Difference between revisions of "Jetson TX1"
m |
(→System Tools) |
||
(134 intermediate revisions by 12 users not shown) | |||
Line 1: | Line 1: | ||
− | NVIDIA | + | NVIDIA [https://developer.nvidia.com/embedded/buy/jetson-tx1-devkit Jetson TX1] is an embedded system-on-module (SoM) with quad-core ARM Cortex-A57, 4GB LPDDR4 and integrated 256-core Maxwell GPU. <br /> |
Useful for deploying computer vision and deep learning, Jetson TX1 runs Linux and provides 1TFLOPS of FP16 compute performance in 10 watts of power. | Useful for deploying computer vision and deep learning, Jetson TX1 runs Linux and provides 1TFLOPS of FP16 compute performance in 10 watts of power. | ||
− | Jetson TX1 is available as the '''[[#Jetson TX1 Module|module]]''', '''[[#Jetson TX1 Developer Kit|developer kit]]''', and in compatible '''[[#Ecosystem Products|ecosystem]]''' products. | + | Jetson TX1 is available as the '''[[#Jetson TX1 Module|module]]''', '''[[#Jetson TX1 Developer Kit|developer kit]]''', and in compatible '''[[#Ecosystem Products|ecosystem]]''' products. See the wiki of other Jetson's '''[[Jetson|here]]''', including the latest [[Jetson AGX Xavier]]. |
+ | {| style="color: black; background-color: #ffffff; width: 600px;" | ||
+ | |- | ||
+ | | style="width: 50px; background-color: white;"| | ||
+ | | style="width: 550px; background-color: #76b900;"| | ||
+ | {{spaces|1}} <span style="font-family: Trebuchet MS; color: white;">'''Parallel ForAll''' — </span>''[https://devblogs.nvidia.com/parallelforall/nvidia-jetson-tx1-supercomputer-on-module-drives-next-wave-of-autonomous-machines/ <span style="font-family: Trebuchet MS; color:white;">NVIDIA Jetson TX1 Drives Next Wave of Autonomous Machines</span>]'' | ||
+ | |}<br /> | ||
[[File:Jetson_TX1_DevKit_Module_combo.jpg|800px|right|text-bottom]] | [[File:Jetson_TX1_DevKit_Module_combo.jpg|800px|right|text-bottom]] | ||
− | |||
= Jetson TX1 Module = | = Jetson TX1 Module = | ||
Line 41: | Line 46: | ||
=== Software Support === | === Software Support === | ||
− | <div style="width: | + | <div style="width:40%;column-count:2;-moz-column-count:2;-webkit-column-count:2"> |
− | * [https://developer.nvidia.com/embedded/jetpack JetPack 2. | + | * [https://developer.nvidia.com/embedded/jetpack JetPack 4.2.2] |
− | * [https://developer.nvidia.com/embedded/linux-tegra Linux4Tegra | + | * [https://developer.nvidia.com/embedded/linux-tegra Linux4Tegra R32.2.1] (L4T) |
− | * CUDA Toolkit | + | * Linux kernel 4.9 |
− | * cuDNN | + | * Ubuntu 18.04 aarch64 |
− | * [https://developer.nvidia.com/tensorrt TensorRT] 1.0 | + | * [https://developer.nvidia.com/cuda-toolkit CUDA Toolkit] 10.0.326 |
− | * [https://developer.nvidia.com/embedded/visionworks VisionWorks] 1. | + | * [https://developer.nvidia.com/cudnn cuDNN] 7.5.0 |
− | * | + | * [https://developer.nvidia.com/tensorrt TensorRT] 5.1.6 |
− | * OpenGL 4. | + | * [https://docs.nvidia.com/deeplearning/frameworks/install-tf-jetson-platform/index.html TensorFlow] 1.14.0 |
− | + | * [https://developer.nvidia.com/embedded/visionworks VisionWorks] 1.6 | |
− | * | + | * OpenCV 3.3.1 |
+ | * OpenGL 4.6 / OpenGL ES 3.2.5 | ||
+ | * Vulkan 1.1.1 | ||
+ | * [http://developer.nvidia.com/embedded/dlc/l4t-multimedia-api-reference-32-1 L4T Multimedia API] (Argus 0.97) | ||
+ | * GStreamer 1.14.1 | ||
* V4L2 media controller support | * V4L2 media controller support | ||
− | + | * [https://developer.nvidia.com/nsight-systems NVIDIA Nsight Systems] 2019.4 | |
− | * [https://developer.nvidia.com/ | + | * [https://developer.nvidia.com/nsight-graphics NVIDIA Nsight Graphics] 2019.2 |
− | * [https://developer.nvidia.com/ | + | * [https://developer.nvidia.com/nsight-compute NVIDIA Nsight Compute] 1.0 |
− | * [https://developer.nvidia.com/ | ||
</div> | </div> | ||
+ | |||
+ | See the '''[[Jetson Zoo]]''' for more software packages to install on top of JetPack. | ||
+ | |||
+ | {| style="color: black; background-color: #ffffff; width: 575px;" | ||
+ | |- | ||
+ | | style="width: 1px; background-color: white;"| | ||
+ | | style="width: 550px; background-color: #76b900;"| | ||
+ | {{spaces|1}} <span style="font-family: Trebuchet MS; color: white;">'''Parallel ForAll''' — </span>''[https://devblogs.nvidia.com/parallelforall/jetpack-doubles-jetson-inference-perf/ <span style="font-family: Trebuchet MS; color:white;">JetPack 3.1 Doubles Jetson's Low-Latency Inference Performance</span>]'' | ||
+ | |} | ||
=== Availability === | === Availability === | ||
Line 100: | Line 117: | ||
* '''[http://developer.nvidia.com/embedded/dlc/jetson-tx1-module-data-sheet Module Datasheet]''' {{spaces|8}} the official module features, ports, signal pin-out, and package specifications. | * '''[http://developer.nvidia.com/embedded/dlc/jetson-tx1-module-data-sheet Module Datasheet]''' {{spaces|8}} the official module features, ports, signal pin-out, and package specifications. | ||
* '''[http://developer.nvidia.com/embedded/dlc/jetson-tx1-oem-product-design-guide Design Guide]''' {{spaces|16}} detailed technical design and layout information for creating OEM products. | * '''[http://developer.nvidia.com/embedded/dlc/jetson-tx1-oem-product-design-guide Design Guide]''' {{spaces|16}} detailed technical design and layout information for creating OEM products. | ||
