def getData(): frame = highgui.cvQueryFrame(capture) if frame is None: return None cv.cvSplit(frame, b_img, g_img, r_img, None) cv.cvInRangeS(r_img, 150, 255, r_img) cv.cvInRangeS(g_img, 0, 100, g_img) cv.cvInRangeS(b_img, 0, 100, b_img) cv.cvAnd(r_img, g_img, laser_img) cv.cvAnd(laser_img, b_img, laser_img) cv.cvErode(laser_img,laser_img) #,0,2) cv.cvDilate(laser_img,laser_img) c_count, contours = cv.cvFindContours (laser_img, storage, cv.sizeof_CvContour, cv.CV_RETR_LIST, cv.CV_CHAIN_APPROX_NONE, cv.cvPoint (0,0)) if c_count: return returnEllipses(contours) else: return None
def read(self):
frame = self.input.read()
# which channels to combine
cv_rs = [None]*4
#self.debug_print('channels:%s'%self.channels)
# if frame only has one channel, just return it
if frame.nChannels == 1 :
for i in self.channels :
cv_rs[i] = frame
else :
for i in self.channels :
cv_rs[i] = cv.cvCreateImage(cv.cvSize(frame.width,frame.height),frame.depth,1)
#self.debug_print(cv_rs)
# extract the color channel
#print 'frame.nChannels',frame.nChannels
cv.cvSplit(frame,cv_rs[0],cv_rs[1],cv_rs[2],cv_rs[3])
#cvt_im = cv.cvCreateImage(cv.cvSize(frame.width,frame.height),frame.depth,3)
cv.cvMerge(cv_rs[0],cv_rs[1],cv_rs[2],cv_rs[3],frame)
return frame
def read(self): frame=self.input.read() if self.enabled: cv_rs = [None]*4 cv_thresh = [0]*4 cv_max = [255]*4 for i in self.channels : cv_rs[i] = cv.cvCreateImage(cv.cvSize(frame.width,frame.height),frame.depth,1) cv_thresh[i] = self.thresholds[i] cv_max[i] = self.max_thresholds[i] # extract the color channel cv.cvSplit(frame,cv_rs[0],cv_rs[1],cv_rs[2],cv_rs[3]) #self.debug_print(cv_rs) for i in self.channels : cv.cvThreshold(cv_rs[i],cv_rs[i],cv_thresh[i],cv_max[i],self.type) #cv_thresh = cv.cvCreateImage(cv.cvSize(frame.width,frame.height),frame.depth,3) cv.cvZero(frame) cv.cvMerge(cv_rs[0],cv_rs[1],cv_rs[2],cv_rs[3],frame) #frame = cv_thresh return frame
def getFilter(frameWidht, frameHeight):
cvNamedWindow("Filtred")
cvCreateTrackbar("hmax", "Filtred", getHlsFilter('hmax'), 180, trackBarChangeHmax)
cvCreateTrackbar("hmin", "Filtred", getHlsFilter('hmin'), 180, trackBarChangeHmin)
#cvCreateTrackbar("lmax", "Filtred", hlsFilter['lmax'], 255, trackBarChangeLmax)
#cvCreateTrackbar("lmin", "Filtred", hlsFilter['lmin'], 255, trackBarChangeLmin)
cvCreateTrackbar("smax", "Filtred", getHlsFilter('smax'), 255, trackBarChangeSmax)
cvCreateTrackbar("smin", "Filtred", getHlsFilter('smin'), 255, trackBarChangeSmin)
cvSetMouseCallback("Filtred", mouseClick, None)
frame = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 3)
hlsFrame = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 3)
filtredFrame = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 3)
mask = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 1)
hFrame = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 1)
lFrame = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 1)
sFrame = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 1)
ThHFrame = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 1)
ThLFrame = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 1)
ThSFrame = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 1)
key = -1
while key == -1:
if not cvGrabFrame(CAM):
print "Could not grab a frame"
exit
frame = cvQueryFrame(CAM)
cvCvtColor(frame, hlsFrame, CV_BGR2HLS)
cvSplit(hlsFrame, hFrame, lFrame, sFrame, None)
pixelInRange(hFrame, getHlsFilter('hmin'), getHlsFilter('hmax'), 0, 180, ThHFrame)
#pixelInRange(lFrame, getHlsFilter('lmin'), getHlsFilter('lmax'), 0, 255, ThLFrame)
