{ "ok": true, "data": { "title": "EZ-0075", "rev_id": 10679, "updated_at": "2021-08-27T10:28:30+00:00", "chunk_count": 20, "chunks": [ { "title": "EZ-0075", "rev_id": 10679, "heading_path": "", "chunk_index": 0, "content": "# EZ-0075", "char_count": 9, "token_estimate": 3 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "NVIDIA® Jetson Nano™ Developer Kit", "chunk_index": 1, "content": "
\n\"EZ_0075_1.jpg\"\n
EZ_0075_1.jpg<\/figcaption>\n<\/figure>", "char_count": 158, "token_estimate": 40 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "Description", "chunk_index": 2, "content": "NVIDIA® Jetson Nano™ Developer Kit is a small,\npowerful computer that lets you run run multiple neural networks in parallel for applications like image classification,\nobject detection, segmentation, and speech processing.\nAll in an easy-to-use platform that runs in as little as 5 watts.\nIt’s simpler than ever to get started!\nJust insert a microSD card with the system image, boot the developer kit, and begin using the latest NVIDIA JetPack SDK.\nJetPack is compatible with NVIDIA’s world-leading AI platform for training and deploying AI software.\n\"EZ_0075_10.jpg\" The same JetPack SDK is used across the entire NVIDIA Jetson™ family of products.\nPlus, it’s compatible with NVIDIA’s world-leading AI platform for training and deploying AI software,\nreducing complexity and effort for developers.", "char_count": 866, "token_estimate": 217 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "Features", "chunk_index": 3, "content": "
\n\"EZ_0075_11.jpg\"\n
EZ_0075_11.jpg<\/figcaption>\n<\/figure>", "char_count": 162, "token_estimate": 41 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "Features", "chunk_index": 4, "content": "| Features | Details |\n|--------------|-----------------------------------------------------------------------|\n| GPU | 128-core Maxwell |\n| CPU | Quad-core ARM A57 @ 1.43 GHz |\n| Memory | 4 GB 64-bit LPDDR4 25.6 GB\/s |\n| Storage | microSD (not included) |\n| Video Encode | 4K @ 30 \\| 4x 1080p @ 30 \\| 9x 720p @ 30 (H.264\/H.265) |\n| Video Decode | 4K @ 60 \\| 2x 4K @ 30 \\| 8x 1080p @ 30 \\| 18x 720p @ 30 (H.264\/H.265) |\n| Camera | 1x MIPI CSI-2 DPHY lanes |\n| Connectivity | Gigabit Ethernet, M.2 Key E |\n| Display | HDMI 2.0 and eDP 1.4 |\n| USB | 4x USB 3.0, USB 2.0 Micro-B |\n| Others | GPIO, I2C, I2S, SPI, UART |", "char_count": 1156, "token_estimate": 289 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "Features", "chunk_index": 5, "content": "| Mechanical | 100 mm x 80 mm x 29 mm |", "char_count": 88, "token_estimate": 22 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "Package Include", "chunk_index": 6, "content": "- 80x100mm Reference Carrier Board\n- Jetson Nano Module with passive heatsink\n- Pop-Up Stand\n- Getting Started Guide\n\n(the complete devkit with module and heatsink weighs 138 grams)", "char_count": 189, "token_estimate": 48 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "Gallery", "chunk_index": 7, "content": "| | | |\n|-----------------------------------------------------------------------------------|-----------------------------------------------|-----------------------------------------------|\n|
\n \"EZ_0075_1.jpg\"\n
EZ_0075_1.jpg<\/figcaption>\n <\/figure> | [none \\|300px](File:EZ_0075_4.jpg \"wikilink\") | [none \\|300px](File:EZ_0075_3.jpg \"wikilink\") |", "char_count": 698, "token_estimate": 175 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "Gallery", "chunk_index": 8, "content": "| | | |\n|-----------------------------------------------------------------------------------|-----------------------------------------------|-----------------------------------------------|\n|
\n \"EZ_0075_2.jpg\"\n
