From c64514ba405788f7bd2a0b98c74fa1720243cbd5 Mon Sep 17 00:00:00 2001 From: Siwat Sirichai Date: Fri, 9 Dec 2022 13:31:41 +0700 Subject: [PATCH] test Lane Detection --- ColorPicker.py | 55 ++++++++++++++++++++++ LaneDetectionModule.py | 102 ++++++++++++++++++++++++++++++++++++++++ utils.py | 104 +++++++++++++++++++++++++++++++++++++++++ vid1.mp4 | Bin 0 -> 2632558 bytes 4 files changed, 261 insertions(+) create mode 100644 ColorPicker.py create mode 100644 LaneDetectionModule.py create mode 100644 utils.py create mode 100644 vid1.mp4 diff --git a/ColorPicker.py b/ColorPicker.py new file mode 100644 index 0000000..c3f858c --- /dev/null +++ b/ColorPicker.py @@ -0,0 +1,55 @@ +import cv2 +import numpy as np + +frameWidth = 640 +frameHeight = 480 +cap = cv2.VideoCapture(1) +cap.set(3, frameWidth) +cap.set(4, frameHeight) + + +def empty(a): + pass + +cv2.namedWindow("HSV") +cv2.resizeWindow("HSV", 640, 240) +cv2.createTrackbar("HUE Min", "HSV", 0, 179, empty) +cv2.createTrackbar("HUE Max", "HSV", 179, 179, empty) +cv2.createTrackbar("SAT Min", "HSV", 0, 255, empty) +cv2.createTrackbar("SAT Max", "HSV", 255, 255, empty) +cv2.createTrackbar("VALUE Min", "HSV", 0, 255, empty) +cv2.createTrackbar("VALUE Max", "HSV", 255, 255, empty) + +cap = cv2.VideoCapture('vid1.mp4') +frameCounter = 0 + +while True: + frameCounter +=1 + if cap.get(cv2.CAP_PROP_FRAME_COUNT) ==frameCounter: + cap.set(cv2.CAP_PROP_POS_FRAMES,0) + frameCounter=0 + + _, img = cap.read() + imgHsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV) + + h_min = cv2.getTrackbarPos("HUE Min", "HSV") + h_max = cv2.getTrackbarPos("HUE Max", "HSV") + s_min = cv2.getTrackbarPos("SAT Min", "HSV") + s_max = cv2.getTrackbarPos("SAT Max", "HSV") + v_min = cv2.getTrackbarPos("VALUE Min", "HSV") + v_max = cv2.getTrackbarPos("VALUE Max", "HSV") + print(h_min) + + lower = np.array([h_min, s_min, v_min]) + upper = np.array([h_max, s_max, v_max]) + mask = cv2.inRange(imgHsv, lower, upper) + result = cv2.bitwise_and(img, img, mask=mask) + + mask = cv2.cvtColor(mask, cv2.COLOR_GRAY2BGR) + hStack = np.hstack([img, mask, result]) + cv2.imshow('Horizontal Stacking', hStack) + if cv2.waitKey(1) and 0xFF == ord('q'): + break + +cap.release() +cv2.destroyAllWindows() \ No newline at end of file diff --git a/LaneDetectionModule.py b/LaneDetectionModule.py new file mode 100644 index 0000000..1d8631c --- /dev/null +++ b/LaneDetectionModule.py @@ -0,0 +1,102 @@ +import cv2 +import numpy as np +import utils + + +curveList = [] +avgVal = 10 + +def getLaneCurve(img, display = 2): + + imgCopy = img.copy() + imgResult = img.copy() + #### STEP 1 + imgThres = utils.thresholding(img) + + #### STEP 2 + hT, wT, c = img.shape + points = utils.valTrackbars() + imgWarp = utils.warpImg(imgThres, points, wT, hT) + imgWarpPoints = utils.drawPoints(imgCopy, points) + + #### STEP 3 + middlePoint,imgHist = utils.getHistogram(imgWarp,display=True,minPer=0.5,region=4) + curveAveragePoint, imgHist = utils.getHistogram(imgWarp, display=True, minPer=0.9) + curveRaw = curveAveragePoint - middlePoint + + #### STEP 4 + curveList.append(curveRaw) + if len(curveList)>avgVal: + curveList.pop(0) + curve = int(sum(curveList)/len(curveList)) + ''' + cv2.imshow('Thres', imgThres) + cv2.imshow('Warp', imgWarp) + cv2.imshow('Warp Points', imgWarpPoints) + cv2.imshow('Histogram', imgHist) + return