pixelInRange(sFrame, getHlsFilter('smin'), getHlsFilter('smax'), 0, 255, ThSFrame)
cvSetZero(mask)
cvAnd(ThHFrame, ThSFrame, mask)
cvSetZero(filtredFrame)
cvCopy(frame, filtredFrame, mask)
cvShowImage("Filtred", filtredFrame)
key = cvWaitKey(10)
if key == 'r':
key = -1
resetHlsFilter()
cvDestroyWindow("Filtred")
def read(self): src = self.camera.read() thresh = self.thresh2pg.read() red = self.red2pg.read() raw_thresh = self.thresh.read() cvt_red = cv.cvCreateImage(cv.cvSize(raw_thresh.width,raw_thresh.height),raw_thresh.depth,1) cv.cvSplit(raw_thresh,cvt_red,None,None,None) cvpt_min = cv.cvPoint(0,0) cvpt_max = cv.cvPoint(0,0) t = cv.cvMinMaxLoc(cvt_red,cvpt_min,cvpt_max) return src,thresh,red,(cvpt_max.x,cvpt_max.y)
def read(self): raw_thresh = self.thresh.read() cvt_red = cv.cvCreateImage(cv.cvSize(raw_thresh.width,raw_thresh.height),raw_thresh.depth,1) cv.cvSplit(raw_thresh,cvt_red,None,None,None) cvpt_min = cv.cvPoint(0,0) cvpt_max = cv.cvPoint(0,0) t = cv.cvMinMaxLoc(cvt_red,cvpt_min,cvpt_max) if cvpt_max.x == 0 and cvpt_max.y == 0 : return [] return [(cvpt_max.x,cvpt_max.y)]
def read(self): frame = self.input.read() # image we'll eventually return # which channels to combine # if frame only has one channel, just return it if frame.nChannels == 1 : return frame else : cv_rs = [None]*4 cv_rs[self.channel] = cv.cvCreateImage(cv.cvSize(frame.width,frame.height),frame.depth,1) # extract the color channel cv.cvSplit(frame,cv_rs[0],cv_rs[1],cv_rs[2],cv_rs[3]) return cv_rs[self.channel]
def startChroma(background, frameWidht, frameHeight):
#cvNamedWindow("Original")
cvNamedWindow("Chroma")
hlsFrame = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 3)
transparency = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 3)
mask = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 1)
hFrame = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 1)
lFrame = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 1)
sFrame = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 1)
ThHFrame = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 1)
ThLFrame = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 1)
ThSFrame = cvCreateImage(cvSize(frameWidth, frameHeight), IPL_DEPTH_8U, 1)
key = -1
while key == -1:
if not cvGrabFrame(CAM):
print "Could not grab a frame"
exit
frame = cvQueryFrame(CAM)
cvCvtColor(frame, hlsFrame, CV_BGR2HLS)
cvSplit(hlsFrame, hFrame, lFrame, sFrame, None)
pixelInRange(hFrame, getHlsFilter('hmin'), getHlsFilter('hmax'), 0, 180, ThHFrame)
#pixelInRange(lFrame, getHlsFilter('lmin'), getHlsFilter('lmax'), 0, 255, ThLFrame)
pixelInRange(sFrame, getHlsFilter('smin'), getHlsFilter('smax'), 0, 255, ThSFrame)
cvAnd(ThHFrame, ThSFrame, mask)
cvCopy(background, frame, mask)
cvShowImage("Chroma", frame)
key = cvWaitKey(10)
cvDestroyWindow("Chroma")
def read(self) :
frame=self.input.read()
if self.enabled :
cv_rs = [cv.cvCreateImage(cv.cvSize(frame.width,frame.height),frame.depth,1) for i in range(3)]
cv.cvSplit(frame,cv_rs[0],cv_rs[1],cv_rs[2],None)
channel_contours = []
for frame in cv_rs[0] :
# I think these functions are too specialized for transforms
#cv.cvSmooth(frame,frame,cv.CV_GAUSSIAN,3, 0, 0, 0 )
#cv.cvErode(frame, frame, None, 1)
#cv.cvDilate(frame, frame, None, 1)
num_contours,contours=cv.cvFindContours(frame,self.storage,cv.sizeof_CvContour,cv.CV_RETR_LIST,cv.CV_CHAIN_APPROX_NONE,cv.cvPoint(0,0))
if contours is None :
channel_contours.append([])
else :
contours = cv.cvApproxPoly( contours, cv.sizeof_CvContour, self.storage, cv.CV_POLY_APPROX_DP, 3, 1 );
if contours is None :
channel_contours.append([])
