RidgeRun

From RidgeRun Developer Wiki

Company overview

RidgeRun, LLC is a private embedded software company founded in 2006.[1] It maintains a business office in Bradenton, Florida, and a research and development center in San José, Costa Rica.[2][3] The company specializes in video processing, computer vision, Linux customization and streaming software for embedded and edge devices. Its offerings include board bring-up, camera driver development, custom vision algorithms, multimedia framework optimization, system integration, pipeline optimization and artificial intelligence for Linux-based platforms.[4][5][6][7][8]

RidgeRun has worked across multiple system-on-chip (SoC) families through partnerships with vendors including NVIDIA,[9] Texas Instruments (TI),[4] NXP,[7] AMD/Xilinx,[10] Qualcomm,[11] and Hailo.[12] The company’s work began with TI DaVinci and OMAP processors in 2006, delivering SDKs and board support packages (BSPs) for multimedia-ready SoCs.[13] In 2013 it expanded to NXP’s i.MX platforms (i.MX6, i.MX8, and recently i.MX95),[14] and over time shifted from SDK distribution to custom applications for video processing and analysis, with a focus on camera sensor integration, perception, GStreamer, and computer-vision pipelines.[15] [16] [17] [18] [19]

Since 2016, RidgeRun has been an official partner in the NVIDIA Jetson ecosystem, supporting platforms from TK1, TX1, TX2 to AGX Orin and Thor.[9][20] [21] Today, it builds end-to-end, edge-AI solutions optimized for heterogeneous architectures.[22]

The company is recognized for work across the full video pipeline—from capture (cameras, LiDAR, radar, and metadata) through processing/analysis to efficient streaming—often using ISP, GPU, DSP, PVA and FPGA accelerators.[23] [24] [25] RidgeRun contributes to the GStreamer multimedia framework[26] [27] [28] [29] [30] [31], releases open-source tools and drivers, and maintains commercial components for real-time streaming, video stitching, and metadata handling.[32][33] [34] It has participated in initiatives such as the Yocto Project,[35] the GStreamer Conference,[36][37][8] and NVIDIA’s GTC.[38][39] [40]

History and evolution

Early years (2006–2013)

RidgeRun was established in 2006 with an initial focus on embedded Linux SDKs and BSPs for custom hardware, primarily supporting TI DaVinci and OMAP SoCs (e.g., DM36x, DM3730, DM816x).[1][41][42][43] Its SDKs provided multimedia enablement for evaluation boards through custom Linux distribution and device drivers (including V4L2 camera support) and integration with multimedia frameworks.[44][45]

Expansion into SoC vendors for multimedia processing (2013–2014)

By 2013, RidgeRun added Freescale/NXP i.MX Family support (beginning with i.MX6) and adopted Yocto-based build systems for partners.[46][47] The early experiences building SDKs and drivers laid the groundwork for the company’s understanding of Yocto, camera sensors, codecs, and real-time streaming on resource-constrained devices. RidgeRun broadened into digital video and audio processing as a core specialty, leveraging DSP co-processors, VPUs, and early GPUs (via OpenGL and OpenCL) to increase throughput and reduce latency on embedded systems.[48] During this period the company deepened its use of GStreamer, emphasizing zero-copy memory paths and hardware-codec integration (e.g., H.264, AAC, JPEG) to push higher resolutions and frame rates on modest SoCs.[49]

Pivot to computer vision and edge AI (2015–2020)

By 2015, RidgeRun established a partnership with Xilinx and started supporting the Zynq UltraScale+ MPSoC to help customers developing programmable logic (FPGA) subsystems with ARM-based blocks executing Linux for video and audio processing.[50][51] By the end of 2015, with the emergence of on-chip GPUs and the NVIDIA Jetson platform, RidgeRun moved further toward computer vision and edge AI.[52] From the Jetson TX1 and TX2 era onward, the team deployed CUDA-accelerated GStreamer pipelines and optimized OpenCV algorithms for on-device inference (e.g., object detection and video analytics) with low latency and high frame rates, reducing dependence on cloud processing.[53] [54] [55] [56] [57] [58] [59] [60] [61] By 2016 a new division dedicated to support the development of medical devices was created.[62]

