def adjust_exposure(goal):
direction = 0
UP = 1
DOWN = -1
sensor.set_auto_gain(False)
img = sensor.snapshot()
stats = img.get_statistics()
adjuster = 16384
while(abs(stats.l_mean() - goal) > 10 and adjuster > 2):
if(stats.l_mean() < goal):
before_exposure_us = sensor.get_exposure_us()
sensor.set_auto_exposure(False, exposure_us = before_exposure_us + adjuster)
if (sensor.get_exposure_us() == before_exposure_us):
adjuster = 2
if(direction != UP):
adjuster = adjuster >> 1
direction = UP
else:
before_exposure_us = sensor.get_exposure_us()
sensor.set_auto_exposure(False, exposure_us = before_exposure_us - adjuster)
if (sensor.get_exposure_us() == before_exposure_us):
adjuster = 2
if(direction != DOWN or sensor.get_exposure_us() < adjuster):
adjuster = adjuster >> 1
direction = DOWN
img = sensor.snapshot()
stats = img.get_statistics()
def initialize_camera():
err_counter = 0
while 1:
try:
sensor.reset() #Reset sensor may failed, let's try some times
break
except:
err_counter = err_counter + 1
if err_counter == 20:
lcd.draw_string(lcd.width() // 2 - 100,
lcd.height() // 2 - 4,
"Error: Sensor Init Failed", lcd.WHITE,
lcd.RED)
time.sleep(0.1)
continue
sensor.set_pixformat(sensor.RGB565)
# The memory can't analyze models with resolution higher than QVGA
# So better we train the model with QVGA too
sensor.set_framesize(sensor.QVGA) #QVGA=320x240
#sensor.set_framesize(sensor.VGA) #VGA=640x480
# Optimze this settings to get best picture quality
sensor.set_auto_exposure(False, exposure_us=500)
sensor.set_auto_gain(
False
) #, gain_db=100) # must turn this off to prevent image washout...
sensor.set_auto_whitebal(True) # turn this off for color tracking
sensor.run(1)
def init(is_debug, pixformat, delay_time):
#关闭串口，防止初始化过程溢出
uart.deinit()
uart2.deinit()
sensor.reset()
sensor.set_pixformat(sensor.RGB565) #RGB565
sensor.set_framesize(sensor.QVGA) #320*240
sensor.set_gainceiling(128) #增益上限 2,4,8,16,32,64,128
sensor.set_contrast(3) #对比度 -3至3
sensor.set_brightness(0) #亮度。-3至+3
sensor.set_saturation(3) #饱和度。-3至+3
sensor.set_auto_exposure(True) #自动曝光
sensor.skip_frames(time=delay_time)
sensor.set_auto_gain(False) # 在进行颜色追踪时，必须关闭
sensor.set_auto_whitebal(False) # 在进行颜色追踪时，必须关闭
#重新打开串口
uart.init(115200, timeout_char=1000)
uart2.init(115200, timeout_char=1000)
#判断是否debug模式
global CompetitionScene
if is_debug == True:
CompetitionScene = 0
else:
CompetitionScene = 1
def sensor_config(data):
global processing
gain_db, exposure_us, r_gain_db, g_gain_db, b_gain_db = struct.unpack("<fIfff", data)
sensor.set_auto_gain(False, gain_db)
sensor.set_auto_exposure(False, exposure_us)
sensor.set_auto_whitebal(False, (r_gain_db, g_gain_db, b_gain_db))
processing = False
return struct.pack("<fIfff",gain_db, exposure_us, r_gain_db, g_gain_db, b_gain_db)
def initialize():
sensor.reset()
sensor.set_pixformat(
sensor.RGB565) # grayscale is faster (160x120 max on OpenMV-M7)
#GRAYSCALE, RGB565,BAYER
sensor.set_framesize(sensor.QVGA)
sensor.set_auto_whitebal(False)
sensor.set_auto_gain(False)
sensor.set_auto_exposure(False,
exposure_us=100) # make smaller to go faster
sensor.skip_frames(time=2000)
def setLighting(case):
sensor.set_auto_gain(False)
sensor.set_auto_exposure(False)
if case == 1:
light_mode_auto()
if case == 2:
light_mode_home()
if case == 3:
light_mode_night()
if case == 4:
light_mode_cloudy()
if case == 5:
light_mode_office()
def reset_sensor():
sensor.reset()
sensor.set_pixformat(
sensor.RGB565 if COLOR_LINE_FOLLOWING else sensor.GRAYSCALE)
sensor.set_framesize(FRAME_SIZE)
sensor.set_vflip(True)
sensor.set_hmirror(True)
sensor.set_windowing((int((sensor.width() / 2) - ((sensor.width() / 2) * FRAME_WIDE)), int(sensor.height() * (1.0 - FRAME_REGION)), \
int((sensor.width() / 2) + ((sensor.width() / 2) * FRAME_WIDE)), int(sensor.height() * FRAME_REGION) - BOTTOM_PX_TO_REMOVE))
sensor.set_auto_exposure(True)
#sensor.set_auto_exposure(False, exposure_us=500)
sensor.skip_frames(time=1400)
if COLOR_LINE_FOLLOWING: sensor.set_auto_gain(False)
if COLOR_LINE_FOLLOWING: sensor.set_auto_whitebal(False)
def init(self, robot_):
self.robot = robot_
if self.robot == self.ROBOT_O: #O_bot
self.thresholds = [
(35, 100, 26, 78, 22, 72), #Ball
(68, 100, -19, 27, 41, 81), #Yellow Goal