− | * '''[ | + | * '''[https://developer.nvidia.com/embedded/dlc/l4t-28-1-jetson-developer-kit-user-guide DevKit User Guide]''' {{spaces|8}} guide to unpacking, setting up, and flashing the Jetson TX1 Developer Kit. |
* '''[http://developer.nvidia.com/embedded/dlc/jetson-tx1-developer-kit-carrier-board-spec DevKit Carrier Spec]''' {{spaces|6}} design info about the reference carrier board from the devkit. | * '''[http://developer.nvidia.com/embedded/dlc/jetson-tx1-developer-kit-carrier-board-spec DevKit Carrier Spec]''' {{spaces|6}} design info about the reference carrier board from the devkit. | ||
* '''[https://developer.nvidia.com/embedded/dlc/jetson-tx1-developer-kit-carrier-board-design-files DevKit Design Files]''' {{spaces|6}} schematics, layout, and design files for the devkit reference carrier board. | * '''[https://developer.nvidia.com/embedded/dlc/jetson-tx1-developer-kit-carrier-board-design-files DevKit Design Files]''' {{spaces|6}} schematics, layout, and design files for the devkit reference carrier board. | ||
Line 107: | Line 124: | ||
* '''[http://developer.nvidia.com/embedded/dlc/jetson-tx1-thermal-design-guide Thermal Design Guide]''' {{spaces|1}} mechanical specifications for designing active and passive cooling solutions. | * '''[http://developer.nvidia.com/embedded/dlc/jetson-tx1-thermal-design-guide Thermal Design Guide]''' {{spaces|1}} mechanical specifications for designing active and passive cooling solutions. | ||
* '''[http://developer.nvidia.com/embedded/dlc/jetson-tx1-module-pinmux Module PinMux]''' {{spaces|13}} excel spreadsheet macro for generating ARM device tree source (DTS) files. | * '''[http://developer.nvidia.com/embedded/dlc/jetson-tx1-module-pinmux Module PinMux]''' {{spaces|13}} excel spreadsheet macro for generating ARM device tree source (DTS) files. | ||
− | * '''[ | + | * '''[https://developer.nvidia.com/embedded/dlc/l4t-documentation-28-1 L4T Kernel Docs]''' {{spaces|11}} documentation for L4T kernel developers (including V4L2/camera drivers). |
− | |||
* '''[http://developer.nvidia.com/embedded/dlc/tegra-x1-data-sheet-for-jetson-tx1 Tegra X1 TRM]''' {{spaces|15}} Technical Reference Manual for the TX1 system-on-chip and register data. | * '''[http://developer.nvidia.com/embedded/dlc/tegra-x1-data-sheet-for-jetson-tx1 Tegra X1 TRM]''' {{spaces|15}} Technical Reference Manual for the TX1 system-on-chip and register data. | ||
+ | * '''[https://developer.nvidia.com/embedded/dlc/l4t-multimedia-api-reference-28-1 Multimedia API Reference]''' {{spaces|8}} documentation to Argus camera API and V4L2 media codecs | ||
+ | * '''[https://developer.nvidia.com/embedded/dlc/l4t-accelerated-gstreamer-guide-28-1 Accelerated GStreamer Guide]''' {{spaces|1}} example gstreamer pipelines for accessing H.264/H.265 hardware video codec. | ||
Above is a partial list of documents. | Above is a partial list of documents. | ||
Line 118: | Line 136: | ||
This section contains recipes for following along on Jetson. | This section contains recipes for following along on Jetson. | ||
− | === System | + | === System Tools === |
− | <div style="width: | + | <div style="width:75%;column-count:2;-moz-column-count:2;-webkit-column-count:2"> |
− | :* [[Jetson/ | + | :* [[Jetson/Clone|Clone & Restore]] |
+ | :* [https://github.com/jtagxhub/jetpack-agx-build Jetson TX1 Build Assistant Scripts] | ||
+ | :* [[Jetson/FAQ/BSP|BSP FAQ]] | ||
:* [ftp://download.nvidia.com/tegra-public-appnotes/flashing-tools.html Flashing Tools and Protocols] | :* [ftp://download.nvidia.com/tegra-public-appnotes/flashing-tools.html Flashing Tools and Protocols] | ||
:* [http://http.download.nvidia.com/tegra-public-appnotes/bct-overview.html Boot Configuration Table (BCT) Overview] | :* [http://http.download.nvidia.com/tegra-public-appnotes/bct-overview.html Boot Configuration Table (BCT) Overview] | ||
:* [ftp://download.nvidia.com/tegra-public-appnotes/tegra-boot-flow.html Tegra Boot Flow] {{spaces|2}} ([ftp://download.nvidia.com/tegra-public-appnotes/t210-nvtboot-flow.html '''nvtboot''' for TX1]) | :* [ftp://download.nvidia.com/tegra-public-appnotes/tegra-boot-flow.html Tegra Boot Flow] {{spaces|2}} ([ftp://download.nvidia.com/tegra-public-appnotes/t210-nvtboot-flow.html '''nvtboot''' for TX1]) | ||
+ | :* [https://developer.ridgerun.com/wiki/index.php?title=Compiling_Tegra_X1_source_code Compiling the L4T Kernel] | ||
:* [[Jetson/TX1 Upstream Kernel|Using the Upstream Linux Kernel]] | :* [[Jetson/TX1 Upstream Kernel|Using the Upstream Linux Kernel]] | ||
:* [[Jetson/TX1 Sample Root Filesystem|Building the Ubuntu Sample Root Filesystem]] | :* [[Jetson/TX1 Sample Root Filesystem|Building the Ubuntu Sample Root Filesystem]] | ||
Line 129: | Line 150: | ||
:* [[Jetson/TX1 Power Monitor|Measuring Power with Onboard INA Monitors]] | :* [[Jetson/TX1 Power Monitor|Measuring Power with Onboard INA Monitors]] | ||
:* [https://www.youtube.com/watch?v=R_GzhZe8IcM Intro to Tegra System Profiler] | :* [https://www.youtube.com/watch?v=R_GzhZe8IcM Intro to Tegra System Profiler] | ||
− | :* [https:// | + | :* [https://devtalk.nvidia.com/default/topic/940155/jetson-tx1/mipi-dsi-csi-design-and-develop-guide/ MIPI DSI/CSI Design and Develop Guide] |
+ | :* [[Jetson/TX1 SPI|Enabling the SPI Port]] | ||
:* [[Jetson/TX1 Serial Console|Wiring the Serial Console]] | :* [[Jetson/TX1 Serial Console|Wiring the Serial Console]] | ||
