因为edge制作的模型只能判断 摄像头目前画面属于哪个class ,不能把我想要追踪的物体框起来,
nvfd
@nvfd
nvfd 发布的帖子
-
openmv的p7 或p8口好像坏了一个 ,控制不了舵机,我想用p9代替坏的那个,该怎么改代码啊
from pyb import Pin, Timer#导入引脚和定时器
inverse_left=False #change it to True to inverse left wheel 初始化
inverse_right=False #change it to True to inverse right wheel 初始化ain1 = Pin('P0', Pin.OUT_PP)#控制左右两边电机方向
ain2 = Pin('P1', Pin.OUT_PP)
bin1 = Pin('P2', Pin.OUT_PP)
bin2 = Pin('P3', Pin.OUT_PP)
ain1.low()
ain2.low()
bin1.low()
bin2.low()pwma = Pin('P7')
pwmb = Pin('P8')
tim = Timer(4, freq=1000)#设置定时器4 频率为1000hz
ch1 = tim.channel(1, Timer.PWM, pin=pwma)
ch2 = tim.channel(2, Timer.PWM, pin=pwmb)
ch1.pulse_width_percent(0)
ch2.pulse_width_percent(0)def run(left_speed, right_speed):
if inverse_left==False: #如果接反了正负 就取反修正
left_speed=(-left_speed)
if inverse_right==True:# 同上
right_speed=(-right_speed)if left_speed < 0: ain1.low() ain2.high() else: ain1.high() ain2.low() ch1.pulse_width_percent(int(abs(left_speed))) if right_speed < 0: bin1.low() bin2.high() else: bin1.high() bin2.low() ch2.pulse_width_percent(int(abs(right_speed)))
-
按照例程做的追踪小球的小车在没有识别到小球原地旋转的时候 如果发现了小球的话会突然冲刺,而不是像视频里面那个稳稳的跟踪它
# Blob Detection Example # # This example shows off how to use the find_blobs function to find color # blobs in the image. This example in particular looks for dark green objects. import sensor, image, time import car from pid import PID # You may need to tweak the above settings for tracking green 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_auto_whitebal(False) # turn this off. clock = time.clock() # Tracks FPS. # For color tracking to work really well you should ideally be in a very, very, # very, controlled enviroment where the lighting is constant... green_threshold = (52, 82, -67, -47, 26, 61) size_threshold = 1000 x_pid = PID(p=0.5, i=1, imax=100) h_pid = PID(p=0.01, i=0.1, imax=50) def find_max(blobs): max_size=0 for blob in blobs: if blob[2]*blob[3] > max_size: max_blob=blob max_size = blob[2]*blob[3] return max_blob while(True): clock.tick() # Track elapsed milliseconds between snapshots(). img = sensor.snapshot() # Take a picture and return the image. blobs = img.find_blobs([green_threshold]) if blobs: max_blob = find_max(blobs) x_error = max_blob[5]-img.width()/2 h_error = max_blob[2]*max_blob[3]-size_threshold print("x error: ", x_error) ''' for b in blobs: # Draw a rect around the blob. img.draw_rectangle(b[0:4]) # rect img.draw_cross(b[5], b[6]) # cx, cy ''' img.draw_rectangle(max_blob[0:4]) # rect img.draw_cross(max_blob[5], max_blob[6]) # cx, cy x_output=x_pid.get_pid(x_error,1) h_output=h_pid.get_pid(h_error,1) print("h_output",h_output) car.run((-h_output+x_output)*0.5,(-h_output+x_output)*0.5) else: car.run(10,-10)
-
根据追踪小球的小车的例子做了一个出来,但是发现小车并没有像视频里面那样和小球保持一段距离,识别到了就往前顶,
Blob Detection Example
This example shows off how to use the find_blobs function to find color
blobs in the image. This example in particular looks for dark green objects.
import sensor, image, time
import car
from pid import PIDYou may need to tweak the above settings for tracking green 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_auto_whitebal(False) # turn this off.
clock = time.clock() # Tracks FPS.For color tracking to work really well you should ideally be in a very, very,
very, controlled enviroment where the lighting is constant...
green_threshold = (76, 96, -110, -30, 8, 66)
size_threshold = 2000
x_pid = PID(p=3, i=1, imax=100)
h_pid = PID(p=0.22, i=0.1, imax=50)def find_max(blobs):
max_size=0
for blob in blobs:
if blob[2]*blob[3] > max_size:
max_blob=blob
max_size = blob[2]*blob[3]
return max_blobwhile(True):
clock.tick() # Track elapsed milliseconds between snapshots().
img = sensor.snapshot() # Take a picture and return the image.blobs = img.find_blobs([green_threshold]) if blobs: max_blob = find_max(blobs) x_error = max_blob[5]-img.width()/2 h_error = max_blob[2]*max_blob[3]-size_threshold print("x error: ", x_error) ''' for b in blobs: # Draw a rect around the blob. img.draw_rectangle(b[0:4]) # rect img.draw_cross(b[5], b[6]) # cx, cy ''' img.draw_rectangle(max_blob[0:4]) # rect img.draw_cross(max_blob[5], max_blob[6]) # cx, cy x_output=x_pid.get_pid(x_error,1) h_output=h_pid.get_pid(h_error,1) print("h_output",h_output) car.run(-h_output-x_output,-h_output+x_output) else: car.run(10,-10)