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Camarray – Arducam 1MP*2 Stereo Camera MIPI Module

Introduction

This Arducam 1MP*2 Stereo Camera MIPI Module is a stereo camera module with two synchronized monochrome global shutter OV9281 image sensors (2×1MP). It directly connects to the MIPI CSI-2 connectors of Raspberry Pi and Jetson Nano, and runs with a V4L2 camera driver on those platforms. It offers better flexibility to be integrated into your own hardware design or run with your own algorithm on embedded systems for applications like depth sensing, 3d mapping, SLAM, etc.

What is Camarray

Camarray is a series of embedded stereo cameras and multiple camera solutions from Arducam. Upgraded from Arducam Sync Stereo Camera HAT, the Camarry can disguise up to 4 synched camera modules as a single camera slot connection to embedded systems like the Raspberry Pi, Jetson nano, and Xavier NX. With Arducam camarray, your camera connectivities are no longer limited to the camera connectors on the motherboard or the carrier board. Along with Arducam-provided camera drivers, more flexibility can be added to your multi-camera applications.

NOTE

1.The Camarray HAT does not support digital pan in half resolution combine and programmable pan speed control.
2.The Camarray HAT is not a crop and a half (halving the horizontal resolution of each camera and halving the field of view) but a compressed half (halving the horizontal resolution of each camera but leaving the field of view unchanged), so it does not need to support scan mode.

Common Specs

Image Sensor

Sensor ModelOV9281
Shutter TypeGlobal Shutter
Active Pixels1280*2×800
Resolution1MP*2
Image Sensor FormatType 1/4″
Pixel Size3μm×3μm
Color Filter ArrayNone(Monochrome)
9281block diagam
OV9281 Block Diagram

Lens Assembly

InterchangeabilityYES
F/NO2.8
Focus TypeManual Focus
Focusing Range30cm to infinity (when focused to infinity)
Effective Focal Length(EFL)2.8 mm
Field of View(FoV)70° Horizontal
Lens MountM12 Lens
IR SensitivityNo IR filter (sensitive to IR light)
2311stero camera lens 3d

Camera Board

Camera Board Size105×24 mm
2311stereo camera board
Mechanical Drawing
Pin No.Pin NameTypeDescription
13V3Power3.3V power supply
2FSINInputFrame Sync Input
3STBOutputLED Strobe Output
4GNDGroundGround
53V3Power3.3V power supply
6SDAI/OSCCB serial interface data I/O
7SCLInputSCCB serial interface clock input
8GNDGroundGround

Connector & Cable

Connector InterfaceMIPI CSI-2 22-pin 2-lane
Ribbon Cable Length150mm (22pin), 150mm(15-22pin)
Mating connector typeSFW15R-2STE1LF
Pin #NameDescription
1GNDGround
2CAM_D0_NMIPI Data Lane 0 Negative
3CAM_D0_PMIPI Data Lane 0 Positive
4GNDGround
5CAM_D1_NMIPI Data Lane 1 Negative
6CAM_D1_PMIPI Data Lane 1 Positive
7GNDGround
8CAM_CK_NMIPI Clock Lane Negative
9CAM_CK_PMIPI Clock Lane Positive
10GNDGround
11CAM_D2_NMIPI Data Lane 2 Negative
12CAM_D2_PMIPI Data Lane 2 Positive
13GNDGround
14CAM_D3_NMIPI Data Lane 3 Negative
15CAM_D3_PMIPI Data Lane 3 Positive
16GNDGround
17CAM_IO0Power Enable
18CAM_IO1LED Indicator
19GNDGround
20CAM_SCLI2C SCL
21CAM_SDAI2C SDA
22CAM_3V33.3V Power Output

Driver Performance (With Official V4L2 Driver)

Video FormatGERY(8-bit)/Y10P(10-bit)
Output Interface2-lane MIPI serial output
Output Formats8/10-bit BW RAW

Frame Rate (adjustable: 5fps~80fps)

Raspberry PiJetson Nano
RAW8(GREY)[email protected]×800[email protected]×800
RAW10(Y10P)[email protected]×800[email protected]×800

Quick Start Guide

NOTE

Same operation on Xavier NX. The only difference is the driver package.

Hardware Setup​

Check the Driver

This step is to check if you have other drivers installed. If you are sure that you don’t have other drivers installed, you can skip this step and go to install Arducam V4L2 driver.

1.Driver type

There is three drivers for Jetson:​​

  • Official IMX219 driver
  • Arducam IMX477 driver
  • Arducam V4L2 driver

NOTE

These three drivers are in conflict with each other and only one of the three options is available.​

1) The Arducam IMX477 driver and Arducam V4L2 driver will automatically overwrite the other drivers and you don’t need to uninstall the other drivers.

2) If you want to use the official IMX219 driver, please type the following command to uninstall Arducam IMX477 driver or Arducam V4L2 driver.

sudo dpkg -r arducam-nvidia-l4t-kernel

3) Installing the Arducam IMX477 driver is the same process as installing the Arducam V4L2 driver, only the driver package (.deb) is different.

The product is driven by the Arducam V4L2.

2.Check your driver

Execute the following command and see if it responds. If there is no response, the corresponding driver is not installed.​​​

#Check if you have installed Official IMX219 driver

dmesg | grep imx219
Check your driver1
For example, no response, you don’t install the official IMX219 driver.

#Check if you have installed Arducam IMX477 driver

dmesg | grep imx477
Check your driver2
For example, no response, you don’t install the Arducam IMX477 driver.

#Check if you have installed Arducam V4L2 driver

dmesg | grep arducam
Check your driver3
For example, it has response, you installed Arducam V4L2 driver.Failed means you haven’t connected Arducam IMX477 camera or the connection is wrong.

Install Arducam V4L2 Driver​

Please go to this page for detailed instruction.

First Use

1.Install V4L2 python module

for Python3.x:

wget https://bootstrap.pypa.io/get-pip.py  
Install V4L2 python module1

After you type the following command and press【Enter】, it will take several minutes to finish downloading.

sudo python3 get-pip.py  
Install V4L2 python module2
Install V4L2 python module3
 sudo pip3 install v4l2 
Install V4L2 python module4

NOTE

The V4L2 of Python3.x has a known bug that requires a manual fix, and the following error occurs when you import the v4l2 module into Python3.x:

Install V4L2 python module5

You can refer to this link to fix this bug:

https://bugs.launchpad.net/python-v4l2/+bug/1664158

2.Download the demo code

git clone https://github.com/ArduCAM/MIPI_Camera.git  
Download the demo code1
Download the demo code2

3.Check whether the camera is detected

ls /dev/video0
Check whether the camera is detected1

4.Check the video format supported

v4l2-ctl --list-formats-ext
Check the video format supported nano b0263

5.Display images in real time

If accessing Jetson via remote software (e.g., MobaXterm), the following command (executed only once) is required to display the image.

export DISPLAY=:0.0

Enter program directory: 

cd MIPI_Camera/Jetson/Jetvariety/example/
Enter program directory b0263 nano

OV9281 currently supports the following commands:

#RAW8

python3 arducam_displayer.py -f GREY --width 2560 --height 800 -d 0 --fps

#RAW10

python3 arducam_displayer.py -f Y16 --width 2560 --height 800 -d 0 --fps

​GREY for RAW8 and Y16 for RAW10.

​-width and -height indicate the width and height of the input image.

–fps means to display the current frames. If you don’t want to display frames, you can remove this command parameter.

For example, execute the following command:

python3 arducam_displayer.py -f GREY --width 2560 --height 800 -d 0 --fps
RAW8 2560×800
9181 jn1

Press Ctrl+C to exit image display.

NOTE

Display resolution settings may affect the frames displayed.

Dropped frame?

Select Arducam/arducam_displayer.py, right-click on “open with Text Editor“.

dropped frame1

The circled value below represents the number of column in the display resolution. Try making the value lower if the frame is dropped.

dropped frame2

7.Adjust exposure

Open two terminals, the first one is for executing the displaying images command, the second one is for executing the adjusting exposure command.

#Adjust exposure:

v4l2-ctl -c exposure=1000

#Check exposure parameters (minimum, maximum, default)

v4l2-ctl -l
Adjust exposure b0267 nano 1

For example, execute the below command in the second terminal:

v4l2-ctl -c exposure=4000
Adjust exposure b0263 nano 1

Turning up the exposure time results in a brighter image and a lower frame rate.