:* [http://jetsonhacks.com/2015/12/29/gpio-interfacing-nvidia-jetson-tx1/ GPIO Interfacing] (JetsonHacks) | :* [http://jetsonhacks.com/2015/12/29/gpio-interfacing-nvidia-jetson-tx1/ GPIO Interfacing] (JetsonHacks) | ||
− | |||
− | |||
:* [[Jetson/TX1_WiFi_Access_Point|Running WiFi Access Point with hostapd]] | :* [[Jetson/TX1_WiFi_Access_Point|Running WiFi Access Point with hostapd]] | ||
+ | :* [https://github.com/ross-abaco/abaco-launcher Python GUI Gstreamer Launcher] (includes temp sensor and bandwidth monitor) | ||
+ | :* [https://devtalk.nvidia.com/default/topic/1003598/jetson-tx1/code-to-send-a-bayer-video-feed-from-a-tx1-to-an-h-264-encoder-to-an-rtp-sink-/ Sending Bayer➝H.264➝RTP Stream] (GStreamer pipeline) | ||
+ | :* [https://elinux.org/Jetson/TX1_UCM Tegra Use Case Model configuration] | ||
+ | :* [https://github.com/rbonghi/jetson_easy jetson_easy] - automatic setup/scripting | ||
</div> | </div> | ||
+ | |||
+ | === Robotics === | ||
+ | |||
+ | :* [https://github.com/NVIDIA-Jetson NVIDIA Jetson GitHub] {{spaces|8}} (open-source robotics projects with deep learning) | ||
+ | :* [https://github.com/NVIDIA-Jetson/redtail NVIDIA Redtail GitHub] {{spaces|7}} (end-to-end deep learning drone for ROS) | ||
+ | :* [https://developer.nvidia.com/embedded/community/reference-platforms Jetson Reference Platforms] (off-the-shelf robots with TX1/TX2) | ||
+ | :* [[Jetson/FRC_Setup|FIRST FRC Configuration]] {{spaces|5}} (setup guide for FIRST Robotics) | ||
+ | :* [https://www.chiefdelphi.com/media/papers/download/5169 ROS for FRC Whitepaper] {{spaces|2}} (Zebracorns team #900 Vision [https://github.com/FRC900/2017VisionCode GitHub]) | ||
+ | :* [http://www.jetsonhacks.com/2016/10/12/robot-operating-system-ros-on-nvidia-jetson-tx1/ Installing ROS Kinetic] {{spaces|8}} (JetsonHacks) | ||
+ | :* [https://github.com/mit-racecar/particle_filter Fast SLAM Particle Filter] {{spaces|3}} (Accelerated Localization using Raycasting) | ||
+ | :* [http://jetsonhacks.com/2015/12/08/gpioi2c-on-jetson-tx1-lidar-lite-v2-installation/ Using I2C and LIDAR-Lite] {{spaces|1}} (JetsonHacks) | ||
+ | :* [http://ardupilot.org/dev/docs/companion-computer-nvidia-tx1.html Connecting the Pixhawk and TX1] (ArduPilot) | ||
=== Computer Vision === | === Computer Vision === | ||
Line 145: | Line 181: | ||
:* [https://developer.nvidia.com/embedded/learn/tutorials#collapseVisionWorks VisionWorks Training] | :* [https://developer.nvidia.com/embedded/learn/tutorials#collapseVisionWorks VisionWorks Training] | ||
:* [https://devtalk.nvidia.com/default/topic/934354/typical-approaches-to-test-camera-functionality-for-l4t-r23-2-on-jetson-tx1/ Camera Testing in L4T on TX1] | :* [https://devtalk.nvidia.com/default/topic/934354/typical-approaches-to-test-camera-functionality-for-l4t-r23-2-on-jetson-tx1/ Camera Testing in L4T on TX1] | ||
− | :* [https:// | + | :* [https://github.com/ross-abaco/rtp-motion-estimation Motion Estimation on RTP streaming video] |
=== Deep Learning === | === Deep Learning === | ||
+ | <div style="width:80%;column-count:2;-moz-column-count:2;-webkit-column-count:2"> | ||
+ | :* [https://developer.nvidia.com/embedded/twodaystoademo NVIDIA Two Days to a Demo] {{spaces|1}} ([https://devblogs.nvidia.com/parallelforall/jetpack-doubles-jetson-tx1-deep-learning-inference/ TensorRT]) | ||
:* [https://developer.nvidia.com/deep-learning-institute NVIDIA Deep Learning Institute] {{spaces|1}} ([https://developer.nvidia.com/deep-learning-courses QwikLabs]) | :* [https://developer.nvidia.com/deep-learning-institute NVIDIA Deep Learning Institute] {{spaces|1}} ([https://developer.nvidia.com/deep-learning-courses QwikLabs]) | ||
:* Caffe {{spaces|1}} (BVLC [https://github.com/BVLC/caffe/wiki/Model-Zoo Model Zoo]) | :* Caffe {{spaces|1}} (BVLC [https://github.com/BVLC/caffe/wiki/Model-Zoo Model Zoo]) | ||
+ | :** [https://github.com/nvidia/caffe NVcaffe FP16] {{spaces|1}} ([https://github.com/dusty-nv/jetson-inference/blob/master/docs/building-nvcaffe.md Install Guide]) | ||
:** [http://jetsonhacks.com/2015/12/07/caffe-deep-learning-framework-nvidia-jetson-tx1/ Caffe Installation on TX1] (JetsonHacks) | :** [http://jetsonhacks.com/2015/12/07/caffe-deep-learning-framework-nvidia-jetson-tx1/ Caffe Installation on TX1] (JetsonHacks) | ||
:** [https://gitlab.com/jbernauer/tx1-lab1 Caffe Hands-on Lab] {{spaces|2}} [https://github.com/juliebernauer/tx1-lab2 GitHub repo] | :** [https://gitlab.com/jbernauer/tx1-lab1 Caffe Hands-on Lab] {{spaces|2}} [https://github.com/juliebernauer/tx1-lab2 GitHub repo] | ||
:** [http://myplace.frontier.com/~r.bond/cats/cats.htm Cat Detector with Caffe and TX1] {{spaces|2}} (Robert Bond) | :** [http://myplace.frontier.com/~r.bond/cats/cats.htm Cat Detector with Caffe and TX1] {{spaces|2}} (Robert Bond) | ||
:** [https://www.nvidia.com/content/tegra/embedded-systems/pdf/jetson_tx1_whitepaper.pdf GPU-based Inference whitepaper] {{spaces|1}} [https://devtalk.nvidia.com/default/topic/935300/jetson-tx1/deep-learning-inference-performance-validation-on-tx1/ Performance Validation] | :** [https://www.nvidia.com/content/tegra/embedded-systems/pdf/jetson_tx1_whitepaper.pdf GPU-based Inference whitepaper] {{spaces|1}} [https://devtalk.nvidia.com/default/topic/935300/jetson-tx1/deep-learning-inference-performance-validation-on-tx1/ Performance Validation] | ||
