Difference between revisions of "Linetracking with opencv"
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+ | Now you should be able to realize line detection with pi camera. However, you might find it is not satisfying because sometimes the video window suddenly disappears and the terminal gives you a Nonetype error again. | ||
== Authors == | == Authors == |
Revision as of 20:29, 3 December 2018
Overview
This Tutorial will show how to make a line detection and find a center of line for a line following pi car.
Materials/Prerequisites
You will need a Raspberry pi 3 with python installed and Pi camera (Webcam works too). you also need to install OpenCV onto your Raspberry Pi. We can follow instructions to install OpenCV. If it is the first time to use pi camera, to be able to access the Raspberry pi camera with OpenCV and Python, we recommend to look at this instruction. For interfacing with the Raspberry Pi camera module using Python, the basic idea is to install picamera module with NumPy array support since OpenCV represents images as NumPy arrays when using Python bindings.
Process
If you are using Webcam, you can simply follow this link to realize line detection. The code is given below:
import sys
import time
import cv2
import numpy as np
import os
Kernel_size=15
low_threshold=40
high_threshold=120
rho=10
threshold=15
theta=np.pi/180
minLineLength=10
maxLineGap=1
Initialize camera
video_capture = cv2.VideoCapture(0)
while True:
# CAPTURE FRAME-BY-FRAME
ret, frame = video_capture.read()
time.sleep(0.1)
#Convert to Grayscale
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#Blur image to reduce noise. if Kernel_size is bigger the image will be more blurry
blurred = cv2.GaussianBlur(gray, (Kernel_size, Kernel_size), 0)
#Perform canny edge-detection.
#If a pixel gradient is higher than high_threshold is considered as an edge.
#if a pixel gradient is lower than low_threshold is is rejected , it is not an edge.
#Bigger high_threshold values will provoque to find less edges.
#Canny recommended ratio upper:lower between 2:1 or 3:1
edged = cv2.Canny(blurred, low_threshold, high_threshold)
#Perform hough lines probalistic transform
lines = cv2.HoughLinesP(edged,rho,theta,threshold,minLineLength,maxLineGap)
#Draw cicrcles in the center of the picture
cv2.circle(frame,(320,240),20,(0,0,255),1)
cv2.circle(frame,(320,240),10,(0,255,0),1)
cv2.circle(frame,(320,240),2,(255,0,0),2)
#With this for loops only a dots matrix is painted on the picture
#for y in range(0,480,20):
#for x in range(0,640,20):
#cv2.line(frame,(x,y),(x,y),(0,255,255),2)
#With this for loops a grid is painted on the picture
for y in range(0,480,40):
cv2.line(frame,(0,y),(640,y),(255,0,0),1)
for x in range(0,640,40):
cv2.line(frame,(x,0),(x,480),(255,0,0),1)
#Draw lines on input image
if(lines != None):
for x1,y1,x2,y2 in lines[0]:
cv2.line(frame,(x1,y1),(x2,y2),(0,255,0),2)
cv2.putText(frame,'lines_detected',(50,50),cv2.FONT_HERSHEY_SIMPLEX,1,(0,255,0),1)
cv2.imshow("line detect test", frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything is done, release the capture
video_capture.release()
cv2.destroyAllWindows()
Our group is using pi camera so the code needs to be modified. Otherwise it will show Nonetype error due to an image not being read properly from disk or a frame not being read from the video stream. You cannot use cv2.VideoCapture when you should instead be using the picamera Python package to access the Raspberry Pi camera module.
There are two ways to modify the code to replace USB Webcam with pi camera.
One is swapping out the cv2.VideoCapture for the VideoStream that works with both the Raspberry Pi camera module and USB webcams. more details
We did another way. Firstly we import some pi camera packages
from picamera.array import PiRGBArray
from picamera import PiCamera
when initializing camera, we comment out video_capture = cv2.VideoCapture(0). Instead, we give code below:
#Initialize camera
camera = PiCamera()
camera.resolution = (640, 480)
camera.framerate = 10
rawCapture = PiRGBArray(camera, size=(640, 480))
We also change the "While True" loop into:
for f in camera.capture_continuous(rawCapture, format="bgr", use_video_port=True):
Finally, we comment out "ret, frame = video_capture.read()" and add:
frame = f.array
Now you should be able to realize line detection with pi camera. However, you might find it is not satisfying because sometimes the video window suddenly disappears and the terminal gives you a Nonetype error again.
Authors
Pi Car Discovery Group