ocq2 发布的帖子

可以的话如何更改呢？请提供一个思路谢谢

追其他物体的小车如何让小车跑到物体面前距离很近呢？想着考虑以后收取物体 越近越好，如何修改程序呢？

追小球的小车里的PID整定后的参数各是多少呢？

您说的检测矿泉水瓶是用模板匹配还是神经网络训练出来的呢？

# 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
from image import SEARCH_EX, SEARCH_DS

# 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.GRAYSCALE) # 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=0.5, i=1, imax=100)
h_pid = PID(p=0.05, i=0.1, imax=50)

template = image.Image("/qiu.pgm")

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_template(template, 0.70, step=4, search=SEARCH_EX) #, roi=(10, 0, 60, 60))

    if blobs:
        max_blob = find_max(blobs)
        x_error = max_blob[0]+max_blob[2]/2-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) # rect
        img.draw_cross(int(max_blob[0]+max_blob[2]/2),int( max_blob[1]+max_blob[3]/2)) # 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(18,-18)

openmv4plus 利用神经网络训练出来其他物体的模型例如矿泉水瓶，如何应用在追其他物体的小车上呢？

电脑上深度学习处理图像的程序能在openmv4plus上运行吗？如何可以如何实现呢？

用的是 openmv 4 H7 plus