else :
final_contours = []
for c in contours.hrange() :
area = abs(cv.cvContourArea(c))
#self.debug_print('Polygon Area: %f'%area)
if area >= self.min_area :
lst = []
for pt in c :
lst.append((pt.x,pt.y))
final_contours.append(lst)
contours = contours.h_next
channel_contours.append(final_contours)
return channel_contours
def read(self): frame = self.input.read() if self.debug : raw_frame = cv.cvCreateImage(cv.cvSize(frame.width,frame.height),frame.depth,frame.nChannels) cv.cvCopy(frame,raw_frame,None) self.raw_frame_surface=pygame.image.frombuffer(frame.imageData,(frame.width,frame.height),'RGB') if self.enabled : cvt_red = cv.cvCreateImage(cv.cvSize(frame.width,frame.height),frame.depth,1) cv.cvSplit(frame,None,None,cvt_red,None) if self.debug : red_frame = cv.cvCreateImage(cv.cvSize(cvt_red.width,cvt_red.height),cvt_red.depth,3) cv.cvMerge(cvt_red,None,None,None,red_frame) self.red_frame_surface = pygame.image.frombuffer(red_frame.imageData,(cvt_red.width,cvt_red.height),'RGB') # I think these functions are too specialized for transforms cv.cvSmooth(cvt_red,cvt_red,cv.CV_GAUSSIAN,3, 0, 0, 0 ) cv.cvErode(cvt_red, cvt_red, None, 1) cv.cvDilate(cvt_red, cvt_red, None, 1) if self.debug : thresh_frame = cv.cvCreateImage(cv.cvSize(cvt_red.width,cvt_red.height),cvt_red.depth,3) cv.cvMerge(cvt_red,None,None,None,thresh_frame) self.thresh_frame_surface = pygame.image.frombuffer(cvt_red.imageData,(cvt_red.width,cvt_red.height),'RGB') cvpt_min = cv.cvPoint(0,0) cvpt_max = cv.cvPoint(0,0) t = cv.cvMinMaxLoc(cvt_red,cvpt_min,cvpt_max) print t if cvpt_max.x == 0 and cvpt_max.y == 0 : return [] return [(cvpt_max.x,cvpt_max.y)]
def _get_frame_channel(self,frame=None,channel=0) : if frame is None : frame = self._get_cv_frame() # if frame only has one channel, just return it if frame.nChannels == 1 : return frame # extract the color channel cv_r = cv.cvCreateImage(cv.cvSize(frame.width,frame.height),frame.depth,1) if channel == 0 : cv.cvSplit(frame,cv_r,None,None,None) elif channel == 1 : cv.cvSplit(frame,None,cv_r,None,None) elif channel == 2 : cv.cvSplit(frame,None,None,cv_r,None) elif channel == 3 : cv.cvSplit(frame,None,None,None,cv_r) else : cv.cvCvtColor(frame,cv_r,cv.CV_BGR2GRAY) return cv_r
def main(args):
global capture
global hmax, hmin
highgui.cvNamedWindow('Camera', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Hue', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Satuation', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Value', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Laser', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvMoveWindow('Camera', 0, 10)
highgui.cvMoveWindow('Hue', 0, 350)
highgui.cvMoveWindow('Satuation', 360, 10)
highgui.cvMoveWindow('Value', 360, 350)
highgui.cvMoveWindow('Laser', 700, 40)
highgui.cvCreateTrackbar("Brightness Trackbar","Camera",0,255, change_brightness);
highgui.cvCreateTrackbar("hmin Trackbar","Hue",hmin,180, change_hmin);
highgui.cvCreateTrackbar("hmax Trackbar","Hue",hmax,180, change_hmax);
highgui.cvCreateTrackbar("smin Trackbar","Satuation",smin,255, change_smin);
highgui.cvCreateTrackbar("smax Trackbar","Satuation",smax,255, change_smax);
highgui.cvCreateTrackbar("vmin Trackbar","Value",vmin,255, change_vmin);
highgui.cvCreateTrackbar("vmax Trackbar","Value",vmax,255, change_vmax);
print "grabbing camera"
capture = highgui.cvCreateCameraCapture(0)
print "found camera"
highgui.cvSetCaptureProperty(capture,highgui.CV_CAP_PROP_FRAME_WIDTH, 320)
highgui.cvSetCaptureProperty(capture,highgui.CV_CAP_PROP_FRAME_HEIGHT, 240)
frame = highgui.cvQueryFrame(capture)