− | :* [https://github.com/dusty-nv/jetson-reinforcement/blob/master/CMakePreBuild.sh Torch7] {{spaces|1}} install script | + | :* [http://www.jetsonhacks.com/2016/12/30/tensorflow-nvidia-jetson-tx1-development-kit/ TensorFlow] post {{spaces|1}} (JetsonHacks) |
+ | :* [https://github.com/dusty-nv/jetson-reinforcement/blob/master/CMakePreBuild.sh Torch7] {{spaces|1}} install script | ||
+ | :* [https://gist.github.com/dusty-nv/ef2b372301c00c0a9d3203e42fd83426 pyTorch] {{spaces|0}} install script | ||
+ | :* [https://developer.ridgerun.com/wiki/index.php?title=GstInference RidgeRun's GstInference] | ||
+ | :* [https://developer.ridgerun.com/wiki/index.php?title=R2Inference RidgeRun's R2Inference] | ||
:* [http://github.com/dusty-nv dusty-nv's Jetson GitHub] {{spaces|3}} [http://github.com/dusty-nv/jetson-inference jetson-inference] {{spaces|2}} [http://github.com/dusty-nv/jetson-inference jetson-reinforcement] | :* [http://github.com/dusty-nv dusty-nv's Jetson GitHub] {{spaces|3}} [http://github.com/dusty-nv/jetson-inference jetson-inference] {{spaces|2}} [http://github.com/dusty-nv/jetson-inference jetson-reinforcement] | ||
− | :* [https://github.com/vmayoral/basic_reinforcement_learning vmayoral's Basic Reinforcement Learning] {{spaces|3}} [ | + | :* [https://github.com/Abaco-Systems/jetson-inference-gv jetson-inference-gv] Inference on GigEVision / RTP streaming video (Ross Newman) |
+ | :* [https://github.com/S4WRXTTCS/jetson-inference jetson-inference-cards] {{spaces|1}} (playing card recognition by S4WRXTTCS) | ||
+ | :* [https://github.com/vmayoral/basic_reinforcement_learning vmayoral's Basic Reinforcement Learning] {{spaces|3}} | ||
+ | :* [https://jkjung-avt.github.io/ JK Jung RL blog] - NES AI player | ||
+ | :* [https://github.com/AastaNV/ChatBot ChatBot] {{spaces|1}} (TensorFlow→TensorRT inferencing workflow by AastaNV) | ||
+ | :* [https://github.com/AastaNV/Face-Recognition face-recognition] {{spaces|1}} (face detection with TensorRT plugin by AastaNV) | ||
+ | :* [https://github.com/NVIDIA-Jetson NVIDIA GitHub] {{spaces|2}} (open-source robotics/DL projects) | ||
+ | :* [https://github.com/NVIDIA-Jetson/redtail NVIDIA Redtail] {{spaces|2}} (end-to-end deep learning drone for ROS) | ||
+ | :* Training a Fish Detector with DetectNet {{spaces|1}} [https://jkjung-avt.github.io/fisheries-dataset/ part 1] [https://jkjung-avt.github.io/detectnet-training/ part 2] {{spaces|1}} (jkjung) | ||
+ | :* [https://heyjetson.com/ Hey, Jetson!] {{spaces|2}} (Automatic Speech Recognition using CNN/RNN) | ||
+ | :* [https://www.makeartwithpython.com/blog/rich-mans-deep-learning-camera/ Making a Deep Learning Camera with Python] | ||
+ | </div> | ||
+ | |||
+ | === Multimedia === | ||
+ | |||
+ | :* [https://developer.ridgerun.com/wiki/index.php?title=Gstreamer_pipelines_for_Tegra_X1 Gstreamer Pipelines for TX1] | ||
+ | :* [https://developer.ridgerun.com/wiki/index.php?title=GstInterpipe RidgeRun's GstInterpipe] (GStreamer plug-in for communication between two or more independent pipelines) | ||
+ | :* [https://developer.ridgerun.com/wiki/index.php?title=GstWebRTC RidgeRun's GstRRWebRTC] (GStreamer plug-in that turns pipelines into WebRTC compliant endpoints) | ||
+ | :* [https://developer.ridgerun.com/wiki/index.php?title=GstRtspSink RidgeRun's GstRTSPSink] (GStreamer element for high performance streaming to multiple computers using the RTSP/RTP protocols) | ||
+ | :* [https://developer.ridgerun.com/wiki/index.php?title=GStreamer_Daemon RidgeRun's Gstreamer Daemon - GstD] (GStreamer framework for controlling audio and video streaming using TCP connection messages) | ||
+ | :* [http://developer.ridgerun.com/wiki/index.php?title=GstCUDA RidgeRun's GstCUDA] (RidgeRun CUDA ZeroCopy for GStreamer) | ||
+ | :* [https://developer.ridgerun.com/wiki/index.php?title=GStreamer_Pan_Tilt_Zoom_and_Rotate_Element RidgerRun's GstPTZR] (GStreamer Pan Tilt Zoom and Rotate Element) | ||
+ | :* [https://developer.ridgerun.com/wiki/index.php?title=GStreamer_Color_Transfer RidgeRun's GstColorTransfer] (GStreamer plug-in that transfers the color scheme from a reference to a target image) | ||
+ | |||
+ | === V4L2 drivers for cameras === | ||
+ | |||
+ | *RidgeRun has a [https://developer.ridgerun.com/wiki/index.php?title=V4L2_drivers_available_for_Jetson_SoCs list of drivers already supported in Jetson], please check if the driver that you need is already there. Otherwise, RidgeRun offers [https://developer.ridgerun.com/wiki/index.php?title=V4L2_driver_for_camera_sensor_or_capture_chip services to create the driver for you] | ||
+ | |||
+ | === Design FAQs === | ||
+ | There are some useful FAQs for Jetson TX1 design, link is [[Jetson_TX1/FAQ|here]]. | ||
+ | |||
+ | = Linux Distributions = | ||
+ | [[File:Debian.png||right]] | ||
+ | |||
+ | Jetson TX1 comes preloaded with NVIDIA's Linux4Tegra (L4T) distribution based on Ubuntu. | ||
+ | |||
+ | However it is possible to install other distributions on a Tegra device: | ||
+ | |||
+ | * [https://wiki.debian.org/InstallingDebianOn/NVIDIA/Jetson-TX1 Debian]: Debian has installer and kernel support for the Jetson TX1 development kit and provides a u-boot binary | ||
+ | * [https://github.com/AGLExport/meta-jetson Yocto]: Jetson TX1 upstream kernel base Yocto bsp layer | ||