(20, 41, -6, 15, -55, -15)
] # Blue Goal
self.window = (59, 18, 184, 181)
elif self.robot == self.ROBOT_P2: #P2_bot
self.thresholds = [
(39, 100, 26, 78, 22, 72), #Ball
(68, 100, -19, 27, 41, 81), #Yellow Goal
(20, 41, -6, 25, -55, -15)
] # Blue Goal
self.window = (71, 4, 193, 191)
# sensor setup
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QVGA) #Resolution
sensor.set_windowing(self.window)
sensor.skip_frames(time=1000)
sensor.set_auto_exposure(False)
sensor.set_auto_whitebal(False)
# Need to let the above settings get in...
sensor.skip_frames(time=250)
# === GAIN ===
curr_gain = sensor.get_gain_db()
sensor.set_auto_gain(False, gain_db=curr_gain)
# === EXPOSURE ===
curr_exposure = sensor.get_exposure_us()
sensor.set_auto_exposure(False, exposure_us=int(curr_exposure * 0.5))
# === WHITE BAL ===
sensor.set_auto_whitebal(
False, rgb_gain_db=(-6.02073, -3.762909,
3.33901)) #Must remain false for blob tracking
sensor.set_brightness(2)
sensor.set_contrast(2)
sensor.set_saturation(2)
sensor.skip_frames(time=500)
def init(is_debug,delay_time):
uart.deinit()
sensor.reset()
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.set_framesize(sensor.QVGA)
sensor.set_contrast(3)
sensor.set_brightness(-3)
sensor.set_auto_exposure(True)
sensor.skip_frames(time = delay_time)
sensor.set_auto_whitebal(False)
uart.init(115200,timeout_char=1000)
lcd.init()
global CompetitionScene
if is_debug==True:
CompetitionScene=0
else:
CompetitionScene=1
def exposure_compensation():
"""
use P control to set the exposure time according to the clamps brightness
"""
P = 2000
pid = P_control(P)
pid.SetPoint = 40
END = 50
expo = sensor.get_exposure_us()
for i in range(1, END):
img = sensor.snapshot()
llist = []
for r in clamp_roi(roi):
lab = lab_median(img, r)
img = img.draw_rectangle(r)
llist.append(lab[0])
l_mean = int(sum(llist) / len(llist))
print("l_mean = ", l_mean)
img = img.draw_rectangle(roi)
if abs(l_mean - pid.SetPoint) <= 1:
sensor.set_saturation(2)
return
pid.update(l_mean)
output = pid.output
expo += int(output)
if expo < 10000:
sensor.set_auto_gain(0)
expo = sensor.get_exposure_us()
sensor.set_auto_exposure(0, expo)
P = P / 2
continue
if sensor.get_exposure_us() >= 120190:
sensor.set_saturation(2)
return # max exposure time
sensor.set_auto_exposure(0, expo)
sensor.skip_frames(n=60)
print("exp time", sensor.get_exposure_us())
def init(self,
gain_db=0,
shutter_us=500000,
framesize=sensor.WQXGA2,
force_reset=True,
flip=False):
if self.simulate:
self.shutter = shutter_us
self.gain = gain_db
self.snap_started = False
return
if force_reset or self.has_error or self.gain != gain_db or self.shutter != shutter_us or self.framesize != framesize or self.flip != flip:
sensor.reset()
sensor.set_pixformat(self.pixfmt)
sensor.set_framesize(framesize)
if flip: # upside down camera
sensor.set_vflip(True)
sensor.set_hmirror(True)
self.flip = flip
self.framesize = framesize
if shutter_us < 0:
sensor.set_auto_exposure(True)
else:
if shutter_us > 500000:
sensor.__write_reg(0x3037, 0x08) # slow down PLL
if shutter_us > 1000000:
pyb.delay(100)
sensor.__write_reg(0x3037, 0x18) # slow down PLL
if shutter_us > 1500000:
pyb.delay(100)
sensor.__write_reg(0x3036, 80) # slow down PLL
# warning: doesn't work well, might crash
pyb.delay(200)
sensor.set_auto_exposure(False, shutter_us)
self.shutter = shutter_us
if gain_db < 0:
sensor.set_auto_gain(True)
else:
sensor.set_auto_gain(False, gain_db)
self.gain = gain_db
self.wait_init = 2
self.width = sensor.width()
self.height = sensor.height()
def init(is_debug, pixformat, delay_time):
uart.deinit()
sensor.reset()
if pixformat == "GRAY":
sensor.set_pixformat(sensor.GRAYSCALE)
elif pixformat == "RGB":
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QQVGA)
sensor.set_gainceiling(128)
sensor.set_contrast(3)
sensor.set_brightness(0)
sensor.set_saturation(3)
sensor.set_auto_exposure(True)
sensor.skip_frames(time=delay_time)
sensor.set_auto_gain(False)
sensor.set_auto_whitebal(False)
uart.init(115200, timeout_char=1000)
global CompetitionScene
if is_debug == True:
CompetitionScene = 0
else:
CompetitionScene = 1
def adjust_exposure(self, goal):
"""Adjust the exposure of the sensor until the average L (in LAB)
value reaches the desired goal."""