frameSize = cv.cvGetSize(frame)
hsv = cv.cvCreateImage(frameSize,8,3)
mask = cv.cvCreateImage(frameSize,8,1)
hue = cv.cvCreateImage(frameSize,8,1)
satuation = cv.cvCreateImage(frameSize,8,1)
value = cv.cvCreateImage(frameSize,8,1)
laser = cv.cvCreateImage(frameSize,8,1)
while 1:
frame = highgui.cvQueryFrame(capture)
cv.cvCvtColor(frame, hsv, cv.CV_BGR2HSV)
#cv.cvInRangeS(hsv,hsv_min,hsv_max,mask)
cv.cvSplit(hsv,hue,satuation,value,None)
cv.cvInRangeS(hue,hmin,hmax,hue)
cv.cvInRangeS(satuation,smin,smax,satuation)
cv.cvInRangeS(value,vmin,vmax,value)
#cv.cvInRangeS(hue,0,180,hue)
cv.cvAnd(hue, value, laser)
#cv.cvAnd(laser, value, laser)
cenX,cenY = averageWhitePoints(laser)
#print cenX,cenY
draw_target(frame,cenX,cenY)
#draw_target(frame,200,1)
highgui.cvShowImage('Camera',frame)
highgui.cvShowImage('Hue',hue)
highgui.cvShowImage('Satuation',satuation)
highgui.cvShowImage('Value',value)
highgui.cvShowImage('Laser',laser)
k = highgui.cvWaitKey(10)
if k == " ":
highgui.cvDestroyAllWindows()
highgui.cvReleaseCapture (capture)
sys.exit()
def main(args):
global capture
global hmax, hmin
highgui.cvNamedWindow('Camera', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Hue', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Satuation', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Value', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Laser', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvMoveWindow('Camera', 0, 10)
highgui.cvMoveWindow('Hue', 0, 350)
highgui.cvMoveWindow('Satuation', 360, 10)
highgui.cvMoveWindow('Value', 360, 350)
highgui.cvMoveWindow('Laser', 700, 40)
highgui.cvCreateTrackbar("Brightness Trackbar","Camera",0,255, change_brightness);
highgui.cvCreateTrackbar("hmin Trackbar","Hue",hmin,180, change_hmin);
highgui.cvCreateTrackbar("hmax Trackbar","Hue",hmax,180, change_hmax);
highgui.cvCreateTrackbar("smin Trackbar","Satuation",smin,255, change_smin);
highgui.cvCreateTrackbar("smax Trackbar","Satuation",smax,255, change_smax);
highgui.cvCreateTrackbar("vmin Trackbar","Value",vmin,255, change_vmin);
highgui.cvCreateTrackbar("vmax Trackbar","Value",vmax,255, change_vmax);
print "grabbing camera"
capture = highgui.cvCreateCameraCapture(0)
print "found camera"
highgui.cvSetCaptureProperty(capture,highgui.CV_CAP_PROP_FRAME_WIDTH, 320)
highgui.cvSetCaptureProperty(capture,highgui.CV_CAP_PROP_FRAME_HEIGHT, 240)
frame = highgui.cvQueryFrame(capture)
frameSize = cv.cvGetSize(frame)
hsv = cv.cvCreateImage(frameSize,8,3)
mask = cv.cvCreateImage(frameSize,8,1)
hue = cv.cvCreateImage(frameSize,8,1)
satuation = cv.cvCreateImage(frameSize,8,1)
value = cv.cvCreateImage(frameSize,8,1)
laser = cv.cvCreateImage(frameSize,8,1)
turret = FuzzyController(frameSize.width,frameSize.height,True)
move_count = 0
while 1:
frame = highgui.cvQueryFrame(capture)
cv.cvCvtColor(frame, hsv, cv.CV_BGR2HSV)
#cv.cvInRangeS(hsv,hsv_min,hsv_max,mask)
cv.cvSplit(hsv,hue,satuation,value,None)
cv.cvInRangeS(hue,cv.cvScalar(hmin),cv.cvScalar(hmax),hue)
cv.cvInRangeS(satuation,cv.cvScalar(smin),cv.cvScalar(smax),satuation)
cv.cvInRangeS(value,cv.cvScalar(vmin),cv.cvScalar(vmax),value)
#cv.cvInRangeS(hue,0,180,hue)
cv.cvAnd(hue, value, laser)
#cv.cvAnd(laser, value, laser)
cenX,cenY = averageWhitePoints(laser)
#print cenX,cenY
draw_target(frame,cenX,cenY)
if(cenX != 0 and cenY != 0):# and move_count <= 0):
turret.update(cenX,cenY,False)
"""
turret.reset()
move_count = 3
if(cenX < 100):
turret.left(20)
elif(cenX > 200):
turret.right(20)
if(cenY < 80):
turret.up(40)
elif(cenY > 170):
print "DOWN please.."
