Openmv (III) -- get camera pictures in real time

lead

OpenMV( One )– Basic introduction and hardware architecture
OpenMV( Two )–IDE Installation and firmware download

Preface

utilize OpenMV The basis of machine vision development is to analyze the images taken by the camera , Getting the pictures taken by the camera is the first step of the long march . The columns in this series are all OV7725 Roller shutter camera . We will start from OpenMV Start with the corresponding constructor in , Analyze the source code to realize this function .

1. Constructors

OpenMV All functions related to the camera are encapsulated in sensor Module , It's easy to call .

• sensor function

  • sensor.reset()
    Initialize the camera
  • sensor.set_pixformat(pixformat)
    Set pixel format .pixformat There are three parameters ：
    • sensor.GRAYSCAL: Grayscale image , Every pixel 8 position （1 byte ）, Fast processing speed
    • sensor.RGB565: Each pixel is 16 position ,5 Bit red ,6 Bit green ,5 Bit blue , The processing speed is slower than that of gray image
    • sensor.BAYER: Small space , For capturing images only , Can't do image processing
  • sensor.set_framesize(framesize)
    Set the size of each frame , That is, image size . frequently-used framesize There are several parameters ：
    • sensor.QQVGA: 160*120
    • sensor.QVGA: 320*240
    • sensor.VGA: 640*480
    • sensor.LCD: 128*160 ( For official use LCD modular )
    • sensor.QQVGA2: 128*120 ( For official use LCD modular )
  • sensor.skip_frames([n, time])
    Number of frames ignored or waiting time after camera initialization , Wait for the camera to stabilize .
    • n: Frames ignored
    • time: Waiting time
  • sensor.snapshot()
    Take a picture with the camera , And back to imag Images

• clock function
  clock Function can be used to calculate the number of frames per second of the camera

  • clock = time.clock()
    Create a clock
  • clock.tick()
    Start tracking run time
  • clock.fps()
    Stop tracking run time , And return to the current FPS（ Frames per second ）

2. Source code analysis

Let's take the official source code of real-time camera image acquisition as an example , Analyze it , The steps of acquiring images in real time are ：
Initialize the camera --> Set the format of the collected photos --> Set the size of the collected photos --> Wait for the camera to be set --> Take an image

"""  Real time camera image acquisition routine  """
#  Import the corresponding library 
import sensor, image, time

#  Initialize the camera 
sensor.reset()

#  Set the format of the collected photos ： colour RGB
sensor.set_pixformat(sensor.RGB565)

#  Set the size of the collected photos ： 320 * 240
sensor.set_framesize(sensor.QVGA)

#  Wait for a while 2s, Wait until the camera is set 
sensor.skip_frames(time = 2000)

#  Create a clock to calculate the number of frames captured by the camera per second FPS
clock = time.clock()

#  Real time display of photos taken by the camera 
while(True):
	#  to update FPS The clock 
	clock.tick()
	#  Take a picture and return img
	img = sensor.snapshot()
	#  Serial printing FPS Parameters 
	print(clock.fps())

We connect the board to OpenMV IDE, New file , And put the above code copy go in , Click the green button in the lower left corner , We can see IDE The window on the right shows the pictures of the camera in real time ：

And then we click IDE Lower left corner “ Serial terminal ”, You can find that it is printing the camera FPS：

3. Run program offline

One thing to note is that , Our board is connected to IDE When , The running speed will be reduced , When running offline , We can make small FPS Will rise to 2 Times the speed . About how to run our written program offline ？ When our board passes USB When you plug in the computer , It's going to jump out of a U Disk interface , There are three files on it ：

among main.py Is the main function code file , Run first after power on . We can put the code directly copy To main.py in , You can realize the offline operation of the program . Of course , If you want to see the effect of displaying images in real time , We need to add one to our board LCD, And change the procedure as follows （ In the official LCD For example ）：

"""  Real time camera image acquisition routine  """
#  Import the corresponding library 
import sensor, image, lcd

#  Initialize the camera 
sensor.reset()

#  Set the format of the collected photos ： colour RGB
sensor.set_pixformat(sensor.RGB565)

#  Set the size of the collected photos ： 320 * 240
sensor.set_framesize(sensor.QVGA)

#  Wait for a while 2s, Wait until the camera is set 
sensor.skip_frames(time = 2000)

#LCD initialization 
lcd.init()

#  Real time display of photos taken by the camera 
while(True):
	 #  Take pictures and display images .
	lcd.display(sensor.snapshot())