def get_gain(self):
"""
The gain measured in gain-units. The gain range is 16 to 63
(unity gain = 16 gain-units; multiply by 1/16 to get the true
gain).
"""
return sensor.__read_reg(0xBA)
def OV5640AF_Init():
result = sensor.__read_reg(0x3029)
print('FW_STATUS: %X' % result)
if result == 0x00:
AFConfigFile = open('AF_REG.txt', 'r')
addr = 0x8000
sensor.__write_reg(0x3000, 0x20)
while True:
AFConfig = AFConfigFile.readline()
if not AFConfig:
break
str_new = AFConfig.replace(' ', '')
str_new = str_new.replace(',', '')
str_new = str_new.replace('0x', '')
str_new = str_new[:-8]
len_s = int(len(str_new) / 2)
list_nums = []
i = 0
for i in range(0, len_s):
chs = str_new[2 * i:2 * i + 2]
num = int(chs, 16)
list_nums.append(num)
bys = bytes(list_nums)
# print(bys)
for char in bys:
sensor.__write_reg(addr, char)
addr += 1
sensor.__write_reg(0x3022, 0x00)
sensor.__write_reg(0x3023, 0x00)
sensor.__write_reg(0x3024, 0x00)
sensor.__write_reg(0x3025, 0x00)
sensor.__write_reg(0x3026, 0x00)
sensor.__write_reg(0x3027, 0x00)
sensor.__write_reg(0x3028, 0x00)
sensor.__write_reg(0x3029, 0x7f)
sensor.__write_reg(0x3000, 0x00)
while (True):
result = sensor.__read_reg(0x3029)
print('FW_STATUS: %X' % result)
if result != 0x7F:
break
sleep(500)
# In Memory Shadow Removal w/ Frame Differencing Example
#
# Note: You will need an SD card to run this example.
#
# This example demonstrates using frame differencing with your OpenMV Cam using
# shadow removal to help reduce the affects of cast shadows in your scene.
import sensor, image, pyb, os, time
TRIGGER_THRESHOLD = 5
sensor.reset() # Initialize the camera sensor.
sensor.set_pixformat(sensor.RGB565) # or sensor.GRAYSCALE
sensor.set_framesize(sensor.QQVGA) # or sensor.QVGA (or others)
if sensor.get_id() == sensor.OV7725: # Reduce sensor PLL from 6x to 4x.
sensor.__write_reg(0x0D, (sensor.__read_reg(0x0D) & 0x3F) | 0x40)
sensor.skip_frames(time=2000) # Let new settings take affect.
sensor.set_auto_whitebal(False) # Turn off white balance.
sensor.set_auto_gain(False) # Turn this off too.
clock = time.clock() # Tracks FPS.
if not "temp" in os.listdir(): os.mkdir("temp") # Make a temp directory
print("About to save background image...")
sensor.skip_frames(time=2000) # Give the user time to get ready.
sensor.snapshot().save("temp/bg.bmp")
print("Saved background image - Now frame differencing!")
while (True):
clock.tick() # Track elapsed milliseconds between snapshots().
img = sensor.snapshot() # Take a picture and return the image.
# Note: Actual FPS is higher, streaming the FB makes it slower.
print(clock.fps())
if KEY.value() == 1:
while KEY.value() == 1:
blue_led.on()
sleep(0.05)
blue_led.off()
sleep(0.05)
keycount += 1
if keycount > 3:
# 长按K1,释放对焦马达,镜头回到初始状态
sensor.__write_reg(0x3022, 0x08)
while KEY.value() == 1:
blue_led.on()
sleep(0.1)
blue_led.off()
sleep(0.1)
if keycount <= 3:
sensor.__write_reg(0x3022, 0x03)
# 判断对焦是否完成
if keycount != 0:
# 读取对焦状态
result = sensor.__read_reg(0x3029)
print('FW_STATUS: %X' % result)
if result == 0x10 or result == 0x70:
# 对焦完成,暂停对焦过程,使镜头将保持在此对焦位置
sensor.__write_reg(0x3022, 0x06)
keycount = 0
def get_exposure_lines(self):
"""
The exposure measured in row-time from 1 to 2047.