RidgeRun and RidgeRun.ai (2020–2025)

In 2021 the company launched RidgeRun.ai, a division focused on model development, optimization (e.g., pruning/quantization), and deployment for embedded targets and cloud back ends.[63] By 2025, RidgeRun reported access to NVIDIA’s PVA accelerator and tools for custom computer vision algorithms on Jetson platforms.[23] [64][65] As of 2025, the engineering organization comprises approximately 95–100 specialists in embedded Linux, GStreamer, and AI, with most development based in Costa Rica and customer engagement handled through the U.S. office.[66]

Technologies and platforms

RidgeRun’s work spans the usage and customization of Linux and frameworks like OpenGL, OpenCV, CUDA, GStreamer, TensorRT and others in NVIDIA Jetson (TK1, TX1, TX2, Xavier, Orin NX/AGX, Thor), NXP i.MX6/i.MX8/i.MX95, AMD/Xilinx UltraScale+, Qualcomm RB5, QCS8550, Rubik Pi, and Hailo AI accelerators. Areas of emphasis include camera bring-up and drivers, Yocto customization, GStreamer pipeline design, and deployment of vision/AI workloads across ISP, GPU, DSP, and FPGA back ends.[67][68]

Products

RidgeRun develops commercial software components frequently used in edge video and analytics:

  • GstRtspSink — multi-client RTSP/RTP streaming for embedded devices.[69]
  • Bird’s-Eye View (BEV) — top-down multi-camera rendering for surround-view/robotics.[70]
  • GstStitcher — GPU-accelerated panoramic/360° stitching (real-time).[71]
  • Metadata tools — e.g., Gst In-Band Metadata and GstSEIMetadata for in-band metadata handling.[72][73]

These are among the company’s portfolio.[74][75]

Services

RidgeRun provides engineering services that include hardware bring-up, camera and ISP driver development (V4L2/SerDes), Linux customization/Yocto meta-layers, LiDAR and Radar integration, GStreamer pipeline tuning, and training/deployment of AI models on embedded targets. The company engages through subscription models and also offers product licenses to accelerate time to market.[76]

Open-source tools and contributions

  • GStreamer plugins and tooling: GstShark[77][78] (profiling/tracing), GstPerf[79] (inline performance metrics), GstInterpipes[80] (inter-pipeline communication), GstCUDA[81] (CUDA-accelerated elements), GstRtspSink[82], and GstWebRTC components[83]
  • Camera drivers: Free V4L2 drivers/guides for Raspberry Pi IMX219 and IMX477 sensors on Jetson.[84][85]
  • Yocto: Public meta-ridgerun layer and build guides.[86][35]
  • Education and forums: Tutorials and getting-started guides (Yocto, GStreamer, Jetson), and active participation on NVIDIA DevTalk, NXP, Qualcomm, and Hailo forums.[87][88]
  • RidgeRun.ai: Example models and DVC tutorials for ML workflow management.[89]

Founders

RidgeRun was co-founded in 2006 by Todd Fischer (formerly a Hewlett-Packard system architect) and Clark Becker (a former Best Buy senior executive). Fischer as vice-president of engineering and Becker as chief executive. Their combined backgrounds—embedded systems and enterprise technology/operations—shaped RidgeRun’s early focus on multimedia software for embedded devices.[90]