+ | * [https://github.com/AGLExport/agl-jetson AGL distro for jetson TX1/TK1]: AGL distro for Jetson TX1/TK1. | ||
+ | |||
+ | <br /> | ||
+ | = Multiple Cameras = | ||
+ | There are several ways to handle multiple cameras on Jetson TX1 at the same time: | ||
+ | |||
+ | [https://www.e-consystems.com/multiple-csi-cameras-for-nvidia-jetson-tx2.asp 6 MIPI CSI-2 Cameras] support for Jetson TX1 from e-con systems<br /> | ||
+ | [https://www.e-consystems.com/three-synchronized-4k-cameras-for-nvidia-jetson-tx2.asp 3 MIPI CSI-2 Cameras] support for Jetson TX1 from e-con systems | ||
+ | |||
<br /> | <br /> | ||
= Ecosystem Products = | = Ecosystem Products = | ||
− | The following are 3rd-party carriers, enclosures, drones, and accessories available for Jetson TX1 | + | The following are 3rd-party carriers, enclosures, drones, and accessories available for Jetson TX1. |
<br /> | <br /> | ||
− | + | === Cameras === | |
− | :* | + | :* APPROPHO [http://www.appropho.com/products_en.html?type=36 TX1/TX2 Camera Solutions] |
− | :* | + | :* Code Laboratories [https://duo3d.com/ Duo3D camera] |
− | :* Auvidea [http://www.auvidea.eu/index.php/2015-11-08-08-01-27/2016-02-03-12-30-02/j200-dual-jetson-tx1-carrier J200] | + | :* D3 Engineering [https://www.d3engineering.com/solutions/embedded-vision Smart Camera] |
+ | :* DCDZ(冬虫电子) [[Jetson/xcb-lite| XCB-OV5640 ]] OV5640 M12 lens camera | ||
+ | :* DCDZ(冬虫电子) [[Jetson/xcb-lite| XCB-OV5693 ]] OV5693 camera | ||
+ | :* Leopard Imaging [https://leopardimaging.com/product-category/nvidia-jetson-cameras/nvidia-tx1tx2-mipi-camera-kits/csi-2-mipi-cameras/ TX1/TX2 Camera Kits] | ||
+ | :* e-con Systems [https://www.e-consystems.com/13mp-autofocus-nvidia-jetson-tx2-camera-board.asp 13MP AR1335 AF MIPI Jetson TX1/TX2 Camera] | ||
+ | :* e-con Systems [https://www.e-consystems.com/13mp-nvidia-jetson-tx2-camera-board.asp 13MP AR1335 MIPI Jetson TX1/TX2 Camera] | ||
+ | :* e-con Systems [https://www.e-consystems.com/2MP-HDR-Jetson-TX2-TX1-Camera-Board.asp 2MP AR0230AT MIPI Jetson TX1/TX2 Camera] | ||
+ | :* e-con Systems [https://www.e-consystems.com/jetson-tx2-ultra-low-light-camera-board.asp 2MP SONY IMX290 MIPI Jetson TX1/TX2 Camera] | ||
+ | :* e-con Systems [https://www.e-consystems.com/autofocus-liquid-lens-nvidia-jetson-tx2-camera.asp 3.4 MP AF AR0330 MIPI Jetson TX1/TX2 Camera] | ||
+ | :* e-con Systems [https://www.e-consystems.com/13mp-nvidia-jetson-tx1-camera-board.asp 13MP AR1820 MIPI Jetson TX1/TX2 Camera] | ||
+ | :* e-con Systems [https://www.e-consystems.com/3MP-Jetson-TX1-Camera-board.asp 3.4 MP AR0330 MIPI Jetson TX1/TX2 Camera] | ||
+ | :* e-con Systems [https://www.e-consystems.com/gmsl-camera-for-nvidia-jetson-tx2.asp 3.4 MP AR0330 GMSL MIPI Jetson TX1/TX2 Camera] | ||
+ | :* [http://www.photoneo.com/ Photoneo] carrier & camera module | ||
+ | :* [https://www.stereolabs.com/ Stereolabs ZED] stereo depth camera | ||
+ | :* [http://www.viooa.com/ Viooa Solo] | ||
+ | |||
+ | === Carriers === | ||
+ | |||
+ | :* Auvidea [https://auvidea.com/product/70760/ J90] carrier | ||
+ | :* Auvidea [https://auvidea.com/j100/ J100] carrier | ||
+ | :* Auvidea [https://auvidea.com/j106/ J106] carrier (6 camera) | ||
+ | :* Auvidea [https://auvidea.com/j120/ J120] carrier | ||
+ | :* Auvidea [https://auvidea.com/j130-with-4k-video-input/ J130] carrier (4K input) | ||
+ | :* Auvidea [https://auvidea.com/j140-dual-gbe/ J140] dual-GbE carrier | ||
+ | :* Auvidea [https://auvidea.com/j150/ J150] OpenGear blade | ||
+ | :* Auvidea [http://www.auvidea.eu/index.php/2015-11-08-08-01-27/2016-02-03-12-30-02/j200-dual-jetson-tx1-carrier J200] carrier | ||
+ | :* Avermedia [https://www.avermedia.com/professional/product/ex731_aa_n1/overview EX731-AA] carrier | ||
+ | :* Avermedia [https://www.avermedia.com/professional/product/ex713_aa/overview EX713-AA] carrier | ||
+ | :* Avermedia [https://www.avermedia.com/professional/product/ex711_aa/overview EX711-AA] carrier | ||
+ | :* ConnectTech [http://www.connecttech.com/sub/Products/ASG008.asp?l1=GPU&l2=ASG008 Sprocket] carrier | ||
:* ConnectTech [http://www.connecttech.com/sub/Products/ASG003.asp?l1=GPU&l2=ASG003 Orbitty] carrier | :* ConnectTech [http://www.connecttech.com/sub/Products/ASG003.asp?l1=GPU&l2=ASG003 Orbitty] carrier | ||
− | :* ConnectTech [http://www.connecttech.com/sub/Products/ | + | :* ConnectTech [http://www.connecttech.com/sub/Products/ASG006.asp?l1=GPU&l2=ASG006 Spacely] carrier |
+ | :* ConnectTech [http://www.connecttech.com/sub/Products/ASG007.asp?l1=GPU&l2=ASG007 Cogswell] carrier | ||
:* ConnectTech [http://www.connecttech.com/sub/Products/ASG002.asp?l1=GPU&l2=ASG002 Elroy] carrier | :* ConnectTech [http://www.connecttech.com/sub/Products/ASG002.asp?l1=GPU&l2=ASG002 Elroy] carrier | ||
− | |||
:* ConnectTech [http://www.connecttech.com/sub/Products/ASG001.asp?l1=GPU&l2=ASG001 Astro] carrier | :* ConnectTech [http://www.connecttech.com/sub/Products/ASG001.asp?l1=GPU&l2=ASG001 Astro] carrier | ||
+ | :* ConnectTech [http://connecttech.com/sub/Products/VPG003_GraphiteVPXTX1.asp?l1=GPU&l2=VPXTX1 3U VPX] card | ||
:* Colorado Engineering [https://coloradoengineering.com/standard-products/tx1-som/ TX1-SOM] | :* Colorado Engineering [https://coloradoengineering.com/standard-products/tx1-som/ TX1-SOM] | ||
