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--- projects:internetofthings:jetsonnano [2019/08/01 07:42] – [python 3.8] scipio
+++ projects:internetofthings:jetsonnano [2023/11/16 08:39] (current) – [remove desktop] sscipioni
@@ Line 1: / Line 1: @@
 ====== Nvidia Jetson Nano ======
+  * https://github.com/Qengineering/Jetson-Nano-Ubuntu-20-image
   * [[https://developer.nvidia.com/embedded/jetson-nano-developer-kit|interesting projects]]
+  * [[https://elinux.org/Jetson/Cameras|cameras]]
+  * [[https://www.edmundoptics.eu/c/cameras/1012/|camera search engine]]
-===== query =====
+===== remove desktop =====
+<code>
+apt remove -y ubuntu-desktop
+apt remove -y gnome-*
+apt remove -y chromium-browser chromium-codecs-ffmpeg-extra
+apt remove -y libreoffice* docker.io thunderbird bluez*
+apt remove -y libnvinfer-samples
+# remove snap
+systemctl stop snapd
+apt remove --purge --assume-yes snapd gnome-software-plugin-snap
+rm -rf /var/cache/snapd/
+apt autoremove -y
+</code>
+<code>
+systemctl disable lightdm whoopsie  ModemManager bluetooth.service gpsd
+</code>
+===== tools =====
 jtop
@@ Line 55: / Line 78: @@
 sudo make install
 </code>
+===== numpy =====
+Patch to numpy/random/mt19937.c numpy/random/bit_generator.c numpy/random/generator.c
+<code>
+from
+PyCode_New(a, 0, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
+to
+PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
+</code>
 ===== opencv 4.1 =====
@@ Line 68: / Line 104: @@
 apt install -y build-essential cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev
 apt install -y libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev
-</code>
-<del>python 3.7</del>
-<code>
-curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
-python3.7 get-pip.py
-pip3.7 install -U wheel
-pip3.7 install -I numpy
-pip3.7 install Cython
 </code>
@@ Line 110: / Line 137: @@
 <code>
 cp /usr/local/lib/python3.7/site-packages/cv2/python-3.7/cv2.cpython-37m-aarch64-linux-gnu.so lib/lib/python3.7/site-packages/
+</code>
+===== benchmarks =====
+  * **darknet** alexey **20FPS** with YOLOV3-tiny and image size 416
+<code>
+cd /lab/dnn/models/plates-tiny
+darknet detector demo model.data model.test.cfg backup/model_final.weights /lab/dnn/dataset/dataset/marocco/originals/video/01.mkv -dont_show
+</code>
+  * yolo34py  **12FPS**
+<code>
+python process_video.py --model plates-tiny dataset/dataset/marocco/originals/video/01.mkv
 </code>

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