"""
return sensor.__read_reg(0xBB)
sensor.__write_reg(0x13, 0b00000000) # disable automated gain
gain_db = sensor.get_gain_db()
exposure_us = sensor.get_exposure_us()
rgb_gain_db = sensor.get_rgb_gain_db()
print("gain_db is " + str(gain_db))
print("exposure is " + str(exposure_us))
print("rgb_gain_db is " + str(rgb_gain_db))
reg_list = [
0x00, 0x01, 0x02, 0x03, 0x08, 0x10, 0x2d, 0x2e, 0x2f, 0x33, 0x34, 0x35,
0x36, 0x37, 0x37, 0x38
]
sensor_config = []
for i in range(0, 16):
sensor_config += [sensor.__read_reg(reg_list[i])]
result = interface.call("sensor_config", struct.pack("<16I", *sensor_config))
if result is not None:
remote_gain_db, remote_exposure_us, remote_r_gain_db, remote_g_gain_db, remote_b_gain_db = struct.unpack(
"<fIfff", result)
print("sending back: " + str(remote_gain_db) + ", " +
str(remote_exposure_us) + ", " + str(remote_r_gain_db) + ", " +
str(remote_g_gain_db) + ", " + str(remote_b_gain_db))
if remote_exposure_us != exposure_us:
print("exposure_us is " + str(exposure_us) + " but we got " +
str(remote_exposure_us))
exit(1)
if remote_gain_db != gain_db:
print("gain_db is " + str(gain_db) + " but we got " +
# Untitled - By: aakoch - Sun Apr 22 2018
import sensor, image, time
sensor.reset()
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QQVGA)
sensor.skip_frames(time=200)
sensor.__write_reg(0xC, sensor.__read_reg(0x0C) | 0xC0) # flips and mirrors
sensor.skip_frames(time=200)
#sensor.__write_reg(0xC, sensor.__read_reg(0x0C) | 0x1) # color bars
#sensor.skip_frames(time = 200)
#sensor.__write_reg(0xC, sensor.__read_reg(0x0C) & 0xFE) # color bars off
#sensor.skip_frames(time = 2000)
#sensor.__write_reg(0xE, sensor.__read_reg(0x0E) | 0x80) # "night mode"? - I can't tell a differenct
#sensor.skip_frames(time = 2000)
#sensor.__write_reg(0xE, sensor.__read_reg(0x0E) & 0x7F) # "night mode" off?
#sensor.skip_frames(time = 2000)
sensor.set_auto_whitebal(False, (10, 0, 0))
sensor.set_auto_gain(False, 10)
sensor.skip_frames(time=2000)
sensor.snapshot()
print("0x0=", hex(sensor.__read_reg(0x0)))
# Untitled - By: HsienYu - Thu Jun 15 2017
import sensor, time, image, math
from pyb import Servo
# Reset sensor
sensor.reset()
# Sensor settings
sensor.set_contrast(1)
sensor.set_gainceiling(16)
# HQVGA and GRAYSCALE are the best for face tracking.
sensor.set_framesize(sensor.HQVGA)
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.__write_reg(0x0C, sensor.__read_reg(0x0C) | (1 << 7)) #Flips Camera
s1 = Servo(1) # servo on position 1 (PD12, VIN, GND)
s2 = Servo(2) # servo on position 1 (PD13, VIN, GND)
# Load Haar Cascade
# By default this will use all stages, lower satges is faster but less accurate.
face_cascade = image.HaarCascade("frontalface", stages=15)
# Default Pan/Tilt for the camera in degrees.
# Camera range is from -90 to 90
cam_pan = 60
cam_tilt = 60
# Turn the camera to the default position
"""
s1.angle(0,0)
# Reset sensor
sensor.reset()
x = 0
y = 0
z = 0
a = 0
i = 303
j = 303
# Sensor settings
sensor.set_contrast(3)
sensor.set_gainceiling(16)
# HQVGA and GRAYSCALE are the best for face tracking.
sensor.set_framesize(sensor.HQVGA)
sensor.set_pixformat(sensor.GRAYSCALE)
sensor.__write_reg(0x0C, sensor.__read_reg(0x0C) | (1 << 7))
# Load Haar Cascade
# By default this will use all stages, lower satges is faster but less accurate.
face_cascade = image.HaarCascade("frontalface", stages=25)
print(face_cascade)
led = pyb.LED(3)
# FPS clock
clock = time.clock()
while (True):
clock.tick()
led.on()
# Capture snapshot
img = sensor.snapshot()
# Find objects.
# In Memory Shadow Removal w/ Frame Differencing Example
#
# This example demonstrates using frame differencing with your OpenMV Cam using
# shadow removal to help reduce the affects of cast shadows in your scene.
import sensor, image, pyb, os, time
TRIGGER_THRESHOLD = 5
sensor.reset() # Initialize the camera sensor.
sensor.set_pixformat(sensor.RGB565) # or sensor.GRAYSCALE
sensor.set_framesize(sensor.QQVGA) # or sensor.QVGA (or others)
if sensor.get_id() == sensor.OV7725: # Reduce sensor PLL from 6x to 4x.
sensor.__write_reg(0x0D, (sensor.__read_reg(0x0D) & 0x3F) | 0x40)
sensor.skip_frames(time = 2000) # Let new settings take affect.
sensor.set_auto_whitebal(False) # Turn off white balance.
sensor.set_auto_gain(False) # Turn this off too.
clock = time.clock() # Tracks FPS.
# Take from the main frame buffer's RAM to allocate a second frame buffer.
# There's a lot more RAM in the frame buffer than in the MicroPython heap.
# However, after doing this you have a lot less RAM for some algorithms...
# So, be aware that it's a lot easier to get out of RAM issues now. However,
# frame differencing doesn't use a lot of the extra space in the frame buffer.
# But, things like AprilTags do and won't work if you do this...
extra_fb = sensor.alloc_extra_fb(sensor.width(), sensor.height(), sensor.RGB565)
print("About to save background image...")
sensor.skip_frames(time = 2000) # Give the user time to get ready.
extra_fb.replace(sensor.snapshot())
print("Saved background image - Now frame differencing!")
