「樹莓派」使用OpenCV & Numpy機器視覺來巡線

「樹莓派」使用OpenCV & Numpy機器視覺來巡線

本期講解如何使用OpenCV以及Numpy來分析畫面中的黑線或白線的所在位置,從而實現機器視覺來巡線。

「樹莓派」使用OpenCV & Numpy機器視覺來巡線

我們可以從黑色背景上尋白線也可以從白色背景上尋黑線

你可以將這個功能應用在你自己的機器人上面

所需代碼:

CVline:

<code>#!/usr/bin/env/python3

# File name   : RPiCam.py

# Date: 2019/12/23



import cv2

import zmq

import base64

import picamera

from picamera.array import PiRGBArray

import numpy as np



IP = '192.168.3.11'



camera = picamera.PiCamera()

camera.resolution = (640, 480)

camera.framerate = 20

rawCapture = PiRGBArray(camera, size=(640, 480))



context = zmq.Context()

footage_socket = context.socket(zmq.PAIR)

footage_socket.connect('tcp://%s:5555'%IP)

print(IP)



linePos_1 = 380

linePos_2 = 430

lineColorSet = 255



for frame in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):

frame_image = frame.array



frame_findline = cv2.cvtColor(frame_image, cv2.COLOR_BGR2GRAY)

retval, frame_findline =  cv2.threshold(frame_findline, 0, 255, cv2.THRESH_OTSU)

frame_findline = cv2.erode(frame_findline, None, iterations=6)

colorPos_1 = frame_findline[linePos_1]

colorPos_2 = frame_findline[linePos_2]

try:

lineColorCount_Pos1 = np.sum(colorPos_1 == lineColorSet)

lineColorCount_Pos2 = np.sum(colorPos_2 == lineColorSet)



lineIndex_Pos1 = np.where(colorPos_1 == lineColorSet)

lineIndex_Pos2 = np.where(colorPos_2 == lineColorSet)



if lineColorCount_Pos1 == 0:

lineColorCount_Pos1 = 1

if lineColorCount_Pos2 == 0:

lineColorCount_Pos2 = 1



left_Pos1 = lineIndex_Pos1[0][lineColorCount_Pos1-1]

right_Pos1 = lineIndex_Pos1[0][0]

center_Pos1 = int((left_Pos1+right_Pos1)/2)



left_Pos2 = lineIndex_Pos2[0][lineColorCount_Pos2-1]

right_Pos2 = lineIndex_Pos2[0][0]

center_Pos2 = int((left_Pos2+right_Pos2)/2)



center = int((center_Pos1+center_Pos2)/2)

except:

center = None

pass



print(center)



try:

cv2.line(frame_image,(left_Pos1,(linePos_1+30)),(left_Pos1,(linePos_1-30)),(255,128,64),1)

cv2.line(frame_image,(right_Pos1,(linePos_1+30)),(right_Pos1,(linePos_1-30)),(64,128,255),)

cv2.line(frame_image,(0,linePos_1),(640,linePos_1),(255,255,64),1)



cv2.line(frame_image,(left_Pos2,(linePos_2+30)),(left_Pos2,(linePos_2-30)),(255,128,64),1)

cv2.line(frame_image,(right_Pos2,(linePos_2+30)),(right_Pos2,(linePos_2-30)),(64,128,255),1)

cv2.line(frame_image,(0,linePos_2),(640,linePos_2),(255,255,64),1)



cv2.line(frame_image,((center-20),int((linePos_1+linePos_2)/2)),((center+20),int((linePos_1+linePos_2)/2)),(0,0,0),1)

cv2.line(frame_image,((center),int((linePos_1+linePos_2)/2+20)),((center),int((linePos_1+linePos_2)/2-20)),(0,0,0),1)

except:

pass



encoded, buffer = cv2.imencode('.jpg', frame_image)

jpg_as_text = base64.b64encode(buffer)

footage_socket.send(jpg_as_text)

rawCapture.truncate(0)
/<code>

PC:

<code>#!/usr/bin/python3

# File name   : PC.py

# Author  : William

# Date: 2019/11/21



import cv2

import zmq

import base64

import numpy as np



context = zmq.Context()

footage_socket = context.socket(zmq.PAIR)

footage_socket.bind('tcp://*:5555')



while True:

frame = footage_socket.recv_string()

img = base64.b64decode(frame)

npimg = np.frombuffer(img, dtype=np.uint8)

source = cv2.imdecode(npimg, 1)

cv2.imshow("Stream", source)

cv2.waitKey(1)/<code>


分享到:


相關文章: