def calculate_center(image,imageMask=None):
"""|
:param image: treated image with just the loop for finding center
:type image: IplImage
:returns: Coordinates from the center in pixels (x,y)
"""
i=0
left=-1
right=-1
up=-1
down=-1
if imageMask is None:
imageMask = image
while i<imageMask.width:
if white_detect(imageMask[:,i])>0:
left = i
break
i=i+1
while i<imageMask.width:
if white_detect(imageMask[:,i])==0:
right = i-1
break
i=i+1
if right == -1:
return (-1,-1)
horizoncenter=right-round((right-left)/2.9)
j=3
while j<image.height:
if image[j,horizoncenter]>0:
up = j
break
j=j+1
h=image.height-3
while h>j:
if image[h,horizoncenter]>0:
down = h
break
h=h-1
if down == -1:
return (-2,-2)
verticalcenter = down - round((down-up)/2)
return (horizoncenter,verticalcenter)
def only_robot(image3):
"""|
:param image3 : B/W Image with which it is used
:type image3 : IplImage
"""
xcenter=image3.width
ycenter=-1
i=image3.height-1
firstWhite = -1
lastWhite = -1
firstWhite2 = -1
lastWhite2 = -1
maxWhite=0
while i>=0:
count=white_detect(image3[i,:])
if count>0:
if firstWhite<0:
firstWhite=i
else:
if lastWhite>0:
if firstWhite2<0:
firstWhite2=i
if count>maxWhite:
maxWhite=count
else:
if firstWhite>0:
if lastWhite<0:
lastWhite=i+1
else:
if firstWhite2>0:
if lastWhite2<0:
lastWhite2=i+1
i=i-1
if maxWhite < (image3.width*90)//100:
return (-1,-1)
if firstWhite2==0 or (firstWhite2>0 and lastWhite2<0):
lastWhite2=0
if firstWhite==0 or (firstWhite>0 and lastWhite<0):
lastWhite=0
mid = (firstWhite+lastWhite)//2
mid2 = (firstWhite2+lastWhite2)//2
if mid2 <0:
if mid > image3.height//2:
ycenter = (mid+image3.height)//2
else:
ycenter = mid//2
else:
ycenter=(mid+mid2)//2
return (xcenter,ycenter)
def find_approx_loop(image):
"""|
:param image : B/W Image with which is used for the approx
:type image : IplImage
"""
i=image.width-1
while i>=0:
if white_detect(image[:,i])>0:
j=image.height-1
while j>=0:
if image[j,i]>0:
if white_detect(image[j-6:j+6,i-6:i+6])>17:
return i,j
j=j-1
i=i-1
return -1,-1
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 clean_the_robot(image,imageMask):
"""|
:param image : The image to modify
:type image : IplImage
:param imageMask : Image with morphological mathematic too clear the robot part
:type imageMask : IplImage
"""
i=imageMask.width-1
wbegin=0
while i>=1:
if white_detect(imageMask[:,i])>0:
wbegin = 1
else:
if wbegin==1:
cv.Set(image[:,0:i],0)
return i
i=i-1
cv.Set(image[:,0:1],0)
return -1
def findInternalPoints(image,image2,pointsPerArcs,center=(-1,-1)):
"""|
:param image: Image after first treatment
:type image: Opencv IplImage
:param image2: Initial image treated
:type image2: Opencv IplImage
:param storage: Internal points of the loop
:type storage: Array[(uint,uint)...(uint,uint)]
:param storageInfo: Values of constant of line equation foreach internal points. a and b for an equation ax+b.
:type storageInfo: Array[(float,float)...(float,float)].
:param center: Coordinate of the center of the image
:type center: Tuple (uint,uint)
:returns: With method LUCID_CENTER_PROC and LUCID_RECT_BBOX, return coordinates for a rectangle bounding box (xmin,ymin,xmax,ymax)
:returns: With method LUCID_POLY_BBOX, return all points of the polygone
"""
#init list for points (storage) and for curve equation information
storage = []
storageInfo = []
if center == (-1,-1):
center = (image.width//2+50,image.height//2)
i = center[1]
while i>=0:
if image[i,center[0]]>0:
storage.append((center[0],i))
storageInfo.append((0,1))
break;
else:
i=i-1
#print storage[0][0]
for degrees in np.arange(15,360,15):
#for degrees in np.arange(5,360,5):
x2 = storage[0][0]-center[0]
y2 = storage[0][1]-center[1]
xrot = x2*math.cos(toRadians(degrees))-y2*math.sin(toRadians(degrees))
yrot = y2*math.cos(toRadians(degrees))+x2*math.sin(toRadians(degrees))
xrot = round(xrot + center[0])
yrot = round(yrot + center[1])
#cv.Line( image2, (image.width//2,image.height//2), (xrot,yrot),cv.Scalar( 60, 60,60 ),2,4 );
#print "inter"
if center[0]==xrot:
m=1
p=0
i = center[1]
while i<image.height:
if image[i,center[0]]>0:
storage.append((center[0],i))
storageInfo.append((m,p))
break;
else:
i=i+1
if i==image.height:
storage.append((-1,-1))
else:
m = (yrot - center[1])/(xrot - center[0])
p = -(m*xrot)+yrot
#print center[0],center[1],xrot,yrot,m,p
x = center[0]
y = center[1]
ok =False
while 1:
if degrees<190:
x=x+1
else:
x=x-1
y=m*x+p
y = int(round(y))
if x<image.width-2 and x>=2 and y<image.height-2 and y>=2:
if white_detect(image[(y-2):(y+2),(x-2):(x+2)])>0:
storage.append((x,y))
storageInfo.append((m,p))
ok = True
#cv.Circle( image,storage[0],5,cv.RGB(255,255,255 ),-1,8 )
break
else:
break
if ok == False:
x = center[0]
y = center[1]
while 1:
if degrees<90 or degrees>270:
y=y-1
else:
y=y+1
if m==0:
#storage.append((0,0))
break
x=(y-p)/m
x = int(round(x))
if x<image.width-2 and x>=2 and y<image.height-2 and y>=2:
if white_detect(image[(y-2):(y+2),(x-2):(x+2)])>0:
storage.append((x,y))
storageInfo.append((m,p))
#cv.Circle( image,storage[0],5,cv.RGB(255,255,255 ),-1,8 )
break
else:
#storage.append((0,0))
break
return storage,storageInfo
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)
