Difference between revisions of "Jetson TX1"

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NVIDIA's [https://developer.nvidia.com/embedded-computing Jetson TX1] is an embedded system-on-module (SoM) with quad-core ARM Cortex-A57, 4GB LPDDR4 and integrated 256-core Maxwell GPU.  <br />
+
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. See wiki of other Jetson's [[Jetson|here]].
+
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="color: black; background-color: #ffffff; width: 600px;"
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* '''[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.  
* '''[http://developer.nvidia.com/embedded/dlc/l4t-24-1-jetson-tx1-user-guide DevKit User Guide]''' {{spaces|8}} guide to unpacking, setting up, and flashing the Jetson TX1 Developer Kit.
+
* '''[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.
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* '''[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.
* '''[http://developer.nvidia.com/embedded/dlc/l4t-multimedia-guide-24-1 Multimedia Guide]''' {{spaces|9}} example gstreamer pipelines for accessing H.264/H.265 hardware video codec.
+
* '''[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/l4t-documentation-24-1 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.
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:* [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://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://elinux.org/Jetson/TX1_UCM Tegra Use Case Model configuration]
 +
:* [https://github.com/rbonghi/jetson_easy jetson_easy] - automatic setup/scripting
  
 
</div>
 
</div>
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:* [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://developer.ridgerun.com/wiki/index.php?title=Gstreamer_pipelines_for_Tegra_X1 gstreamer Pipelines for TX1]
 
 
:* [https://github.com/ross-abaco/rtp-motion-estimation Motion Estimation on RTP streaming video]
 
:* [https://github.com/ross-abaco/rtp-motion-estimation Motion Estimation on RTP streaming video]
  
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:* [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]
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:* [https://github.com/dusty-nv/jetson-reinforcement/blob/master/CMakePreBuild.sh Torch7]  {{spaces|1}} install script
 
:* [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://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/Abaco-Systems/jetson-inference-gv jetson-inference-gv] Inference on GigEVision / RTP streaming video (Ross Newman)
 
:* [https://github.com/Abaco-Systems/jetson-inference-gv jetson-inference-gv] Inference on GigEVision / RTP streaming video (Ross Newman)
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:* [https://github.com/vmayoral/basic_reinforcement_learning vmayoral's Basic Reinforcement Learning] {{spaces|3}}
 
:* [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://jkjung-avt.github.io/ JK Jung RL blog] - NES AI player
:* [https://github.com/AastaNV/Face-Recognition face-recognition] {{spaces|1}} (face recognition sample with TensorRT plugin API)
+
:* [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 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)
 
:* [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)
 
:* 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)
</div><br />
+
:* [https://heyjetson.com/ Hey, Jetson!] {{spaces|2}} (Automatic Speech Recognition using CNN/RNN)
<br />
+
:* [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 =
 
= Linux Distributions =
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* [https://github.com/AGLExport/meta-jetson Yocto]: Jetson TX1 upstream kernel base Yocto bsp layer
 
* [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.
 
* [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 />
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:* Auvidea [https://auvidea.com/j150/ J150] OpenGear blade
 
:* 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
 
:* 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/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
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:* Code Laboratories [https://duo3d.com/ Duo3D camera]
 
:* Code Laboratories [https://duo3d.com/ Duo3D camera]
 
:* D3 Engineering [https://www.d3engineering.com/solutions/embedded-vision Smart Camera]
 
:* D3 Engineering [https://www.d3engineering.com/solutions/embedded-vision Smart Camera]
:* 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-Lite carrier]] with eDP, CSI, DSI, MicroHDMI etc
 +
:* 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
 +
:* 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
 
:* Erle Robotics [http://erlerobotics.com Erle-Brain Pro] (coming soon)
 
:* Erle Robotics [http://erlerobotics.com Erle-Brain Pro] (coming soon)
 
:* [http://f1tenth.org/ Formula F1/10] RC car
 
:* [http://f1tenth.org/ Formula F1/10] RC car
 +
:* Gumstix [https://store.gumstix.com/aerocore2-for-nvidia-jetson.html Aerocore2] drone carrier
 
:* [http://www.jetsonhacks.com/category/robotics/jetson-racecar/ JetsonHacks RACECAR]
 
:* [http://www.jetsonhacks.com/category/robotics/jetson-racecar/ JetsonHacks RACECAR]
 
:* Leopard Imaging [https://www.leopardimaging.com/TX1_Camera_Kit.html TX1 Camera Kits]
 
:* Leopard Imaging [https://www.leopardimaging.com/TX1_Camera_Kit.html TX1 Camera Kits]
 
:* Leopard Imaging [https://www.leopardimaging.com/LI-TX1-CB.html TX1 Camera Carrier]
 
:* Leopard Imaging [https://www.leopardimaging.com/LI-TX1-CB.html TX1 Camera Carrier]
:* e-con Systems [https://www.e-consystems.com/13mp-nvidia-jetson-tx2-camera-board.asp 13MP AR1335 MIPI Jetson TX1 Camera]
+
:* 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/autofocus-liquid-lens-nvidia-jetson-tx2-camera.asp 3.4 MP AF AR0330 MIPI Jetson TX1 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/13mp-nvidia-jetson-tx1-camera-board.asp 13MP AR1820 MIPI Jetson TX1 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/3MP-Jetson-TX1-Camera-board.asp 3.4 MP AR0330 MIPI Jetson TX1 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/multiple-csi-cameras-for-nvidia-jetson-tx2.asp Six Synchronized 3.4 MP AR0330 MIPI Jetson TX1 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://tealdrones.com/ iDrone Teal] high-speed drone
 
:* [http://tealdrones.com/ iDrone Teal] high-speed drone
 
:* [https://mit-racecar.github.io/ MIT RACECAR]
 
:* [https://mit-racecar.github.io/ MIT RACECAR]
Line 266: Line 310:
 
:* [https://www.vision4ce.com/wp-content/uploads/2017/09/CHARM-100-170801.pdf Vision4CE CHARM-100] enclosure
 
:* [https://www.vision4ce.com/wp-content/uploads/2017/09/CHARM-100-170801.pdf Vision4CE CHARM-100] enclosure
 
:* ZHAW [http://www.pender.ch/products_zhaw.shtml 4K HDMI2CSI interface]
 
:* 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]]
  
 
</div>
 
</div>
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= USB 3.0 webcams known to be working =
 
= 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 @ 30 FPS (uncompressed), 1920x1080 @ 60 FPS (MJPG compressed), 4096x2160 @ 30 FPS (MJPG compressed), 4208x3120 @ 20 FPS (MJPG compressed),  as well as other settings.
+
* 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/13mp-autofocus-usb-camera.asp See3CAM_130] was tested on [[Jetson TX1]] with 1920x1080 @ 30 FPS (uncompressed), 1920x1080 @ 60 FPS (MJPG compressed), 4096x2160 @ 30 FPS (MJPG compressed), 4208x3120 @ 20 FPS (MJPG compressed), 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 @ 30 FPS (uncompressed), 2304x1536 @ 12 FPS (uncompressed), 1920x1080 @ 60 FPS (MJPG compressed), 2304x1536 @ 48 FPS (MJPG compressed),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/8MP-AF-UVC-USB-Camera.asp See3CAM_81] was tested on [[Jetson TX1]] with 1920x1080 @ 30 FPS (uncompressed), 3264x2448 @ 5 FPS (uncompressed), 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
 
* Stereolabs ZED

Revision as of 19:57, 29 May 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 ForAllNVIDIA Jetson TX1 Drives Next Wave of Autonomous Machines


Jetson TX1 DevKit Module combo.jpg

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.

Jetson TX1 Block Diagram Module.png

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

  Parallel ForAllJetPack 3.1 Doubles Jetson's Low-Latency Inference Performance

Availability


Jetson TX1 Developer Kit

The Jetson TX1 Developer Kit bundles together all the parts to get started, including:

Jetson TX1 DevKit.jpg

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

Robotics

Computer Vision

Deep Learning

Multimedia

V4L2 drivers for cameras

Design FAQs

There are some useful FAQs for Jetson TX1 design, link is here.

Linux Distributions

Debian.png

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:

TX1 SoC is also used in consumer products.

4k usb camera

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.