示例#1
0
# For color tracking to work really well you should ideally be in a very, very,
# very, controlled enviroment where the lighting is constant. Additionally, if
# you want to track more than 2 colors you need to set the boundaries for them
# very narrowly. If you try to track... generally red, green, and blue then
# you will end up just tracking everything which you don't want.
red_threshold   = (  40,   60,   60,   90,   50,   70)
blue_threshold  = (   0,   20,  -10,   30,  -60,   10)
# You may need to tweak the above settings for tracking red and blue things...
# Select an area in the Framebuffer to copy the color settings.

sensor.reset() # Initialize the camera sensor.
sensor.set_pixformat(sensor.RGB565) # use RGB565.
sensor.set_framesize(sensor.QQVGA) # use QQVGA for speed.
sensor.skip_frames(10) # Let new settings take affect.
sensor.set_whitebal(False) # turn this off.
clock = time.clock() # Tracks FPS.

while(True):
    clock.tick() # Track elapsed milliseconds between snapshots().
    img = sensor.snapshot() # Take a picture and return the image.

    blobs = img.find_blobs([red_threshold, blue_threshold])
    merged_blobs = img.find_markers(blobs)
    if merged_blobs:
        for b in merged_blobs:
            # Draw a rect around the blob.
            img.draw_rectangle(b[0:4]) # rect
            img.draw_cross(b[5], b[6]) # cx, cy
            # Draw the color label. b[8] is the color label.
            img.draw_string(b[0]+2, b[1]+2, "%d" % b[8])
示例#2
0
uart.init(128000, 8, None, 1, timeout=10)

# config led
led_uart = pyb.LED(2)  # green led to show uart
led_uart.off()
led_track = pyb.LED(1)  # blue led to show find target
led_track.off()
led_failed = pyb.LED(3)  # red led to show warning
led_failed.off()

# cam sensor config
sensor.reset()  # Initialize the camera sensor.
sensor.set_pixformat(sensor.RGB565)  # use RGB565.
sensor.set_framesize(sensor.QVGA)  # use QQVGA for speed.
sensor.skip_frames(20)  # Let new settings take affect.
sensor.set_whitebal(False)  # turn this off.
clock = time.clock()  # Tracks FPS.

# set orig blob, can also call get_init_blob in Vision_contr
orig_blob = (160, 82, 500)

# pid init
pid = initPID()

while (True):
    clock.tick()  # Track elapsed milliseconds between snapshots().
    img = sensor.snapshot()  # Take a picture and return the image.
    #print(clock.fps()) # Note: Your OpenMV Cam runs about half as fast while
    # connected to your computer. The FPS should increase once disconnected.
    orient = find_speed(img, orig_blob, pid)
    if (orient):
示例#3
0
# Untitled - By: akshatha_kamath - Thu Jan 17 2019

import sensor, image, time

sensor.reset()
sensor.set_pixformat(sensor.RGB565)  #To use RGB
#sensor.set_pixformat(sensor.GRAYSCALE) #to use grayscale
sensor.set_framesize(sensor.QVGA)
sensor.set_whitebal(False)
sensor.skip_frames(time=2000)

clock = time.clock()

while (True):
    clock.tick()
    img = sensor.snapshot()
    print(clock.fps())
示例#4
0
# recorder object RGB565 frames or Grayscale frames. Use photo editing software
# like GIMP to compress and optimize the Gif before uploading it to the web.
#
# This example demonstrates using frame differencing with your OpenMV Cam to do
# motion detection. After motion is detected your OpenMV Cam will take video.

import sensor, image, time, gif, pyb, os

RED_LED_PIN = 1
BLUE_LED_PIN = 3

sensor.reset()  # Initialize the camera sensor.
sensor.set_pixformat(sensor.RGB565)  # or sensor.GRAYSCALE
sensor.set_framesize(sensor.QQVGA)  # or sensor.QVGA (or others)
sensor.skip_frames(10)  # Let new settings take affect.
sensor.set_whitebal(False)  # Turn off white balance.

if not "temp" in os.listdir(): os.mkdir("temp")  # Make a temp directory

while (True):

    pyb.LED(RED_LED_PIN).on()
    print("About to save background image...")
    sensor.skip_frames(60)  # Give the user time to get ready.

    pyb.LED(RED_LED_PIN).off()
    sensor.snapshot().save("temp/bg.bmp")
    print("Saved background image - Now detecting motion!")
    pyb.LED(BLUE_LED_PIN).on()

    diff = 10  # We'll say we detected motion after 10 frames of motion.
示例#5
0
# recording a Mjpeg file you can use VLC to play it. If you are on Ubuntu then
# the built-in video player will work too.
#
# This example demonstrates using frame differencing with your OpenMV Cam to do
# motion detection. After motion is detected your OpenMV Cam will take video.

import sensor, image, time, mjpeg, pyb, os

RED_LED_PIN = 1
BLUE_LED_PIN = 3

sensor.reset() # Initialize the camera sensor.
sensor.set_pixformat(sensor.RGB565) # or sensor.GRAYSCALE
sensor.set_framesize(sensor.QVGA) # or sensor.QQVGA (or others)
sensor.skip_frames(10) # Let new settings take affect.
sensor.set_whitebal(False) # Turn off white balance.

if not "temp" in os.listdir(): os.mkdir("temp") # Make a temp directory

while(True):

    pyb.LED(RED_LED_PIN).on()
    print("About to save background image...")
    sensor.skip_frames(60) # Give the user time to get ready.

    pyb.LED(RED_LED_PIN).off()
    sensor.snapshot().save("temp/bg.bmp")
    print("Saved background image - Now detecting motion!")
    pyb.LED(BLUE_LED_PIN).on()

    diff = 10 # We'll say we detected motion after 10 frames of motion.