− | :* | + | :* Gumstix [https://store.gumstix.com/aerocore2-for-nvidia-jetson.html Aerocore2] drone carrier |
− | :* | + | :* Leopard Imaging [https://www.leopardimaging.com/LI-TX1-CB.html TX1 Camera Carrier] |
− | :* | + | :* [https://mr-technologies.com/supercomputer-gpu-modules/ MR TECH AM203] AMC carrier for ATCA/μTCA |
+ | :* [https://mr-technologies.com/supercomputer-gpu-modules/ MR TECH TX1 carrier] with XIMEA camera interfaces | ||
+ | :* [http://www.pixevia.com/p-core?i=s10 Pixevia CORE X1] drone carrier | ||
+ | |||
+ | === Enclosures === | ||
+ | :* ConnectTech [http://www.connecttech.com/sub/Products/ESG501.asp?l1=GPU&l2=ESG501 Rosie] enclosure | ||
+ | :* ConnectTech [http://connecttech.com/sub/Products/ESG503.asp?l1=GPU&l2=ESG503 Rudi] enclosure | ||
+ | :* ConnectTech [http://www.connecttech.com/sub/Products/UTX1AS-Array-Server.asp UTX1AS] array server | ||
+ | :* Puget Systems [https://www.pugetsystems.com/store/item.php?cat=Case&id=11365&com=d41d8cd9 Acrylic Enclosure] | ||
+ | :* USES Integrated [https://www.usesintegrated.com/ UTX1AS] array server | ||
+ | :* [https://www.vision4ce.com/wp-content/uploads/2017/09/CHARM-100-170801.pdf Vision4CE CHARM-100] enclosure | ||
+ | |||
+ | === Expansion Boards === | ||
+ | :* Auvidea [http://auvidea.eu/j20/ J20] 6-camera module | ||
+ | :* DCDZ(冬虫电子) [[Jetson/xcb-lite| XCB-Lite carrier]] with eDP, CSI, DSI, MicroHDMI etc | ||
+ | :* DCDZ(冬虫电子) [[Jetson/xcb-lite| XCB-H2C ]] HDMI to CSI expansion board | ||
+ | :* DCDZ(冬虫电子) [[Jetson/xcb-lite| XCB-SDI ]] SDI to CSI expansion board | ||
+ | :* DCDZ(冬虫电子) [[Jetson/xcb-lite| XCB-8eyes ]] 4 or 8 cameras ADAS expansion board | ||
+ | :* DCDZ(冬虫电子) [[Jetson/xcb-lite| XCB-AUDIO ]] Sound card expansion board | ||
+ | :* ZHAW [http://www.pender.ch/products_zhaw.shtml 4K HDMI2CSI interface] | ||
+ | :* [[BeadaPanel#BeadaPanel_for_NVIDIA_Jetson_Dev._Board|BeadaPanel USB Display+WiFi+Storage 3-In-1 Companion Kit]] | ||
+ | |||
+ | === Other === | ||
+ | :* [http://f1tenth.org/ Formula F1/10] RC car | ||
+ | :* [http://www.jetsonhacks.com/category/robotics/jetson-racecar/ JetsonHacks RACECAR] | ||
:* [http://tealdrones.com/ iDrone Teal] high-speed drone | :* [http://tealdrones.com/ iDrone Teal] high-speed drone | ||
− | :* [ | + | :* [https://mit-racecar.github.io/ MIT RACECAR] |
:* [http://pleiades.ca/ Pleiades Spiri] developer drone | :* [http://pleiades.ca/ Pleiades Spiri] developer drone | ||
− | :* | + | :* [http://www.prioria.com Prioria Merlin] autopilot |
− | :* [ | + | :* RidgeRun [https://developer.ridgerun.com/wiki/index.php?title=Category:TegraX1 GStreamer and Multimedia Solutions] |
− | |||
− | |||
TX1 SoC is also used in [[TX1 product list|consumer products]]. | TX1 SoC is also used in [[TX1 product list|consumer products]]. | ||
<br /> | <br /> | ||
+ | <br /> | ||
+ | |||
+ | = USB 3.0 webcams known to be working = | ||
+ | |||
+ | * e-con Systems' [https://www.e-consystems.com/4k-usb-camera.asp See3CAM_CU135] was tested on [[Jetson TX1]] with 1920x1080 @ 29 FPS (uncompressed), 1920x1080 @ 18 FPS (MJPG compressed), 4096x2160 @ 6 FPS (uncompressed), 4208x3120 @ 3 FPS (uncompressed), as well as other settings. | ||
+ | |||
+ | * e-con Systems' [https://www.e-consystems.com/13mp-autofocus-usb-camera.asp See3CAM_130] was tested on [[Jetson TX1]] with 1920x1080 @ 29 FPS (uncompressed), 1920x1080 @ 15 FPS (MJPG compressed), 4096x2160 @ 7 FPS (uncompressed), 4208x3120 @ 4 FPS (uncompressed), as well as other settings. | ||
+ | |||
+ | * e-con Systems' [https://www.e-consystems.com/8MP-AF-UVC-USB-Camera.asp See3CAM_81] was tested on [[Jetson TX1]] with 1920x1080 @ 12 FPS (uncompressed), 3264x2448 @ 5 FPS (uncompressed), as well as other settings. | ||
+ | |||
+ | * e-con Systems' [https://www.e-consystems.com/ar0330-liquid-lens-usb-camera-board.asp See3CAM_30] was tested on [[Jetson TX1]] with 1920x1080 @ 13 FPS (uncompressed), 1280x720 @ 30 FPS (uncompressed), 1920x1080 @ 42 FPS (MJPG compressed), 1280x720 @ 20 FPS (MJPG compressed),as well as other settings. | ||
+ | |||
+ | * e-con Systems' [https://www.e-consystems.com/ar0330-lowlight-usb-cameraboard.asp See3CAM_CU30] was tested on [[Jetson TX1]] with 1920x1080 @ 13 FPS (uncompressed), 1280x720 @ 30 FPS (uncompressed), 1920x1080 @ 42 FPS (MJPG compressed), 1280x720 @ 20 FPS (MJPG compressed),as well as other settings. | ||
+ | |||
+ | * Stereolabs ZED | ||
+ | * Point Grey Flea3 & Blackfly | ||
+ | * Logitech C920 | ||
+ | |||
<br /> | <br /> | ||
Revision as of 19:33, 13 November 2019
NVIDIA Jetson TX1 is an embedded system-on-module (SoM) with quad-core ARM Cortex-A57, 4GB LPDDR4 and integrated 256-core Maxwell GPU.
Useful for deploying computer vision and deep learning, Jetson TX1 runs Linux and provides 1TFLOPS of FP16 compute performance in 10 watts of power.
Jetson TX1 is available as the module, developer kit, and in compatible ecosystem products. See the wiki of other Jetson's here, including the latest Jetson AGX Xavier.
Parallel ForAll — NVIDIA Jetson TX1 Drives Next Wave of Autonomous Machines |
Contents
Jetson TX1 Module
The Jetson TX1 module contains all the active processing components. The ports are broken out through a carrier board.
Below is a partial list of the module's features. Please see the Module Datasheet for the complete specifications.
