test Lane Detection
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a6e16ab212
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import cv2
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import numpy as np
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frameWidth = 640
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frameHeight = 480
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cap = cv2.VideoCapture(1)
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cap.set(3, frameWidth)
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cap.set(4, frameHeight)
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def empty(a):
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pass
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cv2.namedWindow("HSV")
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cv2.resizeWindow("HSV", 640, 240)
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cv2.createTrackbar("HUE Min", "HSV", 0, 179, empty)
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cv2.createTrackbar("HUE Max", "HSV", 179, 179, empty)
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cv2.createTrackbar("SAT Min", "HSV", 0, 255, empty)
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cv2.createTrackbar("SAT Max", "HSV", 255, 255, empty)
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cv2.createTrackbar("VALUE Min", "HSV", 0, 255, empty)
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cv2.createTrackbar("VALUE Max", "HSV", 255, 255, empty)
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cap = cv2.VideoCapture('vid1.mp4')
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frameCounter = 0
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while True:
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frameCounter +=1
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if cap.get(cv2.CAP_PROP_FRAME_COUNT) ==frameCounter:
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cap.set(cv2.CAP_PROP_POS_FRAMES,0)
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frameCounter=0
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_, img = cap.read()
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imgHsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
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h_min = cv2.getTrackbarPos("HUE Min", "HSV")
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h_max = cv2.getTrackbarPos("HUE Max", "HSV")
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s_min = cv2.getTrackbarPos("SAT Min", "HSV")
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s_max = cv2.getTrackbarPos("SAT Max", "HSV")
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v_min = cv2.getTrackbarPos("VALUE Min", "HSV")
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v_max = cv2.getTrackbarPos("VALUE Max", "HSV")
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print(h_min)
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lower = np.array([h_min, s_min, v_min])
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upper = np.array([h_max, s_max, v_max])
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mask = cv2.inRange(imgHsv, lower, upper)
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result = cv2.bitwise_and(img, img, mask=mask)
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mask = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR)
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hStack = np.hstack([img, mask, result])
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cv2.imshow('Horizontal Stacking', hStack)
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if cv2.waitKey(1) and 0xFF == ord('q'):
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break
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cap.release()
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cv2.destroyAllWindows()
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import cv2
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import numpy as np
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import utils
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curveList = []
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avgVal = 10
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def getLaneCurve(img, display = 2):
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imgCopy = img.copy()
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imgResult = img.copy()
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#### STEP 1
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imgThres = utils.thresholding(img)
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#### STEP 2
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hT, wT, c = img.shape
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points = utils.valTrackbars()
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imgWarp = utils.warpImg(imgThres, points, wT, hT)
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imgWarpPoints = utils.drawPoints(imgCopy, points)
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#### STEP 3
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middlePoint,imgHist = utils.getHistogram(imgWarp,display=True,minPer=0.5,region=4)
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curveAveragePoint, imgHist = utils.getHistogram(imgWarp, display=True, minPer=0.9)
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curveRaw = curveAveragePoint - middlePoint
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#### STEP 4
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curveList.append(curveRaw)
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if len(curveList)>avgVal:
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curveList.pop(0)
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curve = int(sum(curveList)/len(curveList))
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'''
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cv2.imshow('Thres', imgThres)
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cv2.imshow('Warp', imgWarp)
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cv2.imshow('Warp Points', imgWarpPoints)
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cv2.imshow('Histogram', imgHist)
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return None
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'''
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#### STEP 5
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if display != 0:
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imgInvWarp = utils.warpImg(imgWarp, points, wT, hT, inv=True)
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imgInvWarp = cv2.cvtColor(imgInvWarp, cv2.COLOR_GRAY2BGR)
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imgInvWarp[0:hT // 3, 0:wT] = 0, 0, 0
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imgLaneColor = np.zeros_like(img)
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imgLaneColor[:] = 0, 255, 0
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imgLaneColor = cv2.bitwise_and(imgInvWarp, imgLaneColor)
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imgResult = cv2.addWeighted(imgResult, 1, imgLaneColor, 1, 0)
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midY = 450
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cv2.putText(imgResult, str(curve), (wT // 2 - 80, 85), cv2.FONT_HERSHEY_COMPLEX, 2, (255, 0, 255), 3)
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cv2.line(imgResult, (wT // 2, midY), (wT // 2 + (curve * 3), midY), (255, 0, 255), 5)
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cv2.line(imgResult, ((wT // 2 + (curve * 3)), midY - 25), (wT // 2 + (curve * 3), midY + 25), (0, 255, 0), 5)
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for x in range(-30, 30):
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w = wT // 20
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cv2.line(imgResult, (w * x + int(curve // 50), midY - 10),
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(w * x + int(curve // 50), midY + 10), (0, 0, 255), 2)
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#fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer);
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#cv2.putText(imgResult, 'FPS ' + str(int(fps)), (20, 40), cv2.FONT_HERSHEY_SIMPLEX, 1, (230, 50, 50), 3);
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if display == 2:
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imgStacked = utils.stackImages(0.7, ([img, imgWarpPoints, imgWarp],
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[imgHist, imgLaneColor, imgResult]))
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cv2.imshow('ImageStack', imgStacked)
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elif display == 1:
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cv2.imshow('Resutlt', imgResult)
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'''
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cv2.imshow('Thres', imgThres)
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cv2.imshow('Warp', imgWarp)
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cv2.imshow('Warp Points', imgWarpPoints)
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cv2.imshow('Histogramp', imgHist)
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'''
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#### NORMALIZATION
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curve = curve/100
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if curve>1: curve ==1