turret.down(40)
print cenY
"""
#move_count -= 1
#draw_target(frame,200,1)
highgui.cvShowImage('Camera',frame)
highgui.cvShowImage('Hue',hue)
highgui.cvShowImage('Satuation',satuation)
highgui.cvShowImage('Value',value)
highgui.cvShowImage('Laser',laser)
k = highgui.cvWaitKey(10)
if k == 'q':
sys.exit()
def main(args):
global capture
global hmax, hmin
highgui.cvNamedWindow('Camera', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Hue', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Satuation', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Value', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Laser', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvMoveWindow('Camera', 0, 10)
highgui.cvMoveWindow('Hue', 0, 350)
highgui.cvMoveWindow('Satuation', 360, 10)
highgui.cvMoveWindow('Value', 360, 350)
highgui.cvMoveWindow('Laser', 700, 40)
highgui.cvCreateTrackbar("Brightness Trackbar", "Camera", 0, 255,
change_brightness)
highgui.cvCreateTrackbar("hmin Trackbar", "Hue", hmin, 180, change_hmin)
highgui.cvCreateTrackbar("hmax Trackbar", "Hue", hmax, 180, change_hmax)
highgui.cvCreateTrackbar("smin Trackbar", "Satuation", smin, 255,
change_smin)
highgui.cvCreateTrackbar("smax Trackbar", "Satuation", smax, 255,
change_smax)
highgui.cvCreateTrackbar("vmin Trackbar", "Value", vmin, 255, change_vmin)
highgui.cvCreateTrackbar("vmax Trackbar", "Value", vmax, 255, change_vmax)
print "grabbing camera"
capture = highgui.cvCreateCameraCapture(0)
print "found camera"
highgui.cvSetCaptureProperty(capture, highgui.CV_CAP_PROP_FRAME_WIDTH, 320)
highgui.cvSetCaptureProperty(capture, highgui.CV_CAP_PROP_FRAME_HEIGHT,
240)
frame = highgui.cvQueryFrame(capture)
frameSize = cv.cvGetSize(frame)
hsv = cv.cvCreateImage(frameSize, 8, 3)
mask = cv.cvCreateImage(frameSize, 8, 1)
hue = cv.cvCreateImage(frameSize, 8, 1)
satuation = cv.cvCreateImage(frameSize, 8, 1)
value = cv.cvCreateImage(frameSize, 8, 1)
laser = cv.cvCreateImage(frameSize, 8, 1)
while 1:
frame = highgui.cvQueryFrame(capture)
cv.cvCvtColor(frame, hsv, cv.CV_BGR2HSV)
#cv.cvInRangeS(hsv,hsv_min,hsv_max,mask)
cv.cvSplit(hsv, hue, satuation, value, None)
cv.cvInRangeS(hue, hmin, hmax, hue)
cv.cvInRangeS(satuation, smin, smax, satuation)
cv.cvInRangeS(value, vmin, vmax, value)
#cv.cvInRangeS(hue,0,180,hue)
cv.cvAnd(hue, value, laser)
#cv.cvAnd(laser, value, laser)
cenX, cenY = averageWhitePoints(laser)
#print cenX,cenY
draw_target(frame, cenX, cenY)
#draw_target(frame,200,1)
highgui.cvShowImage('Camera', frame)
highgui.cvShowImage('Hue', hue)
highgui.cvShowImage('Satuation', satuation)
highgui.cvShowImage('Value', value)
highgui.cvShowImage('Laser', laser)
k = highgui.cvWaitKey(10)
if k == " ":
highgui.cvDestroyAllWindows()
highgui.cvReleaseCapture(capture)
sys.exit()
frame = highgui.cvQueryFrame (capture)
if frame is None:
# no image captured... end the processing
break
# mirror the captured image
cv.cvFlip (frame, None, 1)
# compute the hsv version of the image
cv.cvCvtColor (frame, hsv, cv.CV_BGR2HSV)
# compute which pixels are in the wanted range
cv.cvInRangeS (hsv, hsv_min, hsv_max, mask)
# extract the hue from the hsv array
cv.cvSplit (hsv, hue, None, None, None)
# select the rectangle of interest in the hue/mask arrays
hue_roi = cv.cvGetSubRect (hue, selection)
mask_roi = cv.cvGetSubRect (mask, selection)
# it's time to compute the histogram
cv.cvCalcHist (hue_roi, hist, 0, mask_roi)
# extract the min and max value of the histogram
min_val, max_val = cv.cvGetMinMaxHistValue (hist, None, None)
# compute the scale factor
if max_val > 0:
scale = 255. / max_val
else:
frame = highgui.cvQueryFrame(capture)
if frame is None:
# no image captured... end the processing
break
# mirror the captured image
#cv.cvFlip (frame, None, 1)