self.logger.debug("goal=", goal)
direction = 0
UP = 1
DOWN = -1
sensor.set_auto_gain(False)
img = sensor.snapshot() if self.snapshot == None else self.snapshot
stats = img.get_statistics()
adjuster = self.adjuster
while (abs(stats.l_mean() - goal) > 10 and adjuster > 2):
self.logger.debug("adjuster=", adjuster,
", sensor.get_exposure_us()=",
sensor.get_exposure_us())
if (stats.l_mean() < goal):
before_exposure_us = sensor.get_exposure_us()
sensor.set_auto_exposure(False,
exposure_us=before_exposure_us +
adjuster)
if (sensor.get_exposure_us() == before_exposure_us):
adjuster = 2
if (direction != UP):
adjuster = adjuster >> 1
direction = UP
else:
before_exposure_us = sensor.get_exposure_us()
sensor.set_auto_exposure(False,
exposure_us=before_exposure_us -
adjuster)
if (sensor.get_exposure_us() == before_exposure_us):
adjuster = 2
if (direction != DOWN or sensor.get_exposure_us() < adjuster):
adjuster = adjuster >> 1
direction = DOWN
img = self.take()
stats = img.get_statistics()
self.adjuster = 16384
def LENetTest(loopCnt=600, isFull=False, barLen=80):
sensor.reset() # Reset and initialize the sensor.
sensor.set_contrast(3)
sensor.set_pixformat(
sensor.GRAYSCALE) # Set pixel format to RGB565 (or GRAYSCALE)
sensor.set_framesize(sensor.CIF) # Set frame size to QVGA (320x240)
sensor.set_windowing((96, 96)) # Set 128x128 window.
sensor.set_auto_gain(True)
sensor.set_auto_whitebal(False)
sensor.set_auto_exposure(False)
sensor.skip_frames(time=400) # Wait for settings take effect.
net = nn.load('/lenet.network')
labels = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9']
clock = time.clock()
tAvg = 0.0
startTick = time.ticks()
while (True):
if time.ticks() - startTick > loopCnt:
break
clock.tick()
img = sensor.snapshot()
t0 = time.ticks()
tmp_img = img.copy().binary([(120, 255)], invert=True)
lst = net.search(tmp_img, threshold=0.8, min_scale=1.0, scale_mul=0.8, \
x_overlap=-1, y_overlap=-1, contrast_threshold=0.5, softmax=False)
t1 = time.ticks() - t0
tAvg = tAvg * 0.9 + t1 * 0.1
img.draw_string(4, 8, 'LENET', color=(0, 0, 0))
lnLen = (barLen * (loopCnt - (time.ticks() - startTick))) // loopCnt
DrawPgsBar(img, barLen, loopCnt, startTick)
for obj in lst:
print('Detected %s - Confidence %f%%' %
(labels[obj.index()], obj.value()))
img.draw_rectangle(obj.rect(), color=(255, 255, 255))
img.draw_string(4, 4, labels[obj.index()])
print('algo time cost : %.2f ms' % (tAvg))
sensor_size = sensor.VGA
sensor.set_pixformat(sensor_format)
sensor.set_framesize(sensor_size)
if img_width != sensor.width() or img_height != sensor.height():
sensor.set_windowing((int((sensor.width()-img_width)/2),int((sensor.height()-img_height)/2),img_width,img_height))
sensor.skip_frames(time = 2000)
# get the current the current exposure and gains and send them to the remote cam so that the
# 2 cams have the same image settings
sensor.snapshot()
gain_db = sensor.get_gain_db()
exposure_us = sensor.get_exposure_us()
print("exposure is " + str(exposure_us))
rgb_gain_db = sensor.get_rgb_gain_db()
sensor.set_auto_gain(False, gain_db)
sensor.set_auto_exposure(False, exposure_us)
sensor.set_auto_whitebal(False, rgb_gain_db)
result = interface.call("sensor_config", struct.pack("<fIfff", gain_db, exposure_us,
rgb_gain_db[0], rgb_gain_db[1], rgb_gain_db[2]))
if result is not None:
gain_db, exposure_us, r_gain_db, g_gain_db, b_gain_db = struct.unpack("<fIfff", result)
print("ret is " + str(exposure_us))
else:
# apparently something went wrong with the remote cam
# stopping there in this case
print("The remote cam did not respond correcly. Stopping here...")
exit(1)
clock = time.clock()
idx = 0
from pyb import LED
threshold_index = 4 # 0 for red, 1 for green, 2 for blue
# Color Tracking Thresholds (L Min, L Max, A Min, A Max, B Min, B Max)
# The below thresholds track in general red/green/blue things. You may wish to tune them...
thresholds = [(50, 100, -8, 26, -4, 18)]
sensor.reset()
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.set_framesize(sensor.VGA)
sensor.set_windowing((500, 440))
sensor.skip_frames(time = 2000)
sensor.set_auto_gain(False) # must be turned off for color tracking
sensor.set_auto_whitebal(False) # must be turned off for color tracking
sensor.set_auto_exposure(False,1200)
clock = time.clock()
a=0
led1=LED(1)
led2=LED(2)
uart = UART(3,115200) #串口3，波特率115200
# Only blobs that with more pixels than "pixel_threshold" and more area than "area_threshold" are
# returned by "find_blobs" below. Change "pixels_threshold" and "area_threshold" if you change the
# camera resolution. "merge=True" merges all overlapping blobs in the image.
def send_data_packet(x, y):
temp = struct.pack(">bHHb", #格式为俩个字符俩个整型
0xAA, #帧头1
int(x), # up sample by 4 #数据1
int(y), # up sample by 4 #数据2
0xAE) #帧头2
uart.write(temp)
if blob.pixels() > max_size:
max_blob=blob
max_size = blob.pixels()
return max_blob
sensor.reset()
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.set_framesize(sensor.QVGA)
sensor.set_windowing((320, 240))
sensor.skip_frames(time = 1000)
sensor.set_auto_gain(False)
sensor.set_auto_whitebal(False)
sensor.set_brightness(0)
clock = time.clock()
exposure_time = sensor.get_exposure_us()
sensor.set_auto_exposure(False, \
exposure_us = int(exposure_time * EXPOSURE_TIME_SCALE))
xPositionNow = 0
yPositionNow = 0
xPositionLast = 0
yPositionLast = 0
imageSize = 128
while(True):
clock.tick()
img = sensor.snapshot()
blobs = img.find_blobs([thresholds], roi=roi1, pixels_threshold=5, area_threshold=5, merge=True)
for b in blobs:
max_blob=find_max(blobs)
img.draw_rectangle(max_blob.rect())
# This example shows off how to find circles in the image using the Hough # Transform. https://en.wikipedia.org/wiki/Circle_Hough_Transform # # Note that the find_circles() method will only find circles which are completely # inside of the image. Circles which go outside of the image/roi are ignored... import sensor, image, time, pyb import frc_can from pyb import UART from math import sqrt sensor.reset() sensor.set_pixformat(sensor.RGB565) # grayscale is faster sensor.set_framesize(sensor.QVGA) sensor.skip_frames(time=2500) sensor.set_auto_exposure(False) sensor.set_auto_gain(False) sensor.set_auto_whitebal(False) pyb.LED(1).off() pyb.LED(3).off() original_exposure = sensor.get_exposure_us() sensor.set_auto_exposure(False, int(.50 * original_exposure)) clock = time.clock() # Histogram baseline for yellow power-cell #hist = [39, 90, -40, 29, 44, 95] hist = [37, 98, -68, 21, 34, 99]
# ||| UART SETUP ||| uart = UART(3, 9600, timeout_char = 1000) # ||| SENSOR SETUP ||| sensor.reset() sensor.set_pixformat(sensor.RGB565) sensor.set_framesize(sensor.QVGA) sensor.skip_frames(time = 1000) # ||| GAIN ||| curr_gain = sensor.get_gain_db() sensor.set_auto_gain(False, gain_db=curr_gain) # ||| EXPOSURE ||| curr_exposure = sensor.get_exposure_us() sensor.set_auto_exposure(False, exposure_us = int(curr_exposure)) # ||| WHITE BAL ||| sensor.set_auto_whitebal(False, rgb_gain_db=curr_wbal) # ||| SET VALUES & WINDOWING ||| sensor.set_windowing(vwin_val) sensor.set_saturation(3) sensor.set_brightness(3) #Change to -3 sensor.set_contrast(3) # ||| INDICATOR LED ||| LED(1).on() time.sleep(100) LED(1).off()
SEARCHING_PIXEL_THRESHOLD = SEARCHING_AREA_THRESHOLD
TRACKING_RESOLUTION = sensor.QQVGA
TRACKING_AREA_THRESHOLD = 256
TRACKING_PIXEL_THRESHOLD = TRACKING_AREA_THRESHOLD
TRACKING_EDGE_TOLERANCE = 0.05 # Blob can move 5% away from the center.
sensor.reset() # Reset and initialize the sensor.
sensor.set_pixformat(sensor.GRAYSCALE) # Set pixel format to GRAYSCALE
sensor.set_framesize(SEARCHING_RESOLUTION)
sensor.skip_frames(time = 1000) # Wait for settings take effect.
clock = time.clock() # Create a clock object to track the FPS.
sensor.set_auto_gain(False) # Turn off as it will oscillate.
sensor.set_auto_exposure(False, exposure_us=EXPOSURE_MICROSECONDS)
sensor.skip_frames(time = 1000)
# sensor_w and sensor_h are the image sensor raw pixels w/h (x/y are 0 initially).
x, y, sensor_w, sensor_h = sensor.ioctl(sensor.IOCTL_GET_READOUT_WINDOW)
while(True):
clock.tick()
img = sensor.snapshot()
# We need to find an IR object to track - it's likely to be really bright.
blobs = img.find_blobs(TRACKING_THRESHOLDS,
area_threshold=SEARCHING_AREA_THRESHOLD,
pixels_threshold=SEARCHING_PIXEL_THRESHOLD)
if len(blobs):
import sensor, image, time
from pyb import *
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(10)
sensor.set_auto_exposure(False)
sensor.set_auto_whitebal(False, (-6.317097, -6.02073, -6.774588))
sensor.set_brightness(-3)
uart = UART(3, 115200, timeout_char=1000)
red_threshold = (51, 9, 15, 88, -16, 66) #(82, 18, 40, 90, 3, 51)
yellow_threshold = (82, 13, -29, 55, 26, 68) #(82, 36, 2, 53, 29, 71)
blue_threshold = (68, 24, -34, 9, -59, 3) #(64, 19, -7, 28, -60, -26)
area = 3500
time_out = 120 * 1000
servo1 = Servo(1)
servo2 = Servo(2)
def send_finish_flag():
uart.writechar(0xFF)
delay(1)
uart.writechar(0x46)
delay(1)
uart.writechar(0x23)
delay(1)
# English:
labels = ["9", "8", "7", "10", "ACE", "JACK", "QUEEN", "KING"]
# German:
#labels=["9","8","7","10","Ass","Bube","Dame","Koenig"]
sensor.reset()
# initialize color images
sensor.set_pixformat(sensor.RGB565)
# The memory can't analyze models with resolution higher than QVGA
# and the model is trained with QVGA too
sensor.set_framesize(sensor.QVGA) #QVGA=320x240
# It is a good idea to tune the camera exposure
# and disable the auto-gain function.
# Please tune this settings to get best picture quality
sensor.set_auto_exposure(False, exposure_us=125) # 500
sensor.set_auto_gain(False) # must turn this off to prevent image washout...
sensor.set_auto_whitebal(True) # turn this off for color tracking
# only use a squared window
sensor.set_windowing((224, 224))
sensor.run(1)
lcd.clear()
while (True):
# get an image snapshot
img = sensor.snapshot()
# let the model find something...
fmap = kpu.forward(task, img)
plist = fmap[:]
def __init__(self,
draw_stats=False,
draw_lines=False,
draw_lap_times=False,
draw_timer=False,
draw_line_stats=False,
save_first_frame=False,
flip_text=False,
mirror_text=False,
rotate_text=0,
flip_travel_direction=False):
# Setup hardware
self.red_led = pyb.LED(1)
self.green_led = pyb.LED(2)
self.blue_led = pyb.LED(3)
self.infra_led = pyb.LED(4)
self.usb_serial = pyb.USB_VCP() # Serial Port
# Auto gain and white balance settings
#sensor.set_auto_gain(False) # must be turned off for color tracking
#sensor.set_auto_whitebal(False) # must be turned off for color tracking
# Set line finding parameters
self.min_degree = 45
self.max_degree = 135
self.threshold = 1000
self.theta_margin = 25 # Max angle of lines to be merged and considered one
self.rho_margin = 25 # Max spacing between lines along the rho axis
self.x_stride = 2
self.y_stride = 8
# Configure IO pins for signaling
self.action_pin = pyb.Pin('P7', pyb.Pin.OUT_OD, pyb.Pin.PULL_NONE)
self.page_pin = pyb.Pin('P8', pyb.Pin.OUT_OD, pyb.Pin.PULL_NONE)
self.lap_pin = pyb.Pin('P9', pyb.Pin.OUT_OD, pyb.Pin.PULL_NONE)
# Configure the imaging sensor
sensor.reset() # Initialize the sensor
sensor.set_pixformat(sensor.GRAYSCALE) # Set pixel format
sensor.set_framesize(sensor.QQQVGA) # Set frame size
sensor.set_auto_exposure(True,
exposure_us=5000) # Smaller means faster
sensor.skip_frames(time=2000) # Wait for settings take effect
# Delta value in pixels for x/y for tracking new lines
self.line_id_max_delta = 40
# Max frames without a line before line history is cleared
self.frames_before_line_purge = 200 # should be inverse -> sensor.get_exposure_us / 25
# Default travel direction is from top to bottom
self.flip_travel_direction = flip_travel_direction
# Configure clock for tracking FPS
self.clock = time.clock()