References

  1. ↑ 1.0 1.1 LinuxDevices, “Embedded Linux specialist RidgeRun runs again,” July 13, 2006. https://linuxdevices.org/embedded-linux-specialist-ridgerun-runs-again/ (accessed Aug 28, 2025).
  2. ↑ RidgeRun, “Contact RidgeRun.” https://www.ridgerun.com/contact (accessed Aug 28, 2025).
  3. ↑ Hoy En el TEC, “Dispositivos de última tecnología refuerzan el trabajo en el SIP-Lab,” May 24, 2018. https://www.tec.ac.cr/hoyeneltec/2018/05/24/dispositivos-ultima-tecnologia-refuerzan-trabajo-sip-lab (accessed Aug 28, 2025).
  4. ↑ 4.0 4.1 Texas Instruments, “RDGRN-3P-SW-SERVICES.” https://www.ti.com/tool/RDGRN-3P-SW-SERVICES (accessed Aug 28, 2025).
  5. ↑ NVIDIA Developer Blog, “Building a Multi-Camera Media Server for AI Processing on the NVIDIA Jetson Platform,” May 8, 2020. https://developer.nvidia.com/blog/building-multi-camera-media-server-ai-processing-jetson/ (accessed Aug 28, 2025).
  6. ↑ FRAMOS, “FRAMOS & RidgeRun: Embedded Vision & AI Software Solutions.” https://framos.com/partner/ridgerun/ (accessed Aug 28, 2025).
  7. ↑ 7.0 7.1 NXP, “RidgeRun, LLC (Partner Profile).” https://www.nxp.com/webapp/connect/displayPartnerProfile.sp?partnerId=4462 (accessed Aug 28, 2025).
  8. ↑ 8.0 8.1 GStreamer Conference, “Edge AI GStreamer Plugins,” Sept 25, 2023. https://indico.freedesktop.org/event/5/contributions/224/ (accessed Aug 28, 2025).
  9. ↑ 9.0 9.1 NVIDIA Developer, “Jetson Ecosystem.” https://developer.nvidia.com/embedded/ecosystem (accessed Aug 28, 2025).
  10. ↑ RidgeRun, “RidgeRun Xilinx Zynq UltraScale+ MPSoC Support & Integrations.” https://www.ridgerun.com/xilinx (accessed Aug 28, 2025).
  11. ↑ Qualcomm Documentation, “GStreamer Daemon.” https://docs.qualcomm.com/bundle/publicresource/topics/80-70020-50/gstreamer-daemon.html (accessed Aug 28, 2025).
  12. ↑ RidgeRun, “Hailo AI Accelerator Support.” https://www.ridgerun.com/hailo (accessed Aug 28, 2025).
  13. ↑ Texas Instruments, “OS Support by Platform (TI DaVinci and Sitara Processors).” https://www.ti.com/en/graphics/dsp/shared/ti_os_table_3-11-12.pdf (accessed Aug 28, 2025).
  14. ↑ NXP Community, “RidgeRun SDK: i.MX6 – X11, Qt and Enlightenment,” July 8, 2014. https://community.nxp.com/t5/i-MX-Processors-Knowledge-Base/RidgeRun-SDK-i-MX6-X11-QT-and-Enlightenment/ta-p/1123096 (accessed Aug 28, 2025).
  15. ↑ NVIDIA, “GTC 2020: How to Build a Multi-Camera Media Server for AI Processing on Jetson,” 2020. https://developer.nvidia.com/gtc/2020/video/s22396-vid (accessed Aug 28, 2025).
  16. ↑ NVIDIA, “GTC Silicon Valley 2019: GstCUDA – Easy GStreamer and CUDA Integration,” 2019. https://developer.nvidia.com/gtc/2019/video/s9391 (accessed Aug 28, 2025).
  17. ↑ YouTube, “RidgeRun Virtual Booth NVIDIA GTC 2024,” Apr 28, 2025. https://www.youtube.com/watch?v=_RFSz0GxqsI (accessed Aug 28, 2025).
  18. ↑ YouTube, “RidgeRun – MMA Fighter Detection Network,” May 25, 2022. https://www.youtube.com/watch?v=NhWL9g6ZQSc (accessed Aug 28, 2025).
  19. ↑ YouTube, “Six OV5647 Camera Capture with Tegra X1 / X2,” Jan 5, 2017. https://www.youtube.com/watch?v=PzT85x-ZkgQ (accessed Aug 28, 2025).