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if curve<-1:curve == -1
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return curve
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if __name__ == '__main__':
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cap = cv2.VideoCapture('vid1.mp4')
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initialTrackBarVals = [116, 138, 20, 232]
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utils.initializeTrackbars(initialTrackBarVals)
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frameCounter = 0
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curveList = []
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while True:
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frameCounter +=1
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if cap.get(cv2.CAP_PROP_FRAME_COUNT) ==frameCounter:
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cap.set(cv2.CAP_PROP_POS_FRAMES,0)
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frameCounter=0
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success, img = cap.read()
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img = cv2.resize(img,(480,240))
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curve = getLaneCurve(img, display = 1)
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print(curve)
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#cv2.imshow('Vid', img)
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cv2.waitKey(1)
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@ -0,0 +1,104 @@
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import cv2
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import numpy as np
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def thresholding(img):
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imgHsv = cv2.cvtColor(img,cv2.COLOR_BGR2HSV)
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lowerWhite = np.array([19,0,150])
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upperWhite = np.array([170,70,255])
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maskWhite = cv2.inRange(imgHsv,lowerWhite,upperWhite)
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return maskWhite
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def warpImg(img,points,w,h,inv = False):
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pts1 = np.float32(points)
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pts2 = np.float32([[0,0],[w,0],[0,h],[w,h]])
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if inv:
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matrix = cv2.getPerspectiveTransform(pts2, pts1)
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else:
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matrix = cv2.getPerspectiveTransform(pts1,pts2)
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imgWarp = cv2.warpPerspective(img,matrix,(w,h))
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return imgWarp
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def nothing(a):
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pass
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def initializeTrackbars(intialTracbarVals,wT=480, hT=240):
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cv2.namedWindow("Trackbars")
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cv2.resizeWindow("Trackbars", 360, 240)
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cv2.createTrackbar("Width Top", "Trackbars", intialTracbarVals[0],wT//2, nothing)
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cv2.createTrackbar("Height Top", "Trackbars", intialTracbarVals[1], hT, nothing)
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cv2.createTrackbar("Width Bottom", "Trackbars", intialTracbarVals[2],wT//2, nothing)
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cv2.createTrackbar("Height Bottom", "Trackbars", intialTracbarVals[3], hT, nothing)
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def valTrackbars(wT=480, hT=240):
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widthTop = cv2.getTrackbarPos("Width Top", "Trackbars")
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heightTop = cv2.getTrackbarPos("Height Top", "Trackbars")
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widthBottom = cv2.getTrackbarPos("Width Bottom", "Trackbars")
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heightBottom = cv2.getTrackbarPos("Height Bottom", "Trackbars")
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points = np.float32([(widthTop, heightTop), (wT-widthTop, heightTop),
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(widthBottom , heightBottom ), (wT-widthBottom, heightBottom)])
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return points
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def drawPoints(img,points):
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for x in range(4):
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cv2.circle(img,(int(points[x][0]),int(points[x][1])),15,(0,0,255),cv2.FILLED)
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return img
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def getHistogram(img,minPer=0.1,display= False,region=1):
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if region == 1:
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histValues = np.sum(img, axis= 0)
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else:
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histValues = np.sum(img[img.shape[0]//region:,:], axis = 0)
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maxValue = np.max(histValues)
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minValue = minPer*maxValue
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indexArray = np.where(histValues >= minValue)
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basePoint = int(np.average(indexArray))
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#print(basePoint)
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if display:
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imgHist = np.zeros((img.shape[0],img.shape[1],3),np.uint8)
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for x,intensity in enumerate(histValues):
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cv2.line(imgHist,(x,img.shape[0]),(x,img.shape[0]-intensity//255//region),(255,0,255),1)
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cv2.circle(imgHist,(basePoint,img.shape[0]),20,(0,255,255),cv2.FILLED)
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return basePoint,imgHist
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return basePoint
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def stackImages(scale,imgArray):
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rows = len(imgArray)
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cols = len(imgArray[0])
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rowsAvailable = isinstance(imgArray[0], list)
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width = imgArray[0][0].shape[1]
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height = imgArray[0][0].shape[0]
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if rowsAvailable:
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for x in range ( 0, rows):
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for y in range(0, cols):
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if imgArray[x][y].shape[:2] == imgArray[0][0].shape [:2]:
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imgArray[x][y] = cv2.resize(imgArray[x][y], (0, 0), None, scale, scale)
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else:
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imgArray[x][y] = cv2.resize(imgArray[x][y], (imgArray[0][0].shape[1], imgArray[0][0].shape[0]), None, scale, scale)
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if len(imgArray[x][y].shape) == 2: imgArray[x][y]= cv2.cvtColor( imgArray[x][y], cv2.COLOR_GRAY2BGR)
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imageBlank = np.zeros((height, width, 3), np.uint8)
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hor = [imageBlank]*rows
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hor_con = [imageBlank]*rows
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for x in range(0, rows):
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hor[x] = np.hstack(imgArray[x])
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ver = np.vstack(hor)
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else:
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for x in range(0, rows):
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if imgArray[x].shape[:2] == imgArray[0].shape[:2]:
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imgArray[x] = cv2.resize(imgArray[x], (0, 0), None, scale, scale)
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else:
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imgArray[x] = cv2.resize(imgArray[x], (imgArray[0].shape[1], imgArray[0].shape[0]), None,scale, scale)
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if len(imgArray[x].shape) == 2: imgArray[x] = cv2.cvtColor(imgArray[x], cv2.COLOR_GRAY2BGR)
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hor= np.hstack(imgArray)
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ver = hor
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return ver
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