# Configure the lcd screen.
lcd.init()
# Initialize image buffer
self.img = sensor.snapshot()
#Allocate memory for exceptions in async/timer driven code
micropython.alloc_emergency_exception_buf(100) # Debugging only
# Allocation for interrupt callbacks
self._timer = pyb.Timer(13)
self._timer.init(freq=10)
self._timer.callback(self._cb)
self._render_ref = self.render
self._pin_reset_ref = self.pin_reset
# Scale, sensor to screen
self.scale = 1.5
# Show performance/debug statistics/info
self.draw_stats = draw_stats
self.draw_lines = draw_lines
self.draw_lap_times = draw_lap_times
self.draw_timer = draw_timer
self.draw_line_stats = draw_line_stats
self.line_draw_color = (255, 0, 0)
self._fps = None
self._known_lines = []
self._lap_timestamp = None
self.lap_timestamps = []
self._lap_notification_timestamp = None
self.lap_notification_timeout = 5000
self.save_first_frame = save_first_frame
self.flip_text = flip_text
self.mirror_text = mirror_text
self.rotate_text = rotate_text
# High FPS Example
#
# This example shows off how to make the frame rate of the global shutter camera extremely
# high. To do so you need to set the resolution to a low value such that pixel binning is
# activated on the camera and then reduce the maximum exposure time.
#
# When the resolution is 320x240 or less the camera reads out pixels 2x faster. When the
# resolution is 160x120 or less the camera reads out pixels 4x faster. This happens due
# to pixel binning which is automatically activated for you to increase the readout speed.
#
# While the readout speed may increase the camera must still expose the image for the request
# time so you will not get the maximum readout speed unless you reduce the exposure time too.
# This results in a dark image however so YOU NEED A LOT of lighting for high FPS.
import sensor, image, time
sensor.reset() # Reset and initialize the sensor.
sensor.set_pixformat(sensor.GRAYSCALE) # Set pixel format to GRAYSCALE
sensor.set_framesize(sensor.QQVGA) # Set frame size to QQVGA (160x120) - make smaller to go faster
sensor.skip_frames(time = 2000) # Wait for settings take effect.
clock = time.clock() # Create a clock object to track the FPS.
sensor.set_auto_exposure(True, exposure_us=5000) # make smaller to go faster
while(True):
clock.tick() # Update the FPS clock.
img = sensor.snapshot() # Take a picture and return the image.
