60 lines
1.5 KiB
Python
60 lines
1.5 KiB
Python
import cv2
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import numpy as np
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import math
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import serial
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# import picamera
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# import picamera.array
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threshold1 = 85
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threshold2 = 85
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theta=0
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r_width = 500
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r_height = 300
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minLineLength = 5
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maxLineGap = 10
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k_width = 5
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k_height = 5
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max_slider = 10
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# Linux System Serial Port
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# ser = serial.Serial("/dev/ttyACM0", 115200, timeout=1) # linux
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# Read Image
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camera = cv2.VideoCapture(1)
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# image = cv2.imread(r'C:\Users\aasai\Desktop\new1.jpeg')
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ff, image = camera.read()
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# Resize width=500 height=300 incase of inputting raspi captured image
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image = cv2.resize(image,(r_width,r_height))
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# Convert the image to gray-scale
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gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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# given input image, kernel width =5 height = 5, Gaussian kernel standard deviation
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blurred = cv2.GaussianBlur(gray, (k_width, k_height), 0)
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# Find the edges in the image using canny detector
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edged = cv2.Canny(blurred, threshold1, threshold2)
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# Detect points that form a line
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lines = cv2.HoughLinesP(edged,1,np.pi/180,max_slider,minLineLength,maxLineGap)
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print(lines[0])
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for x in range(0, len(lines)):
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for x1,y1,x2,y2 in lines[x]:
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cv2.line(image,(x1,y1),(x2,y2),(255,0,0),3)
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theta=theta+math.atan2((y2-y1),(x2-x1))
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print(theta)
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threshold=5
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if(theta>threshold):
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print("Go left")
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if(theta<-threshold):
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print("Go right")
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if(abs(theta)<threshold):
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print("Go straight")
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theta=0
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cv2.imshow("Gray Image",gray)
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cv2.imshow("blurred",blurred)
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cv2.imshow("Edged",edged)
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cv2.imshow("Line Detection",image)
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cv2.waitKey(0)
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cv2.destroyAllWindows() |