def find_loop_mesh(imgInfo, showVisuals=False, zoom=0, virtCenter=(-1,-1)):
"""|
:param imgInfo: Information about the input image. Two types allowed yet : Image path or Numpy array
:type imgInfo: String or Numpy array
:param showVisuals: Display for debug
:type showVisuals: Boolean
:param zoom: Zoom level
:type zoom: uint
:param virtCenter: A virtual center if reqal center use is not wanted
:type virtCenter: Tuple (uint,uint)
:returns: (label,x,y) result from loop_detection function
"""
if showVisuals:
(x,y,x2,y2),imageClone,image3,store,virtCenter = meshGen.generate_meshing_info(imgInfo,method=meshGen.LUCID_CENTER_PROC,showVisuals=showVisuals,zoom=zoom,virtCenter=virtCenter)
cv.Rectangle(imageClone,(x,y),(x2,y2),cv.Scalar( 120, 120, 120 ))
else:
(x,y,x2,y2),image3 = meshGen.generate_meshing_info(imgInfo,method=meshGen.LUCID_CENTER_PROC,showVisuals=showVisuals,zoom=zoom,virtCenter=virtCenter)
xres = x2-((x2-x)//2)
yrestemp = -1
yrestemp2 = -1
yres = 0
while y<y2 and (yrestemp < 0 or yrestemp2 < 0):
y+=1
y2-=1
if image3[y,xres]>0:
yrestemp = y
if image3[y2,xres]>0:
yrestemp2 = y2
if y>=y2:
yres = y2-((y2-y)//2)
else:
yres = yrestemp2 - ((yrestemp2-yrestemp)//2)
if showVisuals:
for num in range(len(store)):
cv.Line( image3, virtCenter, store[num],cv.Scalar( 120, 120, 120 ),2,8 );
cv.Line( imageClone, (xres-3,yres-3), (xres+3,yres+3),cv.Scalar( 120, 120, 120 ),2,8 );
cv.Line( imageClone, (xres-3,yres+3), (xres+3,yres-3),cv.Scalar( 120, 120, 120 ),2,8 );
cv.Line( imageClone, (virtCenter[0],virtCenter[1]-3), (virtCenter[0],virtCenter[1]+3),cv.Scalar( 120, 120, 120 ),2,8 );
cv.Line( imageClone, (virtCenter[0]-3,virtCenter[1]), (virtCenter[0]+3,virtCenter[1]),cv.Scalar( 120, 120, 120 ),2,8 );
#real center
cv.Line( imageClone, ((659//2),(463//2)-15), ((659//2),(463//2)+15),cv.Scalar( 120, 120, 120 ),2,8 );
cv.Line( imageClone, ((659//2)-15,(463//2)), ((659//2)+15,(463//2)),cv.Scalar( 120, 120, 120 ),2,8 );
displayCv(('Resultat',imageClone),('RaysVisu',image3))
cv.WaitKey(0)
return "meshing",xres,yres
def face_detection(imgInfo,showVisuals=False,zoom=0):
"""|
:param imgInfo: Information about the input image. Two types allowed yet : Image path or Numpy array
:type imgInfo: String or Numpy array
:param showVisuals: Display for debug
:type showVisuals: Boolean
:param zoom: Zoom level
:type zoom: uint
:returns: (label,x,y) result from loop_detection function
"""
image=imgInfo2cvImage(imgInfo)
image2=cv.CloneImage(image)
if zoom == 0:
cv.AdaptiveThreshold(image2,image2,255,cv.CV_ADAPTIVE_THRESH_MEAN_C,cv.CV_THRESH_BINARY_INV,45,6)
else:
cv.AdaptiveThreshold(image2,image2,255,cv.CV_ADAPTIVE_THRESH_MEAN_C,cv.CV_THRESH_BINARY_INV,121,6)
image3=cv.CloneImage(image2)
cv.Zero(image3)
storage = cv.CreateMemStorage()
contours = cv.FindContours(cv.CloneImage
(image2),storage,cv.CV_RETR_EXTERNAL,cv.CV_CHAIN_APPROX_SIMPLE,(0,0))
cv.DrawContours(image3,contours,cv.RGB(255,255,255),cv.RGB (255,255,255),2,cv.CV_FILLED)
cv.Smooth(image3,image3,cv.CV_MEDIAN,11)
image4 = cv.CloneImage(image3)