None + ''' + #### STEP 5 + if display != 0: + imgInvWarp = utils.warpImg(imgWarp, points, wT, hT, inv=True) + imgInvWarp = cv2.cvtColor(imgInvWarp, cv2.COLOR_GRAY2BGR) + imgInvWarp[0:hT // 3, 0:wT] = 0, 0, 0 + imgLaneColor = np.zeros_like(img) + imgLaneColor[:] = 0, 255, 0 + imgLaneColor = cv2.bitwise_and(imgInvWarp, imgLaneColor) + imgResult = cv2.addWeighted(imgResult, 1, imgLaneColor, 1, 0) + midY = 450 + cv2.putText(imgResult, str(curve), (wT // 2 - 80, 85), cv2.FONT_HERSHEY_COMPLEX, 2, (255, 0, 255), 3) + cv2.line(imgResult, (wT // 2, midY), (wT // 2 + (curve * 3), midY), (255, 0, 255), 5) + cv2.line(imgResult, ((wT // 2 + (curve * 3)), midY - 25), (wT // 2 + (curve * 3), midY + 25), (0, 255, 0), 5) + for x in range(-30, 30): + w = wT // 20 + cv2.line(imgResult, (w * x + int(curve // 50), midY - 10), + (w * x + int(curve // 50), midY + 10), (0, 0, 255), 2) + #fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer); + #cv2.putText(imgResult, 'FPS ' + str(int(fps)), (20, 40), cv2.FONT_HERSHEY_SIMPLEX, 1, (230, 50, 50), 3); + if display == 2: + imgStacked = utils.stackImages(0.7, ([img, imgWarpPoints, imgWarp], + [imgHist, imgLaneColor, imgResult])) + cv2.imshow('ImageStack', imgStacked) + elif display == 1: + cv2.imshow('Resutlt', imgResult) + + ''' + cv2.imshow('Thres', imgThres) + cv2.imshow('Warp', imgWarp) + cv2.imshow('Warp Points', imgWarpPoints) + cv2.imshow('Histogramp', imgHist) + ''' + #### NORMALIZATION + curve = curve/100 + if curve>1: curve ==1 + if curve<-1:curve == -1 + + return curve + + + +if __name__ == '__main__': + cap = cv2.VideoCapture('vid1.mp4') + initialTrackBarVals = [116, 138, 20, 232] + utils.initializeTrackbars(initialTrackBarVals) + frameCounter = 0 + curveList = [] + + while True: + frameCounter +=1 + if cap.get(cv2.CAP_PROP_FRAME_COUNT) ==frameCounter: + cap.set(cv2.CAP_PROP_POS_FRAMES,0) + frameCounter=0 + + success, img = cap.read() + img = cv2.resize(img,(480,240)) + curve = getLaneCurve(img, display = 1) + print(curve) + #cv2.imshow('Vid', img) + cv2.waitKey(1) + + + + diff --git a/utils.py b/utils.py new file mode 100644 index 0000000..9dcaeb9 --- /dev/null +++ b/utils.py @@ -0,0 +1,104 @@ +import cv2 +import numpy as np + + + +def thresholding(img): + imgHsv = cv2.cvtColor(img,cv2.COLOR_BGR2HSV) + lowerWhite = np.array([19,0,150]) + upperWhite = np.array([170,70,255]) + maskWhite = cv2.inRange(imgHsv,lowerWhite,upperWhite) + return maskWhite + +def warpImg(img,points,w,h,inv = False): + pts1 = np.float32(points) + pts2 = np.float32([[0,0],[w,0],[0,h],[w,h]]) + if inv: + matrix = cv2.getPerspectiveTransform(pts2, pts1) + else: + matrix = cv2.getPerspectiveTransform(pts1,pts2) + imgWarp = cv2.warpPerspective(img,matrix,(w,h)) + return imgWarp + +def nothing(a): + pass + +def initializeTrackbars(intialTracbarVals,wT=480, hT=240): + cv2.namedWindow("Trackbars") + cv2.resizeWindow("Trackbars", 360, 240) + cv2.createTrackbar("Width Top", "Trackbars", intialTracbarVals[0],wT//2, nothing) + cv2.createTrackbar("Height Top", "Trackbars", intialTracbarVals[1], hT, nothing) + cv2.createTrackbar("Width Bottom", "Trackbars", intialTracbarVals[2],wT//2, nothing) + cv2.createTrackbar("Height Bottom", "Trackbars", intialTracbarVals[3], hT, nothing) + +def valTrackbars(wT=480, hT=240): + widthTop = cv2.getTrackbarPos("Width Top", "Trackbars") + heightTop = cv2.getTrackbarPos("Height Top", "Trackbars") + widthBottom = cv2.getTrackbarPos("Width Bottom", "Trackbars") + heightBottom = cv2.getTrackbarPos("Height Bottom", "Trackbars") + points = np.float32([(widthTop, heightTop), (wT-widthTop, heightTop), + (widthBottom , heightBottom ), (wT-widthBottom, heightBottom)]) + return points + +def drawPoints(img,points): + for x in range(4): + cv2.circle(img,(int(points[x][0]),int(points[x][1])),15,(0,0,255),cv2.FILLED) + return img + + +def getHistogram(img,minPer=0.1,display= False,region=1): + + if region == 1: + histValues = np.sum(img, axis= 0) + else: + histValues = np.sum(img[img.shape[0]//region:,:], axis = 0) + + + maxValue = np.max(histValues) + minValue = minPer*maxValue + + indexArray = np.where(histValues >= minValue) + basePoint = int(np.average(indexArray)) + #print(basePoint) + + if display: + imgHist = np.zeros((img.shape[0],img.shape[1],3),np.uint8) + for x,intensity in enumerate(histValues): + cv2.line(imgHist,(x,img.shape[0]),(x,img.shape[0]-intensity//255//region),(255,0,255),1) + cv2.circle(imgHist,(basePoint,img.shape[0]),20,(0,255,255),cv2.FILLED) + + return basePoint,imgHist + + return basePoint + + +def stackImages(scale,imgArray): + rows = len(imgArray) + cols = len(imgArray[0]) + rowsAvailable = isinstance(imgArray[0], list) + width = imgArray[0][0].shape[1] + height = imgArray[0][0].shape[0] + if rowsAvailable: + for x in range ( 0, rows): + for y in range(0, cols): + if imgArray[x][y].shape[:2] == imgArray[0][0].shape [:2]: + imgArray[x][y] = cv2.resize(imgArray[x][y], (0, 0), None, scale, scale) + else: + imgArray[x][y] = cv2.resize(imgArray[x][y], (imgArray[0][0].shape[1], imgArray[0][0].shape[0]), None, scale, scale) + if len(imgArray[x][y].shape) == 2: imgArray[x][y]= cv2.cvtColor( imgArray[x][y], cv2.COLOR_GRAY2BGR) + imageBlank = np.zeros((height, width, 3), np.uint8) + hor = [imageBlank]*rows + hor_con = [imageBlank]*rows + for x in range(0, rows): + hor[x] = np.hstack(imgArray[x]) + ver = np.vstack(hor) + else: + for x in range(0, rows): + if imgArray[x].shape[:2] == imgArray[0].shape[:2]: + imgArray[x] = cv2.resize(imgArray[x], (0, 0), None, scale, scale) + else: + imgArray[x] = cv2.resize(imgArray[x], (imgArray[0].shape[1], imgArray[0].shape[0]), None,scale, scale) + if len(imgArray[x].shape) == 2: imgArray[x] = cv2.cvtColor(imgArray[x], cv2.COLOR_GRAY2BGR) + hor= np.hstack(imgArray) + ver = hor + return ver \ No newline at end of file diff --git a/vid1.mp4 b/vid1.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..88c50428faa17c58e07af9fa62c069a423ac665c GIT binary patch literal 2632558 zcmeFZcT|*3)-T#k5SnDuG#RwXISMKu+O!RlL^4Q{EIA`VQKABZl93>iB}fz$35o<2 zP$VM=2ndKMN)Qp_t!iM#Z`OCebI)Dt{B_=5vu9WB+O@-P@2Y;DmKg*B!RF`}87yQk+lAaZj*=VTAp-rV0S2?>E9Uqm2|JwPB4@IU|l{Fez3|HmBv zZ_WR1L=J@K+#URE0OxVCck|g*aaIH8iAr@N$$hrN%dv%Taw z2OnQ&PY+I(12RH{HsEV<-A=x8ECnJqOFnId;*tmif3qMyZxK8KqJW1^hANx<4AkN{y#Ga z%vr$i)KP_A-4vnRvu96Vo;(sk>GWyOS}V{*d)fGUkvwmEXR`Bj^YO5A3q()?=^mg# zA?)ktw_E=RAOMQ2c7RhO5VUoGlL7v4TTXiia2hbbw_Hv$ftmbM0P;Gg6V1vvB%=dFN4zyBFe5s*Xs%{#nmhyPFZ|JL7)=l}2iU4L*t zj1%HP0r>r$IR01m|K1Pdg8I6=FsnM9bumTIfwRl_t);&Yu(Xe^T;I+AKkNGU z9LBd>p9jD$od56i#V-DT$FtiPZ98%9+TV@$Z~t&VT!((20KS_aoI|`}f9~e{zsl$D 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