  20. ↑ NVIDIA Developer Forums, “RidgeRun Support for Six Raspberry Pi Cameras Using ISP,” Nov 10, 2016. https://forums.developer.nvidia.com/t/ridgerun-support-for-six-raspberry-pi-v2-imx219-and-v1-ov5647-cameras-using-isp-multi-camera/46074 (accessed Aug 28, 2025).
  21. ↑ RidgeRun Developer Wiki, “NVIDIA Jetson Thor: Powering the Future of Physical AI.” https://developer.ridgerun.com/wiki/index.php/NVIDIA_Jetson_Thor:_Powering_the_Future_of_Physical_AI (accessed Aug 28, 2025).
  22. ↑ RidgeRun Blog. https://www.ridgerun.com/blog (accessed Aug 28, 2025).
  23. ↑ 23.0 23.1 NVIDIA Developer, “NVIDIA Programmable Vision Accelerator (PVA) SDK.” https://developer.nvidia.com/embedded/pva (accessed Aug 28, 2025).
  24. ↑ NVIDIA GPU Technology Conference, “GstCUDA – Easy GStreamer and CUDA Integration,” 2019. https://developer.download.nvidia.com/video/gputechconf/gtc/2019/presentation/s9391-gstcuda-easy-gstreamer-and-cuda-integration.pdf (accessed Aug 28, 2025).
  25. ↑ RidgeRun Developer Wiki, “FPGA Image Signal Processor,” Nov 15, 2024. https://developer.ridgerun.com/wiki/index.php/FPGA_Image_Signal_Processor (accessed Aug 28, 2025).
  26. ↑ GStreamer, “GStreamer Conference 2023,” Sept 25, 2023. https://gstreamer.freedesktop.org/conference/2023/ (accessed Aug 28, 2025).
  27. ↑ GStreamer, “GStreamer Conference 2017 – Speaker Program,” Oct 21, 2017. https://gstreamer.freedesktop.org/conference/2017/talks-and-speakers.html (accessed Aug 28, 2025).
  28. ↑ GStreamer Conference Video Channel, “GstInference: A GStreamer Deep Learning Framework.” https://gstconf.ubicast.tv/videos/gstinference-a-gstreamer-deep-learning-framework/ (accessed Aug 28, 2025).
  29. ↑ GStreamer Conference Proceedings, “GStreamer Daemon – Building a Media Server under 30 min,” 2017. https://gstreamer.freedesktop.org/data/events/gstreamer-conference/2017/David%20Soto%20-%20GStreamer%20Daemon%20-%20Building%20a%20media%20server%20under%2030min.pdf (accessed Aug 28, 2025).
  30. ↑ GitHub, “RidgeRun/gstd.” https://github.com/RidgeRun/gstd (accessed Aug 28, 2025).
  31. ↑ GitHub, “RidgeRun/gst-inference.” https://github.com/RidgeRun/gst-inference (accessed Aug 28, 2025).
  32. ↑ GitHub, “RidgeRun (organization) – Embedded Solutions.” https://github.com/RidgeRun (accessed Aug 28, 2025).
  33. ↑ RidgeRun Developer Wiki, “GstRtspSink.” https://developer.ridgerun.com/wiki/index.php?title=RtspSink (accessed Aug 28, 2025).
  34. ↑ RidgeRun Developer Wiki, “GstSEIMetadata.” https://developer.ridgerun.com/wiki/index.php/GstSEIMetadata (accessed Aug 28, 2025).
  35. ↑ 35.0 35.1 Yocto Project, “RidgeRun – Consultants.” https://www.yoctoproject.org/blog/consultant/ridgerun/ (accessed Aug 28, 2025).
  36. ↑ GStreamer, “GStreamer Conference 2017: GstShark profiling (slides).” https://gstreamer.freedesktop.org/data/events/gstreamer-conference/2017/Michael%20Gr%C3%BCner%20-%20GstShark%20profiling%20-%20a%20real-life%20example.pdf (accessed Aug 28, 2025).
  37. ↑ GStreamer, “GStreamer Conference 2018 Program (includes RidgeRun talk).” https://gstreamer.freedesktop.org/conference/2018/talks-and-speakers.html (accessed Aug 28, 2025).