EZ_0075_2.jpg<\/figcaption>\n <\/figure> | [none \\|300px](File:EZ_0075_5.jpg \"wikilink\") | [none \\|300px](File:EZ_0075_6.jpg \"wikilink\") |", "char_count": 698, "token_estimate": 175 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "Gallery", "chunk_index": 9, "content": "| | | |\n|-----------------------------------------------------------------------------------|-----------------------------------------------|-----------------------------------------------|\n|
\n \"EZ_0075_7.jpg\"\n
EZ_0075_7.jpg<\/figcaption>\n <\/figure> | [none \\|300px](File:EZ_0075_8.jpg \"wikilink\") | [none \\|300px](File:EZ_0075_9.jpg \"wikilink\") |", "char_count": 698, "token_estimate": 175 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "Document Links", "chunk_index": 10, "content": "- Download Center: \\[ Download Center \\]\n- Jetson Nano Developer Kit User Guide PDF file: [File:Jetson Nano Developer Kit User Guide.pdf](File:Jetson_Nano_Developer_Kit_User_Guide.pdf \"wikilink\")\n\n------------------------------------------------------------------------", "char_count": 345, "token_estimate": 87 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "Software Support", "chunk_index": 11, "content": "- [JetPack 4.2](https:\/\/developer.nvidia.com\/embedded\/jetpack)\n- [Linux4Tegra R32.1](https:\/\/developer.nvidia.com\/embedded\/linux-tegra) (L4T)\n- Linux kernel 4.9\n- Ubuntu 18.04 LTS aarch64\n- CUDA Toolkit 10.0\n- cuDNN 7.3.1\n- [TensorRT](https:\/\/developer.nvidia.com\/tensorrt) 5.0.6\n- TensorFlow 1.31.1\n- [VisionWorks](https:\/\/developer.nvidia.com\/embedded\/visionworks) 1.6\n- OpenCV 3.3.1\n- OpenGL 4.6\n- OpenGL ES 3.2\n- EGL 1.5\n- Vulkan 1.1\n- GStreamer 1.14.1\n- V4L2 media controller support", "char_count": 520, "token_estimate": 130 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "Guides and Tutorials", "chunk_index": 12, "content": "This section contains recipes for following along on Jetson Nano.", "char_count": 65, "token_estimate": 17 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "Guides and Tutorials > System Tools", "chunk_index": 13, "content": "- [L4T Kernel Development Guide](https:\/\/docs.nvidia.com\/jetson\/l4t\/index.html)\n- [Power Supply Considerations](https:\/\/devtalk.nvidia.com\/default\/topic\/1048640\/jetson-nano\/power-supply-considerations-for-jetson-nano-developer-kit\/)\n- [CUDA and VisionWorks Samples](https:\/\/devtalk.nvidia.com\/default\/topic\/1049811\/jetson-nano\/cuda-and-vision-works-demos\/post\/5328027\/#5328027)\n- [Preliminary 3D CAD Model](https:\/\/devtalk.nvidia.com\/default\/topic\/1048817\/jetson-nano\/3d-cad-step-model-for-jetson-nano\/post\/5325051\/#5325051)\n- [Mounting a SWAP File](https:\/\/support.rackspace.com\/how-to\/create-a-linux-swap-file\/)\n- [GPIO Header Pin-out](https:\/\/www.jetsonhacks.com\/nvidia-jetson-nano-j41-header-pinout\/)\n- [Reading Serial Number](https:\/\/devtalk.nvidia.com\/default\/topic\/1050026\/jetson-nano\/read-serial-number-of-jetson-nano\/post\/5329191\/#5329191)\n- [jetson_easy](https:\/\/github.com\/rbonghi\/jetson_easy) - automatic setup\/scripting\n- [jetson_stats](https:\/\/github.com\/rbonghi\/jetson_stats) - jtop, service and other tools", "char_count": 1040, "token_estimate": 260 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "Guides and Tutorials > Computer Vision", "chunk_index": 14, "content": "- [RidgeRun's GstInterpipe](https:\/\/developer.ridgerun.com\/wiki\/index.php?title=GstInterpipe) (GStreamer plug-in for communication between two or more independent pipelines)\n- [RidgeRun's GstRRWebRTC](https:\/\/developer.ridgerun.com\/wiki\/index.php?title=GstWebRTC) (GStreamer plug-in that turns pipelines into WebRTC compliant endpoints)\n- [RidgeRun's GstRTSPSink](https:\/\/developer.ridgerun.com\/wiki\/index.php?title=GstRtspSink) (GStreamer element for high performance streaming to multiple computers using the RTSP\/RTP