print(clock.fps()) # Note: OpenMV Cam runs about half as fast when connected
# to the IDE. The FPS should increase once disconnected.
def set_b_range(self, b_range):
self.b_min = 0
self.b_max = b_range
def get_thresholds(self, l_count, a_count, b_count):
tmp = [(self.l_min + l_count, self.l_max + l_count, \
self.a_min + a_count, self.a_max + a_count, \
self.b_min + b_count, self.b_max + b_count)]
return tmp
img = sensor.snapshot()
while (img.get_statistics().l_mean() < 60):
sensor.set_auto_exposure(False, exposure_us=sensor.get_exposure_us() + 200)
img = sensor.snapshot()
thresholdHolder = ThresholdHolder()
list_of_thresholds = []
print("looping")
l_min = 100
l_max = 0
a_min = 120
a_max = -120
b_min = 120
b_max = -120
#(23, 76, -23, 43, -76, 15)
import sensor, image, time, math, pyb
from pyb import LED
from pyb import USB_VCP
blue_led = LED(3)
green_led = LED(2)
sensor.reset()
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.set_framesize(sensor.VGA)
sensor.set_windowing((640, 80))
sensor.skip_frames(30)
sensor.set_auto_gain(True)
sensor.set_auto_whitebal(True)
sensor.set_auto_exposure(True)
sensor.set_vflip(True)
sensor.set_hmirror(True)
clock = time.clock()
temp = ''
result = ''
usb = USB_VCP()
def barcode_name(code):
if (code.type() == image.EAN2):
return "EAN2"
if (code.type() == image.EAN5):
return "EAN5"
if (code.type() == image.EAN8):
return "EAN8"
if (code.type() == image.UPCE):
return "UPCE"
def biggest(a, b, c):
# 先比较a和b
if a > b:
maxnum = a
else:
maxnum = b
# 再比较maxnum和c
if c > maxnum:
maxnum = c
return maxnum
find_initpoint() #自定义函数 确定电机回到原点
sensor.set_auto_exposure(False, 600) #设置曝光
sensor.skip_frames(time=2000)
sensor.set_auto_gain(False) # must be turned off for color tracking
sensor.set_auto_whitebal(False) # must be turned off for color tracking
sensor.set_saturation(1) #设置饱和度
clock = time.clock()
while (True):
clock.tick()
img = sensor.snapshot()
color_value = p_in_7.value(
) # get value, 0 or 1#读入p_in_7引脚的值 抽签确定的球的颜色 0为黑 1为白
judge_value = p_in_8.value() # get value, 0 or 1#读入p_in_8引脚的值 判断是否开始分球
Ready_value = p_in_9.value() # get value, 0 or 1#读入p_in_9引脚的值 射球是否就绪
# CIFAR is a convolutional nueral network designed to classify it's field of view into several
# different object types and works on RGB video data.
#
# In this example we slide the LeNet detector window over the image and get a list of activations
# where there might be an object. Note that use a CNN with a sliding window is extremely compute
# expensive so for an exhaustive search do not expect the CNN to be real-time.
import sensor, image, time, os, nn
sensor.reset() # Reset and initialize the sensor.
sensor.set_pixformat(sensor.RGB565) # Set pixel format to RGB565 (or GRAYSCALE)
sensor.set_framesize(sensor.QVGA) # Set frame size to QVGA (320x240)
sensor.set_windowing((128, 128)) # Set 128x128 window.
sensor.skip_frames(time=750) # Don't let autogain run very long.
sensor.set_auto_gain(False) # Turn off autogain.
sensor.set_auto_exposure(False) # Turn off whitebalance.
# Load cifar10 network (You can get the network from OpenMV IDE).
net = nn.load('/cifar10.network')
# Faster, smaller and less accurate.
# net = nn.load('/cifar10_fast.network')
labels = ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']
clock = time.clock()
while(True):
clock.tick()
img = sensor.snapshot()
# net.search() will search an roi in the image for the network (or the whole image if the roi is not
# specified). At each location to look in the image if one of the classifier outputs is larger than
# You have to turn automatic gain control and automatic white blance off
# otherwise they will change the image gains to undo any exposure settings
# that you put in place...
sensor.set_auto_gain(False)
sensor.set_auto_whitebal(False)
# Need to let the above settings get in...
sensor.skip_frames(time = 500)
current_exposure_time_in_microseconds = sensor.get_exposure_us()
print("Current Exposure == %d" % current_exposure_time_in_microseconds)
# Auto exposure control (AEC) is enabled by default. Calling the below function
# disables sensor auto exposure control. The additionally "exposure_us"
# argument then overrides the auto exposure value after AEC is disabled.
sensor.set_auto_exposure(False, \
exposure_us = int(current_exposure_time_in_microseconds * EXPOSURE_TIME_SCALE))
print("New exposure == %d" % sensor.get_exposure_us())
# sensor.get_exposure_us() returns the exact camera sensor exposure time
# in microseconds. However, this may be a different number than what was
# commanded because the sensor code converts the exposure time in microseconds
# to a row/pixel/clock time which doesn't perfectly match with microseconds...
# If you want to turn auto exposure back on do: sensor.set_auto_exposure(True)
# Note that the camera sensor will then change the exposure time as it likes.
# Doing: sensor.set_auto_exposure(False)
# Just disables the exposure value update but does not change the exposure
# value the camera sensor determined was good.
while(True):
# Selective Search Example
import sensor, image, time
from random import randint
sensor.reset() # Reset and initialize the sensor.
sensor.set_pixformat(sensor.RGB565) # Set pixel format to RGB565 (or GRAYSCALE)
sensor.set_framesize(sensor.QVGA) # Set frame size to QVGA (320x240)
sensor.skip_frames(time = 2000) # Wait for settings take effect.
sensor.set_auto_gain(False)
sensor.set_auto_exposure(False, exposure_us=10000)
clock = time.clock() # Create a clock object to track the FPS.
while(True):
clock.tick() # Update the FPS clock.
img = sensor.snapshot() # Take a picture and return the image.