  38. ↑ NVIDIA, “GTC 2019: GstCUDA – Write your own GStreamer filter in CUDA,” 2019. https://developer.nvidia.com/gtc/2019/video/s9957 (accessed Aug 28, 2025).
  39. ↑ NVIDIA, “GTC 2020: GStreamer and CUDA,” 2020. https://www.nvidia.com/en-us/on-demand/session/gtcbr/31452/ (accessed Aug 28, 2025).
  40. ↑ YouTube, “RidgeRun.ai at GTC 2025: How to Find Our Booth,” Mar 19, 2025. https://www.youtube.com/watch?v=u8Unlc_BOus (accessed Aug 28, 2025).
  41. ↑ Stack Overflow, “Using GStreamer to serve RTSP stream, working example sought,” Dec 6, 2012. https://stackoverflow.com/questions/13744560/using-gstreamer-to-serve-rtsp-stream-working-example-sought (accessed Aug 28, 2025).
  42. ↑ YouTube, “Embedded Streaming Media with GStreamer (Part 2),” Feb 12, 2013. https://www.youtube.com/watch?v=MDSmrZholBc (accessed Aug 28, 2025).
  43. ↑ LinuxDevices, “Cortex-A8 SoCs gain Linux GUI toolkit,” Oct 29, 2018. https://linuxdevices.org/cortex-a8-socs-gain-linux-gui-toolkit/ (accessed Aug 28, 2025).
  44. ↑ YouTube, “Part 1: GStreamer porting on HawkBoard,” Aug 30, 2010. https://www.youtube.com/watch?v=3QR1Og00w0Y (accessed Aug 28, 2025).
  45. ↑ Stack Overflow (answer), “How to use hardware accelerated video encoding of GStreamer on Android,” Nov 1, 2013. https://stackoverflow.com/a/19723833 (accessed Aug 28, 2025).
  46. ↑ NXP Community, “RidgeRun i.MX 6 Based Solutions,” Apr 2, 2014. https://community.nxp.com/t5/i-MX-Processors-Knowledge-Base/RidgeRun-i-MX-6-Based-Solutions/ta-p/1104855 (accessed Aug 28, 2025).
  47. ↑ RidgeRun Developer Wiki, “IMX6 GStreamer Pipelines – SDK Irazú,” Aug 11, 2017. https://developer.ridgerun.com/wiki/index.php/IMX6_GStreamer_Pipelines_-_SDK_Irazu (accessed Aug 28, 2025).
  48. ↑ NXP (Freescale), “Designing QorIQ Software: SDN Networking and Virtualization,” Oct 1, 2013. https://www.nxp.com/docs/en/supporting-information/DWF13_Designing_QorIQ_Software_SanJose.pdf (accessed Aug 28, 2025).
  49. ↑ TI E2E Support Forums, “RidgeRun GStreamer 0.10 and 1.0 plugins for DM81xx platforms,” June 1, 2012. https://e2e.ti.com/support/processors-group/processors/f/processors-forum/327198/ridgerun-gstreamer-0-10-and-1-0-plugins-for-dm81xx-platforms (accessed Aug 28, 2025).
  50. ↑ RidgeRun Developer Wiki, “Xilinx Ultrascale+ Overview.” https://developer.ridgerun.com/wiki/index.php/Xilinx_Ultrascale%2B_Overview (accessed Aug 28, 2025).
  51. ↑ AMD Adaptive Support, “Xilinx Ultrascale RidgeRun SDK,” Mar 10, 2022. https://adaptivesupport.amd.com/s/question/0D52E00006hpXW8SAM/xilinx-ultrascale-ridgerun-sdk?language=en_US (accessed Aug 28, 2025).
  52. ↑ NVIDIA Developer Blog, “NVIDIA Jetson TX1 Supercomputer-on-Module Drives Next Wave of Autonomous Machines,” Nov 11, 2015. https://developer.nvidia.com/blog/nvidia-jetson-tx1-supercomputer-on-module-drives-next-wave-of-autonomous-machines/ (accessed Aug 28, 2025).
  53. ↑ NVIDIA Developer Forums, “Announcing Yocto Support for Jetson Boards,” Nov 20, 2019. https://forums.developer.nvidia.com/t/announcing-yocto-support-for-jetson-boards/126800 (accessed Aug 28, 2025).
  54. ↑ msadowski.github.io, “Enabling PPS support on Jetson Nano,” Apr 28, 2020. https://msadowski.github.io/pps-support-jetson-nano/ (accessed Aug 28, 2025).