Processing Components
- quad-core ARM Cortex-A57
- 256-core Maxwell GPU
- 4GB LPDDR4
- 16GB eMMC
- H.264/H.265 encoder & decoder
- Dual ISPs (Image Service Processors)
Ports & Peripherals
- HDMI 2.0
- 802.11ac WiFi, Bluetooth 4.0
- USB3, USB2
- Gigabit Ethernet
- 12 lanes MIPI CSI 2.0
- 4 lanes PCIe gen 2.0
- SATA, 2x SDcard
- 3x UART, 3x SPI, 4x I2C
Form-Factor
- 400-pin Samtec board-to-board connector
- dimensions: 50x87mm (1.96" x 3.42")
- mass: 45 grams
- Thermal Transfer Plate (TTP), -25C to 85C operating temperature
- 5.5-19.6VDC input power (consuming 10-15W, under typical load)
Software Support
- JetPack 4.2.2
- Linux4Tegra R32.2.1 (L4T)
- Linux kernel 4.9
- Ubuntu 18.04 aarch64
- CUDA Toolkit 10.0.326
- cuDNN 7.5.0
- TensorRT 5.1.6
- TensorFlow 1.14.0
- VisionWorks 1.6
- OpenCV 3.3.1
- OpenGL 4.6 / OpenGL ES 3.2.5
- Vulkan 1.1.1
- L4T Multimedia API (Argus 0.97)
- GStreamer 1.14.1
- V4L2 media controller support
- NVIDIA Nsight Systems 2019.4
- NVIDIA Nsight Graphics 2019.2
- NVIDIA Nsight Compute 1.0
See the Jetson Zoo for more software packages to install on top of JetPack.
Parallel ForAll — JetPack 3.1 Doubles Jetson's Low-Latency Inference Performance |
Availability
- Europe - Silicon Highway
- USA - Arrow
- Use the Region Selector to find distributors of the module in your region.
Jetson TX1 Developer Kit
The Jetson TX1 Developer Kit bundles together all the parts to get started, including:
What's Included
- mini-ITX Reference carrier board
- Jetson TX1 Module
- fan and heatsink (pre-assembled)
- 5MP CSI camera module (with Omnivision OV5693)
- WiFi/BT antennas
- USB OTG adapter
- 19VDC Power brick
- AC Power cable
The design files for the reference carrier board and camera module included in the devkit are freely available for download.
Getting Started
- Get the latest development software for PC and TX1 by using JetPack.
- Plug in an HDMI display into Jetson, attach the antennas and USB keyboard & mouse, and apply power to boot it up. (User Guide)
- Visit the Embedded Developer Zone and Developer Forum to access the latest documentation & downloads.
Availability
- Use the Region Selector to find distributors of the devkit in your region.
- There's also an Academic Discount available for those belonging to an educational organization.
Platform Documentation
NVIDIA has released comprehensive documentation and reference designs for the Jetson TX1 module and devkit.
- Module Datasheet the official module features, ports, signal pin-out, and package specifications.
- Design Guide detailed technical design and layout information for creating OEM products.
- DevKit User Guide guide to unpacking, setting up, and flashing the Jetson TX1 Developer Kit.
- DevKit Carrier Spec design info about the reference carrier board from the devkit.
- DevKit Design Files schematics, layout, and design files for the devkit reference carrier board.
- DevKit CAD Models 3D STEP file for reference carrier board, heatsink, camera board, and module.
- Camera Design Files schematics, layout, and design files for the devkit MIPI CSI-2 camera module.
- Thermal Design Guide mechanical specifications for designing active and passive cooling solutions.
- Module PinMux excel spreadsheet macro for generating ARM device tree source (DTS) files.
- L4T Kernel Docs documentation for L4T kernel developers (including V4L2/camera drivers).
- Tegra X1 TRM Technical Reference Manual for the TX1 system-on-chip and register data.
- Multimedia API Reference documentation to Argus camera API and V4L2 media codecs
- Accelerated GStreamer Guide example gstreamer pipelines for accessing H.264/H.265 hardware video codec.
Above is a partial list of documents.
Please visit the Downloads Center at Embedded Developer Zone for the full list that's currently available.
Guides and Tutorials
This section contains recipes for following along on Jetson.
System Tools
- Clone & Restore
- Jetson TX1 Build Assistant Scripts
- BSP FAQ
- Flashing Tools and Protocols
- Boot Configuration Table (BCT) Overview
- Tegra Boot Flow (nvtboot for TX1)
- Compiling the L4T Kernel
- Using the Upstream Linux Kernel
- Building the Ubuntu Sample Root Filesystem
- Controlling Core Clock Frequency Performance
- Measuring Power with Onboard INA Monitors
- Intro to Tegra System Profiler
- MIPI DSI/CSI Design and Develop Guide
- Enabling the SPI Port
- Wiring the Serial Console
- GPIO Interfacing (JetsonHacks)
- Running WiFi Access Point with hostapd
- Python GUI Gstreamer Launcher (includes temp sensor and bandwidth monitor)
- Sending Bayer➝H.264➝RTP Stream (GStreamer pipeline)
- Tegra Use Case Model configuration
- jetson_easy - automatic setup/scripting
Robotics
- NVIDIA Jetson GitHub (open-source robotics projects with deep learning)
- NVIDIA Redtail GitHub (end-to-end deep learning drone for ROS)
- Jetson Reference Platforms (off-the-shelf robots with TX1/TX2)
- FIRST FRC Configuration (setup guide for FIRST Robotics)
- ROS for FRC Whitepaper (Zebracorns team #900 Vision GitHub)
- Installing ROS Kinetic (JetsonHacks)
- Fast SLAM Particle Filter (Accelerated Localization using Raycasting)
- Using I2C and LIDAR-Lite (JetsonHacks)
- Connecting the Pixhawk and TX1 (ArduPilot)
Computer Vision
Deep Learning
- NVIDIA Two Days to a Demo (TensorRT)
- NVIDIA Deep Learning Institute (QwikLabs)
- Caffe (BVLC Model Zoo)
- TensorFlow post (JetsonHacks)
- Torch7 install script
- pyTorch install script
- RidgeRun's GstInference
- RidgeRun's R2Inference
- dusty-nv's Jetson GitHub jetson-inference jetson-reinforcement
- jetson-inference-gv Inference on GigEVision / RTP streaming video (Ross Newman)
- jetson-inference-cards (playing card recognition by S4WRXTTCS)
- vmayoral's Basic Reinforcement Learning
- JK Jung RL blog - NES AI player
- ChatBot (TensorFlow→TensorRT inferencing workflow by AastaNV)
- face-recognition (face detection with TensorRT plugin by AastaNV)
- NVIDIA GitHub (open-source robotics/DL projects)
- NVIDIA Redtail (end-to-end deep learning drone for ROS)
- Training a Fish Detector with DetectNet part 1 part 2 (jkjung)
- Hey, Jetson! (Automatic Speech Recognition using CNN/RNN)
- Making a Deep Learning Camera with Python
Multimedia
- Gstreamer Pipelines for TX1
- RidgeRun's GstInterpipe (GStreamer plug-in for communication between two or more independent pipelines)
- RidgeRun's GstRRWebRTC (GStreamer plug-in that turns pipelines into WebRTC compliant endpoints)
- RidgeRun's GstRTSPSink (GStreamer element for high performance streaming to multiple computers using the RTSP/RTP protocols)
- RidgeRun's Gstreamer Daemon - GstD (GStreamer framework for controlling audio and video streaming using TCP connection messages)
- RidgeRun's GstCUDA (RidgeRun CUDA ZeroCopy for GStreamer)
- RidgerRun's GstPTZR (GStreamer Pan Tilt Zoom and Rotate Element)
- RidgeRun's GstColorTransfer (GStreamer plug-in that transfers the color scheme from a reference to a target image)
V4L2 drivers for cameras
- RidgeRun has a list of drivers already supported in Jetson, please check if the driver that you need is already there. Otherwise, RidgeRun offers services to create the driver for you
Design FAQs
There are some useful FAQs for Jetson TX1 design, link is here.