# compute the hsv version of the image
cv.cvCvtColor(frame, hsv, cv.CV_BGR2HSV)
# compute which pixels are in the wanted range
cv.cvInRangeS(hsv, hsv_min, hsv_max, mask)
# extract the hue from the hsv array
cv.cvSplit(hsv, hue, None, None, None)
# select the rectangle of interest in the hue/mask arrays
hue_roi = cv.cvGetSubRect(hue, selection)
mask_roi = cv.cvGetSubRect(mask, selection)
# it's time to compute the histogram
cv.cvCalcHist(hue_roi, hist, 0, mask_roi)
# extract the min and max value of the histogram
min_val, max_val, min_idx, max_idx = cv.cvGetMinMaxHistValue(hist)
# compute the scale factor
if max_val > 0:
scale = 255. / max_val
else:
def detect_squares(self, img_grey, img_orig): """ Find squares within the video stream and draw them """ cv.cvClearMemStorage(self.faces_storage) N = 11 thresh = 5 sz = cv.cvSize(img_grey.width & -2, img_grey.height & -2) timg = cv.cvCloneImage(img_orig) pyr = cv.cvCreateImage(cv.cvSize(sz.width/2, sz.height/2), 8, 3) # create empty sequence that will contain points - # 4 points per square (the square's vertices) squares = cv.cvCreateSeq(0, cv.sizeof_CvSeq, cv.sizeof_CvPoint, self.squares_storage) squares = cv.CvSeq_CvPoint.cast(squares) # select the maximum ROI in the image # with the width and height divisible by 2 subimage = cv.cvGetSubRect(timg, cv.cvRect(0, 0, sz.width, sz.height)) cv.cvReleaseImage(timg) # down-scale and upscale the image to filter out the noise cv.cvPyrDown(subimage, pyr, 7) cv.cvPyrUp(pyr, subimage, 7) cv.cvReleaseImage(pyr) tgrey = cv.cvCreateImage(sz, 8, 1) # find squares in every color plane of the image for c in range(3): # extract the c-th color plane channels = [None, None, None] channels[c] = tgrey cv.cvSplit(subimage, channels[0], channels[1], channels[2], None) for l in range(N): # hack: use Canny instead of zero threshold level. # Canny helps to catch squares with gradient shading if(l == 0): # apply Canny. Take the upper threshold from slider # and set the lower to 0 (which forces edges merging) cv.cvCanny(tgrey, img_grey, 0, thresh, 5) # dilate canny output to remove potential # holes between edge segments cv.cvDilate(img_grey, img_grey, None, 1) else: # apply threshold if l!=0: # tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0 cv.cvThreshold(tgrey, img_grey, (l+1)*255/N, 255, cv.CV_THRESH_BINARY) # find contours and store them all as a list count, contours = cv.cvFindContours(img_grey, self.squares_storage, cv.sizeof_CvContour, cv.CV_RETR_LIST, cv.CV_CHAIN_APPROX_SIMPLE, cv.cvPoint(0,0)) if not contours: continue # test each contour for contour in contours.hrange(): # approximate contour with accuracy proportional # to the contour perimeter result = cv.cvApproxPoly(contour, cv.sizeof_CvContour, self.squares_storage, cv.CV_POLY_APPROX_DP, cv.cvContourPerimeter(contours)*0.02, 0) # square contours should have 4 vertices after approximation # relatively large area (to filter out noisy contours) # and be convex. # Note: absolute value of an area is used because # area may be positive or negative - in accordance with the # contour orientation if(result.total == 4 and abs(cv.cvContourArea(result)) > 1000 and cv.cvCheckContourConvexity(result)): s = 0 for i in range(5): # find minimum angle between joint # edges (maximum of cosine) if(i >= 2): t = abs(self.squares_angle(result[i], result[i-2], result[i-1])) if s<t: s = t # if cosines of all angles are small # (all angles are ~90 degree) then write quandrange # vertices to resultant sequence if(s < 0.3): for i in range(4): squares.append(result[i]) cv.cvReleaseImage(tgrey) return squares
def main(args):
global capture
global hmax, hmin