  55. ↑ Hackster.io, “Embedded Diaries: How to use RPi HQ Camera with Jetson,” May 2, 2019. https://www.hackster.io/SaadTiwana/embedded-diaries-how-to-use-rpi-hq-camera-with-jetson-e2063e (accessed Aug 28, 2025).
  56. ↑ YouTube, “GstCUDA presentation at NVIDIA GTC 2019,” May 31, 2019. https://www.youtube.com/watch?v=PcwlnIoM_cI (accessed Aug 28, 2025).
  57. ↑ AUVidea, “J20 Technical Reference Manual.” https://auvidea.eu/download/manual/J20/J20_technical_reference_1.0.pdf (accessed Aug 28, 2025).
  58. ↑ GStreamer Conference Proceedings, “GStreamer and OpenCV using a GstOpenCV element (Angel Phillips),” 2017. https://gstreamer.freedesktop.org/data/events/gstreamer-conference/2017/Angel%20Phillips%20-%20GStreamer%20and%20OpenCV%20using%20a%20GstOpenCV%20element.pdf (accessed Aug 28, 2025).
  59. ↑ YouTube, “Jetson Xavier Multi Camera AI Demo,” Nov 12, 2019. https://www.youtube.com/watch?v=LKNkBFYJPKs (accessed Aug 28, 2025).
  60. ↑ YouTube, “GstInference (GStreamer Deep Learning),” Apr 12, 2019. https://www.youtube.com/watch?v=MujdGxuYs2g (accessed Aug 28, 2025).
  61. ↑ GStreamer Conference, “GStreamer Conference 2018 – Brochure,” 2018. https://gstreamer.freedesktop.org/data/events/gstreamer-conference/2018/GStreamer%20Conference%202018%20-%20Brochure.pdf (accessed Aug 28, 2025).
  62. ↑ RidgeRun, “Embedded Software Development for Medical Devices.” https://www.ridgerun.com/medical-and-healthcare (accessed Aug 29, 2025).
  63. ↑ RidgeRun.ai, “About.” https://www.ridgerun.ai/about (accessed Aug 28, 2025).
  64. ↑ RidgeRun Shop, “NVIDIA’s PVA Performance Evaluation Binaries.” https://shop.ridgerun.com/products/pva-sample-algorithms (accessed Aug 28, 2025).
  65. ↑ RidgeRun Developer Wiki, “RidgeRun NVIDIA PVA Development – Introduction,” June 18, 2025. https://developer.ridgerun.com/wiki/index.php/RidgeRun_NVIDIA_PVA_Development/Introduction (accessed Aug 28, 2025).
  66. ↑ LinkedIn, “RidgeRun, LLC.” https://www.linkedin.com/company/ridgerun (accessed Aug 29, 2025).
  67. ↑ RidgeRun, “Supported SoC & Platforms.” https://www.ridgerun.com/supported-soc-platforms (accessed Aug 28, 2025).
  68. ↑ RidgeRun, “GStreamer Development & Consulting Services.” https://www.ridgerun.com/engineering-services/gstreamer (accessed Aug 28, 2025).
  69. ↑ RidgeRun Developer Wiki, “GstRtspSink – High-Performance RTSP Sink for GStreamer,” Nov 10, 2024. https://developer.ridgerun.com/wiki/index.php/GstRtspSink (accessed Aug 29, 2025).
  70. ↑ RidgeRun Developer Wiki, “Real-Time Bird's Eye View Generation via Image Transformation,” May 27, 2025. https://developer.ridgerun.com/wiki/index.php/Birds_Eye_View (accessed Aug 29, 2025).
  71. ↑ RidgeRun Developer Wiki, “Image Stitching for NVIDIA Jetson – Quick Start Guide,” Dec 6, 2024. https://developer.ridgerun.com/wiki/index.php/Image_Stitching_for_NVIDIA_Jetson/User_Guide/Quick_Start_Guide (accessed Aug 29, 2025).
  72. ↑ RidgeRun Developer Wiki, “MPEG-TS Metadata Basics,” July 28, 2025. https://developer.ridgerun.com/wiki/index.php/GStreamer_In-Band_Metadata_for_MPEG_Transport_Stream/MPEG_TS_Metadata_Basics (accessed Aug 29, 2025).
