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If you enjoy this Instructable, consider checking out my TechWizTime YouTube Channel.ДЄnd for a good source of Raspberry Pi products, check out my Raspberry Pi Amazon List.

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If you turned on SSH, youвЂ™ll see a warning, click on вЂњYesвЂќД¬ongratulations, youвЂ™ve just installed Raspbian on your Windows 10 PC via QEMU, configured it, optimized it and thatвЂ™s it for this Instructable. Open it again via cmd using the вЂњstart.batвЂќ Type in вЂњsudo /etc/init.d/dphys-swapfile startвЂќД®XTRA: You can go to Localization and select your country of residence or the country you prefer and then click on вЂњKeyboardвЂќ to change your keyboard settings. Type in вЂњsudo /etc/init.d/dphys-swapfile stopвЂќ Go down to where it says вЂњconf_swapsize=100вЂќ and change the вЂњ100вЂќ to вЂњ1024вЂќ Get inside the Terminal of Raspbian once it loads.ДЄ message will appear saying that the partition rezise was successful. In the cmd, start the emulator by starting the вЂњstart.batвЂќ file. YouвЂ™ll get a message stating that the creation of the partition failed, shut down the emulator for the changes to take effect. When it ask for the last sector, press вЂњEnterвЂќ to use the whole ammount of the image. YouвЂ™ll be asked for the first sector of the partition, type in the number you see on the first partition +1.

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Press вЂњEnterвЂќ Step 6: Optimize the Emulator i'm ready to manually download needed cores and copy it to rpi.

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In the cmd, type in вЂњqemu-img.exe resize -raspbian-jessie.img +4GвЂќДЄ small error will appear, but the resizing will take effect. We are bringing you the most powerful and integrated Design, Simulation, and Manufacturing software for free. Type in вЂњsudo nano /etc/udev/rules.d/lesвЂќ Press вЂњEnterвЂќ Type in вЂњKERNEL=вЂќsdaвЂќ, SYMLINK+=вЂќmmcblk0вЂі KERNEL=вЂќsda?вЂќ, SYMLINK+=вЂќmmcblk0p%nвЂќ KERNEL=вЂќsda2вЂі, SYMLINK+=вЂќrootвЂќвЂќ Type вЂњcmdвЂќ on the address bar to start up the command prompt. Type in вЂњqemu-system-arm -kernel kernel-qemu-4.4.34-jessie -cpu arm1176 -m 256 -M versatilepb -no-reboot -serial stdio -append вЂњroot=/dev/sda2 panic=1 rootfstype=ext4 rw init=/bin/bashвЂќ -drive вЂњfile=-raspbian-jessie.img,index=0,media=disk,format=rawвЂќ -redir tcp:2222::22вЂі VPI 1.Get inside the folder where you extracted Raspbian, QEMU and placed the Kernel.Д¬reate a new text file and name it вЂњstart.batвЂќ.JetPack 4.6 Deep Dive and Demo: Register here.Refer to Jetson Roadmap page for roadmap on Jetson hardware and software.

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Notes: (We will update as items below are published) Those familiar with Linux ARM are probably well read on the different number of tiny sized computers available on the market such as Banana Pi, Beaglebone, Radxa Rock and CuBox TV.These little computers fit in the palm of your hand, yet pack enough power to run as a desktop PC.

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Install JetPack 4.6 using SDK Manager or SD card image (for Jetson Nano 2GB Developer Kit, Jetson Nano Developer Kit and Jetson Xavier NX Developer Kit) or upgrade via Debian package management tool (refer to the instructions here) NoMachine can be installed on most flavours of Linux, and that also includes Linux ARM.

Visit JetPack 4.6 and L4T 32.6.1 page for more details.

Direct downloadable links to JetPack and L4T debian packages for Jetson.

Support for YUV444 8, 10 bit encoding and decoding.

Support for Scalable Video Coding (SVC) H.264 encoding.

Support for configuring for Raspberry-PI IMX219 or Raspberry-PI High Def IMX477 at run time using Jetson-IO tool on Jetson Nano 2GB, Jetson Nano and Jetson Xavier NX developer kits.

Enhanced Jetson-IO tools to configure the camera header interface and dynamically add support for a camera using device tree overlays.

Highlights of JetPack 4.6 for Jetson Nano are: Note that the L4T-base container continues to support existing containerized applications that expect it to mount CUDA and TensorRT components from the host.

These containers are built to containerize AI applications for deployment. In addition to l4t-base container image, new CUDA runtime and TensorRT runtime container images are released on NVIDIA NGC, which include CUDA and TensorRT runtime components inside the container itself, as opposed to mounting those components from the host. JetPack 4.6 includes support for Triton Inference Server, new versions of CUDA, cuDNN and TensorRT, VPI 1.1 with support for new computer vision algorithms and python bindings. We are pleased to announce JetPack 4.6, a production release supporting Jetson AGX Xavier series, Jetson Xavier NX, Jetson TX2 series, Jetson TX1, and Jetson Nano.