def getEmbedDetections(self, src, pipParams=None):
img = self.imgProcessor.undistort(src=src)
vBoxes, heatMap = self.scanner.getRelevantBoxes(src=img)
binary = self.preProcess(src=img)
currFitLeft, leftFitType, leftBin = self.lineLeft.getFit(src=binary)
currFitRight, rightFitType, rightBin = self.lineRight.getFit(src=binary)
sanityPass = self.sanityCheckPass(currFitLeft, currFitRight)
if sanityPass:
img = self.addLanePoly(srcShape=binary.shape, dst=img, fitLeft=currFitLeft, fitRight=currFitRight)
else:
if self.lineLeft.reScanJustified():
currFitLeft, leftFitType, leftBin = self.lineLeft.reScanWithPrimary(src=binary)
else:
self.lineLeft.resetFits()
currFitLeft, leftFitType, leftBin = self.lineLeft.getFit(src=binary)
if self.lineRight.reScanJustified():
currFitRight, rightFitType, rightBin = self.lineRight.reScanWithPrimary(src=binary)
else:
self.lineRight.resetFits()
currFitRight, rightFitType, rightBin = self.lineRight.getFit(src=binary)
sanityPass = self.sanityCheckPass(currFitLeft, currFitRight)
if sanityPass:
img = self.addLanePoly(srcShape=binary.shape, dst=img, fitLeft=currFitLeft, fitRight=currFitRight)
aux.drawBoxes(img=img, bBoxes=vBoxes)
origin = (20, 20)
if pipParams is not None:
alpha = pipParams['alpha']
ratio = pipParams['scaleRatio']
commonBin = cv2.addWeighted(src1=leftBin, alpha=0.5, src2=rightBin, beta=0.5, gamma=1.0)
pipHeight = int(commonBin.shape[0] * ratio)
heatWidth = int(heatMap.shape[1] * ratio)
self.addPip(pipImage=commonBin, dstImage=img,
pipAlpha=alpha, pipResizeRatio=ratio, origin=origin)
self.addPip(pipImage=heatMap, dstImage=img,
pipAlpha=alpha, pipResizeRatio=ratio,
origin=(img.shape[1] - heatWidth - 20, 20))
if currFitLeft is not None and currFitRight is not None:
self.addOffsetStamp(leftFit=currFitLeft, rightFit=currFitRight,
image=img, origin=(20, pipHeight + 70), fontScale=0.66, thickness=2,
color=(0, 255, 0))
return img
def embedDetections(self, src, pipParams=None):
"""
Main 'pipeline' for adding Lane polygon AND detected vehicles to the original image
:param src: original image
:param pipParams: alpha and scale ratios
:return: undistorted color image with the Lane embedded.
"""
# 1. Undistortion
img = self.imgProcessor.undistort(src=src)
"""
1a. ====| PROJECT 5 - VEHICLE DETECTION |====
Getting vehicle boxes
"""
vBoxes, heatMap = self.scanner.relevantBoxes(src=img)
# 2. Binary (bird-eye projection)
'''
binary = self.preProcess(src=img)
# 3. Getting fits
#currFitLeft, leftFitType, leftBin = self.lineLeft.getFit(src=binary)
#currFitRight, rightFitType, rightBin = self.lineRight.getFit(src=binary)
# 4. Evaluation
sanityPass = self.sanityCheckPass(currFitLeft, currFitRight)
if sanityPass:
# Adding Lane polygon if sanity check passed
img = self.addLanePoly(srcShape=binary.shape, dst=img, fitLeft=currFitLeft, fitRight=currFitRight)
else:
# Evaluation if box-search re-scan justified without resetting history of previous fits
if self.lineLeft.reScanJustified():
currFitLeft, leftFitType, leftBin = self.lineLeft.reScanWithPrimary(src=binary)
else:
# Resetting fits and starting from scratch with box-search
self.lineLeft.resetFits()
currFitLeft, leftFitType, leftBin = self.lineLeft.getFit(src=binary)
# Same for right fit.
if self.lineRight.reScanJustified():
currFitRight, rightFitType, rightBin = self.lineRight.reScanWithPrimary(src=binary)
else:
self.lineRight.resetFits()
currFitRight, rightFitType, rightBin = self.lineRight.getFit(src=binary)
# Evaluation after second search attempt
# sanityPass, laneWidth = self.sanityCheckPass(currFitLeft, currFitRight)
sanityPass = self.sanityCheckPass(currFitLeft, currFitRight)
# Adding Lane polygon if sanity check passed. Otherwise, simply no poly added
if sanityPass:
img = self.addLanePoly(srcShape=binary.shape, dst=img, fitLeft=currFitLeft, fitRight=currFitRight)
'''
# ====| PROJECT 5 - VEHICLE DETECTION |====
# Drawing vehicle boxes
aux.drawBoxes(img=img, bBoxes=vBoxes)
# Upper left corner where starting to add pip and telemetry
origin = (20, 20)
# Adding PIP
if pipParams is not None:
alpha = pipParams['alpha']
ratio = pipParams['scaleRatio']
# Combining bins from left and right fit searches
#commonBin = cv2.addWeighted(src1=leftBin, alpha=0.5, src2=rightBin, beta=0.5, gamma=1.0)
# To keep for subsequent telemetry stamps
#pipHeight = int(commonBin.shape[0] * ratio)
heatWidth = int(heatMap.shape[1] * ratio)
# Lane Detection Picture-in-Picture
'''
self.addPip(pipImage=commonBin, dstImage=img,
pipAlpha=alpha, pipResizeRatio=ratio, origin=origin)
'''
# ====| PROJECT 5 - VEHICLE DETECTION |====
# Vehicle Detection Picture-in-Picture
self.addPip(pipImage=heatMap, dstImage=img,
pipAlpha=alpha, pipResizeRatio=ratio,
origin=(img.shape[1] - heatWidth - 20, 20))
'''
if currFitLeft is not None and currFitRight is not None:
self.addCurvatureStamp(leftFit=currFitLeft, rightFit=currFitRight,
image=img, origin=(20, pipHeight + 40), fontScale=0.66, thickness=2,
color=(0, 255, 0))
self.addOffsetStamp(leftFit=currFitLeft, rightFit=currFitRight,
image=img, origin=(20, pipHeight + 70), fontScale=0.66, thickness=2,
color=(0, 255, 0))
'''
return img