
What are some alternatives?
When comparing a2o and librealsense you can also consider the following projects:
microwatt - A tiny Open POWER ISA softcore written in VHDL 2008
opentrack - Head tracking software for MS Windows, Linux, and Apple OSX
ciao - Ciao is a modern Prolog implementation that builds up from a logic-based simple kernel designed to be portable, extensible, and modular.
aitrack - 6DoF Head tracking software
cedro - C programming language extension: Cedro pre-processor
Azure-Kinect-Sensor-SDK - A cross platform (Linux and Windows) user mode SDK to read data from your Azure Kinect device.
a2i
JetScan - JetScan : GPU accelerated portable RGB-D reconstruction system
oneDNN - oneAPI Deep Neural Network Library (oneDNN)
FOXTracker - Facial Head Pose Tracker for Gaming
janet - A dynamic language and bytecode vm