protocols)\n- [RidgeRun's Gstreamer Daemon - GstD](https:\/\/developer.ridgerun.com\/wiki\/index.php?title=GStreamer_Daemon) (GStreamer framework for controlling audio and video streaming using TCP connection messages)\n- [RidgeRun's GstCUDA](http:\/\/developer.ridgerun.com\/wiki\/index.php?title=GstCUDA) (RidgeRun CUDA ZeroCopy for GStreamer)\n- [RidgerRun's GstPTZR](https:\/\/developer.ridgerun.com\/wiki\/index.php?title=GStreamer_Pan_Tilt_Zoom_and_Rotate_Element) (GStreamer Pan Tilt Zoom and Rotate Element)\n- [RidgeRun's GstColorTransfer](https:\/\/developer.ridgerun.com\/wiki\/index.php?", "char_count": 1113, "token_estimate": 279 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "Guides and Tutorials > Computer Vision", "chunk_index": 15, "content": "title=GStreamer_Color_Transfer) (GStreamer plug-in that transfers the color scheme from a reference to a target image)", "char_count": 118, "token_estimate": 30 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "Guides and Tutorials > Deep Learning", "chunk_index": 16, "content": "- [Hello AI World](https:\/\/github.com\/dusty-nv\/jetson-inference) (jetson-inference)\n- [TensorFlow 1.13.1 Installer](https:\/\/developer.nvidia.com\/embedded\/downloads#?search=TensorFlow) (pip wheel)\n- [PyTorch 1.1 Installer](https:\/\/devtalk.nvidia.com\/default\/topic\/1049071\/jetson-nano\/pytorch-for-jetson-nano\/) (pip wheel)\n- [MXNet 1.4 Installer](https:\/\/devtalk.nvidia.com\/default\/topic\/1049293\/jetson-nano\/i-was-unable-to-compile-and-install-mxnet-on-the-jetson-nano-is-there-an-official-installation-tutorial-\/post\/5326170\/#5326170) (pip wheel)\n- [Deep Learning Inference Benchmarking Instructions](https:\/\/devtalk.nvidia.com\/default\/topic\/1050377\/jetson-nano\/deep-learning-inference-benchmarking-instructions\/)\n- [TensorFlow Object Detection With TensorRT](https:\/\/medium.com\/swlh\/how-to-run-tensorflow-object-detection-model-on-jetson-nano-8f8c6d4352e8) (TF-TRT)\n- [RidgeRun's GstInference](https:\/\/developer.ridgerun.com\/wiki\/index.php?title=GstInference)\n- [RidgeRun's R2Inference](https:\/\/developer.ridgerun.com\/wiki\/index.php?title=R2Inference)\n\nSee the [NVIDIA AI-IoT GitHub](https:\/\/github.com\/NVIDIA-AI-IOT\/) for other coding resources on deploying AI and deep learning.", "char_count": 1196, "token_estimate": 299 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "Guides and Tutorials > Robotics", "chunk_index": 17, "content": "- [NVIDIA JetBot](https:\/\/github.com\/NVIDIA-AI-IOT\/jetbot) (AI-powered robotics kit)\n- [jetbot_ros](https:\/\/github.com\/dusty-nv\/jetbot_ros) (ROS nodes for JetBot)\n- [ROS Melodic](http:\/\/wiki.ros.org\/melodic\/Installation\/Ubuntu) (ROS install guide)\n- [ros_deep_learning](https:\/\/github.com\/dusty-nv\/ros_deep_learning) (jetson-inference nodes)\n\nSee the Jetson Nano **[Supported Components List](https:\/\/developer.nvidia.com\/embedded\/dlc\/jetson-nano-supported-components-list)** for devices that have been qualified by NVIDIA to work with Jetson Nano.", "char_count": 556, "token_estimate": 139 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "FAQ", "chunk_index": 18, "content": "- FAQ:[ Jetson Nano FAQ](https:\/\/developer.nvidia.com\/embedded\/faq \"wikilink\")\n- Q: My Camera is no responding, why?\n\n` A: Only Support offical camera on Version V2.1`\n\n- Q: What is 12V power supply DC cable's Specifications?\n\n` A: It is 5.5 x 2.5 mm, and Negtive outside, positive inside.`", "char_count": 296, "token_estimate": 74 }, { "title": "EZ-0075", "rev_id": 10679, "heading_path": "Youtube Video", "chunk_index": 19, "content": "\"Youtube.jpeg\"\nPlease follow the link: \\[ Jetson Nano Developer Kit Open Box \\| \\]\n\n------------------------------------------------------------------------", "char_count": 251, "token_estimate": 63 } ] } }