8. Adjust gain

Open two terminals, the first one is for executing the displaying images command, the second one is for executing the adjusting gain command.

#Adjust gain:

v4l2-ctl -c gain=12

#Check exposure parameters (minimum, maximum, default)

v4l2-ctl -l
Adjust gain b0267 nano 1

For example, execute the below command in the second terminal:

v4l2-ctl -c gain=12
Adjust gain b0263 nano1

Turning up the gain results in a brighter image and no change in frame rate.

9.Change frame rate

Type the following command, change the value of “X” to change frame rate.

v4l2-ctl -c frame_rate=X

For example, you want to change the frame rate to 30. First, open two terminals, type the following command in the first terminal:

python3 arducam_displayer.py -f GREY --width 2560 --height 800 -d 0 --fps
change frame rate1 Nano
The last line shows the current frame rate in real time, and the RAW8 configuration defaults to 58fps.

Type the following command in the second terminal to change frame rate:

v4l2-ctl -c frame_rate=30
change frame rate2 Nano
The frame rate changes to 30fps.

Type the following command in the second terminal to view the frame rate range of the current display mode:

v4l2-ctl -l
change frame rate3 Nano
You can change the frame rate from 5fps to 80fps. If the set frame rate exceeds the maximum value, it will work according to the maximum value. The same goes for the minimum value.
IMPORTANT NOTE

Dropped frames may exist due to the platform performance.

For example, if the frame rate is set to 80 fps, the display only goes up to 58fps.

You can test the actual input frames by only receiving data without displaying the image.

The frame rate values here are not real-time and are calculated iteratively with historical values, changing slowly.

important note b0263 nano

Display the Image via VLC Media Player

NOTE

The VLC can only play images exported in RAW8 format.

1. Install VLC media player

sudo apt-get install vlc

2. Open VLC media player

VLC media player

3.Display the image

Press Ctrl+C

display1

Video device name】→ select “/dev/video0“→ click 【Play】.

display2
play3

4.Adjust exposuregain, and frame rate

Press Ctrl+E, drag the sliders at “Exposure“, “Gain” and “Frame_rate” to make adjustments under the “v4l2 control” tab.

Adjust exposure gain and frame rate b0264 nano
play5

Display the Image via Mplayer

1.Install mplayer

sudo apt-get install mplayer

2.Display images

mplayer tv:// -tv driver=v4l2:device=/dev/video0

Do not enter this command remotely, otherwise it will be stuck.

nano mplayer b0267

Or enter the following command to zoom the image. 

mplayer tv:// -tv driver=v4l2:device=/dev/video0 -zoom -x 1280 -y 400

“-x” “- y” denotes the width and height of the scaled image, and it is recommended to modify them in equal proportion.

 mplayer dual pic

What’s Next

Here are the things you can do after this quick start:

  • Check the Application Note for applications like using Arducam userland MIPI camera drivers.
  • Join the discussion in our forum.

Application Note

Using Arducam Camarray on ROS

Please refer to this page for instruction.

Using on OpenCV

Make sure you have checked the driver and installed the driver.

Download the file here.

import numpy as np
import cv2
import time
def fourcc(a, b, c, d):
    return ord(a) | (ord(b) << 8) | (ord(c) << 16) | (ord(d) << 24)

def pixelformat(string):
    if len(string) != 3 and len(string) != 4:
        msg = "{} is not a pixel format".format(string)
        raise argparse.ArgumentTypeError(msg)
    if len(string) == 3:
        return fourcc(string[0], string[1], string[2], ' ')
    else:
        return fourcc(string[0], string[1], string[2], string[3])
cap = cv2.VideoCapture(0,cv2.CAP_V4L2)
cap.set(cv2.CAP_PROP_FOURCC, pixelformat("GREY"))
cap.set(cv2.CAP_PROP_CONVERT_RGB,0)
now = time.time()
frame_num=0
while(True):
    if time.time() - now > 1:
        now = time.time()
        print(frame_num)
        frame_num=0
    else:
        frame_num = frame_num+1
    # Capture frame-by-frame
    ret, frame = cap.read()
    # Display the resulting frame
    cv2.imshow('frame',frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()

Then type the following command:

sudo python ov9281_dulcam_opencv_raw8.py

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