highgui.cvNamedWindow('Hue', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Camera', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Saturation', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Value', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Laser', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvMoveWindow('Camera', 0, 10)
highgui.cvMoveWindow('Hue', 0, 350)
highgui.cvMoveWindow('Saturation', 360, 10)
highgui.cvMoveWindow('Value', 360, 350)
highgui.cvMoveWindow('Laser', 700, 40)
highgui.cvCreateTrackbar("Brightness Trackbar","Camera",0,255, change_brightness);
highgui.cvCreateTrackbar("hmin Trackbar","Hue",hmin,180, change_hmin);
highgui.cvCreateTrackbar("hmax Trackbar","Hue",hmax,180, change_hmax);
highgui.cvCreateTrackbar("smin Trackbar","Saturation",smin,255, change_smin);
highgui.cvCreateTrackbar("smax Trackbar","Saturation",smax,255, change_smax);
highgui.cvCreateTrackbar("vmin Trackbar","Value",vmin,255, change_vmin);
highgui.cvCreateTrackbar("vmax Trackbar","Value",vmax,255, change_vmax);
print "grabbing camera"
capture = highgui.cvCreateCameraCapture(0)
print "found camera"
highgui.cvSetCaptureProperty(capture,highgui.CV_CAP_PROP_FRAME_WIDTH, iwidth)
highgui.cvSetCaptureProperty(capture,highgui.CV_CAP_PROP_FRAME_HEIGHT, iheight)
frame = highgui.cvQueryFrame(capture)
frameSize = cv.cvGetSize(frame)
hsv = cv.cvCreateImage(frameSize,8,3)
mask = cv.cvCreateImage(frameSize,8,1)
hue = cv.cvCreateImage(frameSize,8,1)
saturation = cv.cvCreateImage(frameSize,8,1)
value = cv.cvCreateImage(frameSize,8,1)
laser = cv.cvCreateImage(frameSize,8,1)
while 1:
frame = highgui.cvQueryFrame(capture)
cv.cvCvtColor(frame, hsv, cv.CV_BGR2HSV)
#cv.cvInRangeS(hsv,hsv_min,hsv_max,mask)
cv.cvSplit(hsv,hue,saturation,value,None)
#print hmin, hmax
cv.cvInRangeS(hue,cv.cvScalar(hmin),cv.cvScalar(hmax),hue)
cv.cvInRangeS(saturation,cv.cvScalar(smin),cv.cvScalar(smax),saturation)
cv.cvInRangeS(value,cv.cvScalar(vmin),cv.cvScalar(vmax),value)
#cv.cvInRangeS(hue,cv.cvScalar(0),cv.cvScalar(180),hue)
cv.cvAnd(hue, value, laser)
#cv.cvAnd(laser, value, laser)
# stupid filter
#removeErrantPoints(laser)
cenX,cenY = averageWhitePoints(laser)
px = iwidth/2 - cenX
dis = 57.18832855 / ( px - 5.702350176) + .05753797721
print cenX,px,dis
draw_target(frame,cenX,cenY)
#draw_target(frame,200,1)
highgui.cvShowImage('Hue',hue)
highgui.cvShowImage('Camera',frame)
highgui.cvShowImage('Saturation',saturation)
highgui.cvShowImage('Value',value)
highgui.cvShowImage('Laser',laser)
highgui.cvWaitKey(10)
def main():
print "OpenCV version: %s (%d, %d, %d)" % (cv.CV_VERSION,
cv.CV_MAJOR_VERSION,
cv.CV_MINOR_VERSION,
cv.CV_SUBMINOR_VERSION)
# create windows
create_and_position_window('Thresholded_HSV_Image', 10, 10)
create_and_position_window('RGB_VideoFrame', 10+cam_width, 10)
create_and_position_window('Hue', 10, 10+cam_height)
create_and_position_window('Saturation', 210, 10+cam_height)
create_and_position_window('Value', 410, 10+cam_height)
create_and_position_window('LaserPointer', 0,0)
capture = setup_camera_capture()
# create images for the different channels
h_img = cv.cvCreateImage (cv.cvSize (cam_width,cam_height), 8, 1)
s_img = cv.cvCreateImage (cv.cvSize (cam_width,cam_height), 8, 1)
v_img = cv.cvCreateImage (cv.cvSize (cam_width,cam_height), 8, 1)
laser_img = cv.cvCreateImage (cv.cvSize (cam_width,cam_height), 8, 1)
cv.cvSetZero(h_img)
cv.cvSetZero(s_img)
cv.cvSetZero(v_img)
cv.cvSetZero(laser_img)
while True:
# 1. capture the current image
frame = highgui.cvQueryFrame (capture)
if frame is None:
# no image captured... end the processing
break
hsv_image = cv.cvCloneImage(frame) # temporary copy of the frame
cv.cvCvtColor(frame, hsv_image, cv.CV_BGR2HSV) # convert to HSV
# split the video frame into color channels
cv.cvSplit(hsv_image, h_img, s_img, v_img, None)