if zoom == 0:
erode(image4,image4,9)
dilate(image4,image4,9)
else:
erode(image4,image4,25)
dilate(image4,image4,25)
count = white_detect(image4)
if showVisuals:
displayCv(('Resultat',image),('ErosionDilation',image4),('AdaptiveThresh',image2),('FinalTreatmentVisualisation',image3))
cv.WaitKey(0)
return count
def loop_detection(imgInfo,showVisuals=False,zoom=0):
"""|
:param imgInfo: Information about the input image. Two types allowed yet : Image path or Numpy array
:type imgInfo: String or Numpy array
:param showVisuals: Display for debug
:type showVisuals: Boolean
:param zoom: Zoom level
:type zoom: uint
:returns: (label,x,y) result from loop_detection function
"""
image=imgInfo2cvImage(imgInfo)
image2=cv.CloneImage(image)
#if zoom == 0:
cv.AdaptiveThreshold(image2,image2,255,cv.CV_ADAPTIVE_THRESH_MEAN_C,cv.CV_THRESH_BINARY_INV,45,6)
#else:
#cv.Threshold(image2,image2,30,255,cv.CV_THRESH_BINARY)
image3=cv.CloneImage(image2)
cv.Zero(image3)
storage = cv.CreateMemStorage()
contours = cv.FindContours(cv.CloneImage
(image2),storage,cv.CV_RETR_EXTERNAL,cv.CV_CHAIN_APPROX_SIMPLE,(0,0))
cv.DrawContours(image3,contours,cv.RGB(255,255,255),cv.RGB (255,255,255),2,cv.CV_FILLED)
cv.Smooth(image3,image3,cv.CV_MEDIAN,11)
image4 = cv.CloneImage(image3)
#check if the loop is in the image
count = white_detect(image4[10:image4.height-10,10:image4.width-10])
if count < 50:
return ("No loop detected",-1,-1)
#dilation and erosion if there is no zoom
if zoom == 0:
erode(image4,image4,11)
dilate(image4,image4,11)
count = white_detect(image4[10:image4.height-10,10:image4.width-10])
if count < 50:
(xcenter,ycenter) = find_approx_loop(image3)
if showVisuals==1:
cv.Line(image,(int(xcenter),int(0)),(int(xcenter),int(image.height)),cv.RGB(120.0,120.0,120.0))
cv.Line(image,(int(0),int(ycenter)),(int(image.width),int(ycenter)),cv.RGB(120.0,120.0,120.0))
displayCv(('Resultat',image),('ErosionDilation',image4),('AdaptiveThresh',image2),('FinalTreatmentVisualisation',image3))
cv.WaitKey(0)
return ('ApproxCoord',xcenter-15,ycenter)
if zoom == 0:
(xcenter,ycenter) = only_robot(image3)
if xcenter > 0:
if showVisuals:
cv.Line(image,(int(xcenter),int(0)),(int(xcenter),int(image.height)),cv.RGB(120.0,120.0,120.0))
cv.Line(image,(int(0),int(ycenter)),(int(image.width),int(ycenter)),cv.RGB(120.0,120.0,120.0))
displayCv(('Resultat',image),('ErosionDilation',image4),('AdaptiveThresh',image2),('FinalTreatmentVisualisation',image3))
return ("ArmRobot",xcenter,ycenter)
clean_the_robot(image3,image4)
adjust_detection(image3)
if zoom == 0:
(xcenter,ycenter) = calculate_center(image3,image3)
else:
(xcenter,ycenter) = calculate_center(image3,image3)
if showVisuals:
cv.Line(image,(int(xcenter),int(0)),(int(xcenter),int(image.height)),cv.RGB(120.0,120.0,120.0))
cv.Line(image,(int(0),int(ycenter)),(int(image.width),int(ycenter)),cv.RGB(120.0,120.0,120.0))
displayCv(('Resultat',image),('ErosionDilation',image4),('AdaptiveThresh',image2),('FinalTreatmentVisualisation',image3))
cv.WaitKey(0)
return ("Coord",xcenter,ycenter)