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--- projects:farmrobot:nvidia-jetson-tx1 [2021/01/03 20:13]
jason
+++ projects:farmrobot:nvidia-jetson-tx1 [2021/01/10 02:12]
jason
@@ Line 6: / Line 6: @@
 | ''jetson''  | ''jetson''    |
-===== Stats =====
+===== Running YOLOv5 with on-board camera =====
+Arguments for NVIDIA's GStreamer camera pipeline depend on supported camera formats.
+To start YOLOv5's detection, run the following command and provide the GStreamer camera pipeline as the source:
+<file shell>
+python3.8 detect.py --source "nvarguscamerasrc ! video/x-raw(memory:NVMM), width=(int)2592, height=(int)1458, framerate=(fraction)30/1, format=(string)NV12 ! nvvidconv flip-method=0 ! video/x-raw, format=(string)BGRx ! videoconvert ! video/x-raw, format=(string)BGR ! appsink"
+</file>
+===== Current data =====
+==== On-board camera ====
+<file shell>
+sudo apt install -y v4l-utils
+</file>
+<file shell>
+v4l2-ctl -d /dev/video0 --list-formats-ext
+ioctl: VIDIOC_ENUM_FMT
+        Index       : 0
+        Type        : Video Capture
+        Pixel Format: 'BG10'
+        Name        : 10-bit Bayer BGBG/GRGR
+                Size: Discrete 2592x1944
+                        Interval: Discrete 0.033s (30.000 fps)
+                Size: Discrete 2592x1458
+                        Interval: Discrete 0.033s (30.000 fps)
+                Size: Discrete 1280x720
+                        Interval: Discrete 0.008s (120.000 fps)
+</file>
+{{:projects:farmrobot:img_20210106_183252.jpg?400|}}
+{{:projects:farmrobot:img_20210106_183318.jpg?400|}}
+{{:projects:farmrobot:img_20210106_183359.jpg?400|}}
+{{:projects:farmrobot:img_20210106_183426.jpg?400|}}
+{{:projects:farmrobot:img_20210107_175211.jpg?400|}}
+==== Measurements ====
 YOLOv5 (street.mp4): 11/12 fps (~0.086s +- 0.005s per frame)
+{{:projects:farmrobot:img_20201228_205724.jpg?600|}}
 ===== Setup =====
@@ Line 55: / Line 97: @@
 After the installation finished, disconnect the Jetson TX1 from the host machine.
+==== Mounting external storage to /home ====
+Mount the partition on the SD-card to ''/mnt'':
+<file shell>
+sudo mount /dev/mmcblk2p1 /mnt
+</file>
+Change into the ''/home'' directory and copy all contents to ''/mnt'':
+<file shell>
+cd /home
+cp -adpR * /mnt
+</file>
+Unmount the partition from ''/mnt'':
+<file shell>
+sudo umount /mnt
+</file>
+Then open the disk utility and go to the mounting settings of the partition on the SD-card.
+Set it to automatically mount on ''/home'' on boot, save and reboot the Jetson TX1.
 ==== Updating apt packages ====
@@ Line 123: / Line 189: @@
 sudo swapon ~/swapfile
+</file>
+==== Building OpenCV from source (with GStreamer support) ====
+Because [[https://opencv.org/|OpenCV]] does not support NVIDIA's GStreamer software by default, it has to be built from source with GStreamer support enabled.
+<WRAP info>
+[[https://developer.download.nvidia.com/embedded/L4T/r32_Release_v1.0/Docs/Accelerated_GStreamer_User_Guide.pdf?9N7jupgUlde8JwGYrJQO434MhxI7ZlJf8jfNYE-eI9uMBECrQldp3897ijsNYjnxBWWiY8OtUVfEKr4cLQNUyoevaUfjyXksRnT__8EmmhKVHWYbRK7-6NdQOQ8jJtev1-0IhZKyQ1rxjQh2_35qOofKmyWN8kH58nZHAQyVRax9kaD5tXY|Accelerated GStreamer User Guide]]
+</WRAP>
+To get started, install the packages that OpenCV with GStreamer support depends on:
+<file shell>
+sudo apt install -y libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev
+</file>
+Then, install [[https://numpy.org/|NumPy]] as OpenCV also depends on it:
+<file shell>
+python3.8 -m pip install --user numpy
+</file>
+After all dependencies are installed, go ahead and clone the [[https://github.com/opencv/opencv|OpenCV GitHub repository]], change into its directory and checkout the latest version branch:
+<file shell>
+git clone https://github.com/opencv/opencv.git
+cd opencv
+# General
+git checkout <version>
+# OpenCV 4.5.0
+git checkout 4.5.0
+</file>
+Before you can start building OpenCV, create a ''/build`'' directory and change into it:
+<file shell>
+mkdir build
+cd build
+</file>
+Then, use ''cmake'' to prepare the build with the correct settings:
+<file shell>
+cmake -D CMAKE_BUILD_TYPE=RELEASE \
+-D INSTALL_PYTHON_EXAMPLES=ON \
+-D INSTALL_C_EXAMPLES=OFF \
+-D PYTHON_EXECUTABLE=$(which python3.8) \
+-D BUILD_opencv_python2=OFF \
+-D CMAKE_INSTALL_PREFIX=$(python3.8 -c “import sys; print(sys.prefix)”) \
+-D PYTHON3_EXECUTABLE=$(which python3.8) \
+-D PYTHON3_INCLUDE_DIR=$(python3.8 -c “from distutils.sysconfig import get_python_inc; print(get_python_inc())”) \
+-D PYTHON3_PACKAGES_PATH=$(python3.8 -c “from site import getsitepackages; print(getsitepackages())”) \
+-D WITH_GSTREAMER=ON \
+-D BUILD_EXAMPLES=ON ..
+</file>
+It is important to check the resulting output. Check if the output contains the following important bits:
+<file shell>
+...
+GStreamer:         YES (<version>)
+...
+Python3:
+  Interpreter:     <path>
+  Libraries:       <path>
+  numpy:           <path>
+  install path:    <path>
+...
+</file>
+If everything went well, you can go ahead and build it:
+<file shell>
+sudo make -j$(nproc)
+</file>
+When the build is finished, install it:
+<file shell>
+sudo make install
 </file>
@@ Line 215: / Line 369: @@
 </file>
-Then change the directory into the local repository and clone the official [[https://github.com/ultralytics/yolov5|YOLOv5]] GitHub repository:
+Then change the directory into the local repository and clone the official [[https://github.com/ultralytics/yolov5|YOLOv5 GitHub repository]]:
 <file shell>

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