rois = img.selective_search(threshold = 200, size = 20, a1=0.5, a2=1.0, a3=1.0)
for r in rois:
img.draw_rectangle(r, color=(255, 0, 0))
#img.draw_rectangle(r, color=(randint(100, 255), randint(100, 255), randint(100, 255)))
print(clock.fps())
import sensor, time, image, pyb
from pyb import Pin
# 相机参数设置
sensor.reset() # 初始化相机
sensor.set_pixformat(sensor.GRAYSCALE) # 设置灰度像素模式，每个像素8bit
sensor.set_framesize(sensor.B128X128) # 设置图像大小，用于帧差异
sensor.set_windowing((92,112)) # 设置窗口ROI
sensor.skip_frames(10) # 跳过一些帧，等待感光元件变稳定
# 降低环境因素的影响
sensor.set_auto_gain(True) # 开启自动增益
sensor.set_auto_whitebal(True) # 开启自动白平衡
sensor.set_auto_exposure(True) # 开启自动曝光
# 定义IO口
# 输入引脚
p_in0 = Pin('P0', Pin.IN, Pin.PULL_UP) # 设置P0为“按键1”输入引脚，并开启上拉电阻
p_in1 = Pin('P1', Pin.IN, Pin.PULL_UP) # 设置P1为“按键2”输入引脚，并开启上拉电阻
p_in2 = Pin('P2', Pin.IN, Pin.PULL_UP) # 设置P2为“按键3”输入引脚，并开启上拉电阻
p_in3 = Pin('P3', Pin.IN, Pin.PULL_UP) # 设置P3为“按键4”输入引脚，并开启上拉电阻
# 输出引脚
RED_LED_PIN = 1 # 红色LED输出引脚
GREEN_LED_PIN = 2 # 绿色LED输出引脚
BLUE_LED_PIN = 3 # 蓝色LED输出引脚
p_out0 = Pin('P4', Pin.OUT_PP) # 设置p_out为输出引脚
p_out1 = Pin('P5', Pin.OUT_PP) # 设置p_out为输出引脚
p_out2 = Pin('P6', Pin.OUT_PP) # 设置p_out为输出引脚
p_out3 = Pin('P7', Pin.OUT_PP) # 设置p_out为输出引脚
clock = time.clock() # Create a clock object to track the FPS.
# You have to turn automatic gain control and automatic white blance off
# otherwise they will change the image gains to undo any exposure settings
# that you put in place...
sensor.set_auto_gain(False)
# Need to let the above settings get in...
sensor.skip_frames(time=500)
current_exposure_time_in_microseconds = sensor.get_exposure_us()
print("Current Exposure == %d" % current_exposure_time_in_microseconds)
# Auto exposure control (AEC) is enabled by default. Calling the below function
# disables sensor auto exposure control. The additionally "exposure_us"
# argument then overrides the auto exposure value after AEC is disabled.
sensor.set_auto_exposure(False, \
exposure_us = int(current_exposure_time_in_microseconds * EXPOSURE_TIME_SCALE))
print("New exposure == %d" % sensor.get_exposure_us())
# sensor.get_exposure_us() returns the exact camera sensor exposure time
# in microseconds. However, this may be a different number than what was
# commanded because the sensor code converts the exposure time in microseconds
# to a row/pixel/clock time which doesn't perfectly match with microseconds...
# If you want to turn auto exposure back on do: sensor.set_auto_exposure(True)
# Note that the camera sensor will then change the exposure time as it likes.
# Doing: sensor.set_auto_exposure(False)
# Just disables the exposure value update but does not change the exposure
# value the camera sensor determined was good.
while (True):
GAIN_SCALE = 1.0
sensor.reset() # Reset and initialize the sensor.
sensor.set_pixformat(sensor.RGB565) # Set pixel format to RGB565 (or GRAYSCALE)
sensor.set_framesize(sensor.QVGA) # Set frame size to QVGA (320x240)
# Print out the initial gain for comparison.
print("Initial gain == %f db" % sensor.get_gain_db())
sensor.skip_frames(time = 2000) # Wait for settings take effect.
clock = time.clock() # Create a clock object to track the FPS.
# You have to turn automatic exposure control and automatic white blance off
# otherwise they will change the image exposure to undo any gain settings
# that you put in place...
sensor.set_auto_exposure(False)
sensor.set_auto_whitebal(False)
# Need to let the above settings get in...
sensor.skip_frames(time = 500)
current_gain_in_decibels = sensor.get_gain_db()
print("Current Gain == %f db" % current_gain_in_decibels)
# Auto gain control (AGC) is enabled by default. Calling the below function
# disables sensor auto gain control. The additionally "gain_db"
# argument then overrides the auto gain value after AGC is disabled.
sensor.set_auto_gain(False, \
gain_db = current_gain_in_decibels * GAIN_SCALE)
print("New gain == %f db" % sensor.get_gain_db())
# sensor.get_gain_db() returns the exact camera sensor gain decibels.