  73. ↑ RidgeRun Developer Wiki, “GstSEIMetadata Basics,” Nov 8, 2024. https://developer.ridgerun.com/wiki/index.php/GstSEIMetadata/GstSEIMetadata_Basics (accessed Aug 29, 2025).
  74. ↑ RidgeRun Shop, “All Products.” https://shop.ridgerun.com/collections/all (accessed Aug 29, 2025).
  75. ↑ RidgeRun Documents, “RidgeRun Products Catalog.” https://app-na1.hubspotdocuments.com/documents/5319431/view/810724903?accessId=e71367 (accessed Aug 29, 2025).
  76. ↑ RidgeRun, “Embedded Software Development Services.” https://www.ridgerun.com/engineering-services (accessed Aug 29, 2025).
  77. ↑ RidgeRun Developer Wiki, “GstShark: Performance Analysis & Tracing for GStreamer Developers,” May 12, 2025. https://developer.ridgerun.com/wiki/index.php/GstShark (accessed Aug 29, 2025).
  78. ↑ GitHub, “RidgeRun/gst-shark – GStreamer tracing front-end.” https://github.com/RidgeRun/gst-shark (accessed Aug 29, 2025).
  79. ↑ GitHub, “RidgeRun/gst-perf – GStreamer element to measure framerate, bitrate and CPU usage.” https://github.com/RidgeRun/gst-perf (accessed Aug 29, 2025).
  80. ↑ RidgeRun Developer Wiki, “GstInterpipes – Inter-pipeline communication element,” May 11, 2025. https://developer.ridgerun.com/wiki/index.php/GstInterpipe (accessed Aug 29, 2025).
  81. ↑ RidgeRun Developer Wiki, “GstCUDA Framework – GStreamer CUDA Base Classes,” Nov 7, 2024. https://developer.ridgerun.com/wiki/index.php/GstCUDA_-_GstCUDA_Framework (accessed Aug 29, 2025).
  82. ↑ RidgeRun Developer Wiki, “GstRtspSink – Basic Usage,” Nov 4, 2024. https://developer.ridgerun.com/wiki/index.php/GstRtspSink_-_Basic_usage (accessed Aug 29, 2025).
  83. ↑ RidgeRun Developer Wiki, “GstWebRTC Fundamentals: WebRTC Development Guide,” May 12, 2025. https://developer.ridgerun.com/wiki/index.php/GstWebRTC_-_WebRTC_Fundamentals (accessed Aug 29, 2025).
  84. ↑ RidgeRun Developer Wiki, “Sony IMX219 Linux Driver for Jetson Xavier,” Oct 25, 2024. https://developer.ridgerun.com/wiki/index.php/Xavier/Video_Capture_and_Display/Cameras/IMX219 (accessed Aug 29, 2025).
  85. ↑ RidgeRun Developer Wiki, “Raspberry Pi HQ Camera IMX477 Linux Driver for Jetson,” Jan 1, 2025. https://developer.ridgerun.com/wiki/index.php/Raspberry_Pi_HQ_camera_IMX477_Linux_driver_for_Jetson (accessed Aug 29, 2025).
  86. ↑ RidgeRun Developer Wiki, “Yocto Support for NVIDIA® Jetson™ with JetPack 6 Integration,” June 4, 2025. https://developer.ridgerun.com/wiki/index.php/Yocto_Support_for_NVIDIA®_Jetson™_with_JetPack_6_Integration (accessed Aug 29, 2025).
  87. ↑ RidgeRun Developer Wiki, “Embedded Linux, Multimedia & Robotics Resources – Main Page,” May 12, 2025. https://developer.ridgerun.com/wiki/index.php/Main_Page (accessed Aug 29, 2025).
  88. ↑ RidgeRun, “RidgeRun Blog.” https://www.ridgerun.com/blog (accessed Aug 29, 2025).
  89. ↑ RidgeRun.ai, “Developers Center – Resources and Industry Insights.” https://www.ridgerun.ai/developer (accessed Aug 29, 2025).
  90. ↑ RidgeRun, “About – Embedded Linux Experts.” https://www.ridgerun.com/about (accessed Aug 28, 2025).
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