Simple example of using a MIPI-CSI(2) Camera (like the Raspberry Pi Version 2 camera) with the NVIDIA Jetson Nano Developer Kit. The camera should be installed in the MIPI-CSI Camera Connector on the carrier board. The pins on the camera ribbon should face the Jetson Nano module.
To test the camera:
$ gst-launch-1.0 nvarguscamerasrc ! 'video/x-raw(memory:NVMM),width=3820, height=2464, framerate=21/1, format=NV12' ! nvvidconv flip-method=0 ! 'video/x-raw,width=960, height=616' ! nvvidconv ! nvegltransform ! nveglglessink -e
There are three examples:
simple_camera.py is a Python script which reads from the camera and displays to a window on the screen using OpenCV:
$ python simple_camera.py
face_detect.py is a python script which reads from the camera and uses Haar Cascades to detect faces and eyes:
$ python face_detect.py
Haar Cascades is a machine learning based approach where a cascade function is trained from a lot of positive and negative images. The function is then used to detect objects in other images.
See: https://docs.opencv.org/3.3.1/d7/d8b/tutorial_py_face_detection.html
The third example is a simple C++ program which reads from the camera and displays to a window on the screen using OpenCV:
$ g++ -std=c++11 -Wall -I/usr/lib/opencv simple_camera.cpp -L/usr/lib -lopencv_core -lopencv_highgui -lopencv_videoio -o simple_camera
$ ./simple_camera
$ sudo apt-get install v4l-utils
For the Raspberry Pi V2 camera the output is (assuming the camera is /dev/video0):
$ v4l2-ctl --list-formats-ext
ioctl: VIDIOC_ENUM_FMT
Index : 0
Type : Video Capture
Pixel Format: 'RG10'
Name : 10-bit Bayer RGRG/GBGB
Size: Discrete 3280x2464
Interval: Discrete 0.048s (21.000 fps)
Size: Discrete 3280x1848
Interval: Discrete 0.036s (28.000 fps)
Size: Discrete 1920x1080
Interval: Discrete 0.033s (30.000 fps)
Size: Discrete 1280x720
Interval: Discrete 0.017s (60.000 fps)
Size: Discrete 1280x720
Interval: Discrete 0.017s (60.000 fps)
flip-method : video flip methods
flags: readable, writable, controllable
Enum "GstNvVideoFlipMethod" Default: 0, "none"
(0): none - Identity (no rotation)
(1): counterclockwise - Rotate counter-clockwise 90 degrees
(2): rotate-180 - Rotate 180 degrees
(3): clockwise - Rotate clockwise 90 degrees
(4): horizontal-flip - Flip horizontally
(5): upper-right-diagonal - Flip across upper right/lower left diagonal
(6): vertical-flip - Flip vertically
(7): upper-left-diagonal - Flip across upper left/low
If you can open the camera in GStreamer from the command line, and have issues opening the camera in Python, check the OpenCV version.
>>>cv2.__version__
v2.0 Release September, 2019
- L4T 32.2.1 (JetPack 4.2.2)
- OpenCV 3.3.1
- Tested on Jetson Nano
Initial Release (v1.0) March, 2019
- L4T 32.1.0 (JetPack 4.2)
- Tested on Jetson Nano
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