Linux Distributions
Jetson TX1 comes preloaded with NVIDIA's Linux4Tegra (L4T) distribution based on Ubuntu.
However it is possible to install other distributions on a Tegra device:
- Debian: Debian has installer and kernel support for the Jetson TX1 development kit and provides a u-boot binary
- Yocto: Jetson TX1 upstream kernel base Yocto bsp layer
- AGL distro for jetson TX1/TK1: AGL distro for Jetson TX1/TK1.
Multiple Cameras
There are several ways to handle multiple cameras on Jetson TX1 at the same time:
6 MIPI CSI-2 Cameras support for Jetson TX1 from e-con systems
3 MIPI CSI-2 Cameras support for Jetson TX1 from e-con systems
Ecosystem Products
The following are 3rd-party carriers, enclosures, drones, and accessories available for Jetson TX1.
Cameras
- APPROPHO TX1/TX2 Camera Solutions
- Code Laboratories Duo3D camera
- D3 Engineering Smart Camera
- DCDZ(冬虫电子) XCB-OV5640 OV5640 M12 lens camera
- DCDZ(冬虫电子) XCB-OV5693 OV5693 camera
- Leopard Imaging TX1/TX2 Camera Kits
- e-con Systems 13MP AR1335 AF MIPI Jetson TX1/TX2 Camera
- e-con Systems 13MP AR1335 MIPI Jetson TX1/TX2 Camera
- e-con Systems 2MP AR0230AT MIPI Jetson TX1/TX2 Camera
- e-con Systems 2MP SONY IMX290 MIPI Jetson TX1/TX2 Camera
- e-con Systems 3.4 MP AF AR0330 MIPI Jetson TX1/TX2 Camera
- e-con Systems 13MP AR1820 MIPI Jetson TX1/TX2 Camera
- e-con Systems 3.4 MP AR0330 MIPI Jetson TX1/TX2 Camera
- e-con Systems 3.4 MP AR0330 GMSL MIPI Jetson TX1/TX2 Camera
- Photoneo carrier & camera module
- Stereolabs ZED stereo depth camera
- Viooa Solo
Carriers
- Auvidea J90 carrier
- Auvidea J100 carrier
- Auvidea J106 carrier (6 camera)
- Auvidea J120 carrier
- Auvidea J130 carrier (4K input)
- Auvidea J140 dual-GbE carrier
- Auvidea J150 OpenGear blade
- Auvidea J200 carrier
- Avermedia EX731-AA carrier
- Avermedia EX713-AA carrier
- Avermedia EX711-AA carrier
- ConnectTech Sprocket carrier
- ConnectTech Orbitty carrier
- ConnectTech Spacely carrier
- ConnectTech Cogswell carrier
- ConnectTech Elroy carrier
- ConnectTech Astro carrier
- ConnectTech 3U VPX card
- Colorado Engineering TX1-SOM
- Gumstix Aerocore2 drone carrier
- Leopard Imaging TX1 Camera Carrier
- MR TECH AM203 AMC carrier for ATCA/μTCA
- MR TECH TX1 carrier with XIMEA camera interfaces
- Pixevia CORE X1 drone carrier
Enclosures
- ConnectTech Rosie enclosure
- ConnectTech Rudi enclosure
- ConnectTech UTX1AS array server
- Puget Systems Acrylic Enclosure
- USES Integrated UTX1AS array server
- Vision4CE CHARM-100 enclosure
Expansion Boards
- Auvidea J20 6-camera module
- DCDZ(冬虫电子) XCB-Lite carrier with eDP, CSI, DSI, MicroHDMI etc
- DCDZ(冬虫电子) XCB-H2C HDMI to CSI expansion board
- DCDZ(冬虫电子) XCB-SDI SDI to CSI expansion board
- DCDZ(冬虫电子) XCB-8eyes 4 or 8 cameras ADAS expansion board
- DCDZ(冬虫电子) XCB-AUDIO Sound card expansion board
- ZHAW 4K HDMI2CSI interface
- BeadaPanel USB Display+WiFi+Storage 3-In-1 Companion Kit
Other
- Formula F1/10 RC car
- JetsonHacks RACECAR
- iDrone Teal high-speed drone
- MIT RACECAR
- Pleiades Spiri developer drone
- Prioria Merlin autopilot
- RidgeRun GStreamer and Multimedia Solutions
TX1 SoC is also used in consumer products.
USB 3.0 webcams known to be working
- e-con Systems' See3CAM_CU135 was tested on Jetson TX1 with 1920x1080 @ 29 FPS (uncompressed), 1920x1080 @ 18 FPS (MJPG compressed), 4096x2160 @ 6 FPS (uncompressed), 4208x3120 @ 3 FPS (uncompressed), as well as other settings.
- e-con Systems' See3CAM_130 was tested on Jetson TX1 with 1920x1080 @ 29 FPS (uncompressed), 1920x1080 @ 15 FPS (MJPG compressed), 4096x2160 @ 7 FPS (uncompressed), 4208x3120 @ 4 FPS (uncompressed), as well as other settings.
- e-con Systems' See3CAM_81 was tested on Jetson TX1 with 1920x1080 @ 12 FPS (uncompressed), 3264x2448 @ 5 FPS (uncompressed), as well as other settings.
- e-con Systems' See3CAM_30 was tested on Jetson TX1 with 1920x1080 @ 13 FPS (uncompressed), 1280x720 @ 30 FPS (uncompressed), 1920x1080 @ 42 FPS (MJPG compressed), 1280x720 @ 20 FPS (MJPG compressed),as well as other settings.
- e-con Systems' See3CAM_CU30 was tested on Jetson TX1 with 1920x1080 @ 13 FPS (uncompressed), 1280x720 @ 30 FPS (uncompressed), 1920x1080 @ 42 FPS (MJPG compressed), 1280x720 @ 20 FPS (MJPG compressed),as well as other settings.
- Stereolabs ZED
- Point Grey Flea3 & Blackfly
- Logitech C920
Getting Help
If you have a technical question or bug report, please visit the DevTalk Developer Forums and search or start a topic.
See the official Support page on Embedded Developer Zone for warranty and RMA information: https://developer.nvidia.com/embedded/support
For NVIDIA webstore Customer Service, please see the My Account page or contact 1-800-797-6530.