# Threshold ranges of HSV components.
cv.cvInRangeS(h_img, hmin, hmax, h_img)
cv.cvInRangeS(s_img, smin, smax, s_img)
cv.cvInRangeS(v_img, vmin, vmax, v_img)
# Perform an AND on HSV components to identify the laser!
cv.cvAnd(h_img, v_img, laser_img)
# This actually Worked OK for me without using Saturation.
#cv.cvAnd(laser_img, s_img,laser_img)
# Merge the HSV components back together.
cv.cvMerge(h_img, s_img, v_img, None, hsv_image)
#-----------------------------------------------------
# NOTE: default color space in OpenCV is BGR!!
# we can now display the images
highgui.cvShowImage ('Thresholded_HSV_Image', hsv_image)
highgui.cvShowImage ('RGB_VideoFrame', frame)
highgui.cvShowImage ('Hue', h_img)
highgui.cvShowImage ('Saturation', s_img)
highgui.cvShowImage ('Value', v_img)
highgui.cvShowImage('LaserPointer', laser_img)
# handle events
k = highgui.cvWaitKey (10)
if k == '\x1b' or k == 'q':
# user has press the ESC key, so exit
break
def detect_squares(self, img):
""" Find squares within the video stream and draw them """
N = 11
thresh = 5
sz = cv.cvSize(img.width & -2, img.height & -2)
timg = cv.cvCloneImage(img)
gray = cv.cvCreateImage(sz, 8, 1)
pyr = cv.cvCreateImage(cv.cvSize(sz.width / 2, sz.height / 2), 8, 3)
# create empty sequence that will contain points -
# 4 points per square (the square's vertices)
squares = cv.cvCreateSeq(0, cv.sizeof_CvSeq, cv.sizeof_CvPoint,
self.storage)
squares = cv.CvSeq_CvPoint.cast(squares)
# select the maximum ROI in the image
# with the width and height divisible by 2
subimage = cv.cvGetSubRect(timg, cv.cvRect(0, 0, sz.width, sz.height))
# down-scale and upscale the image to filter out the noise
cv.cvPyrDown(subimage, pyr, 7)
cv.cvPyrUp(pyr, subimage, 7)
tgray = cv.cvCreateImage(sz, 8, 1)
# find squares in every color plane of the image
for c in range(3):
# extract the c-th color plane
channels = [None, None, None]
channels[c] = tgray
cv.cvSplit(subimage, channels[0], channels[1], channels[2], None)
for l in range(N):
# hack: use Canny instead of zero threshold level.
# Canny helps to catch squares with gradient shading
if (l == 0):
# apply Canny. Take the upper threshold from slider
# and set the lower to 0 (which forces edges merging)
cv.cvCanny(tgray, gray, 0, thresh, 5)
# dilate canny output to remove potential
# holes between edge segments
cv.cvDilate(gray, gray, None, 1)
else:
# apply threshold if l!=0:
# tgray(x,y) = gray(x,y) < (l+1)*255/N ? 255 : 0
cv.cvThreshold(tgray, gray, (l + 1) * 255 / N, 255,
cv.CV_THRESH_BINARY)
# find contours and store them all as a list
count, contours = cv.cvFindContours(gray, self.storage,
cv.sizeof_CvContour,
cv.CV_RETR_LIST,
cv.CV_CHAIN_APPROX_SIMPLE,
cv.cvPoint(0, 0))
if not contours:
continue
# test each contour
for contour in contours.hrange():
# approximate contour with accuracy proportional
# to the contour perimeter
result = cv.cvApproxPoly(
contour, cv.sizeof_CvContour, self.storage,
cv.CV_POLY_APPROX_DP,
cv.cvContourPerimeter(contours) * 0.02, 0)
# square contours should have 4 vertices after approximation
# relatively large area (to filter out noisy contours)
# and be convex.
# Note: absolute value of an area is used because
# area may be positive or negative - in accordance with the
# contour orientation
if (result.total == 4
and abs(cv.cvContourArea(result)) > 1000
and cv.cvCheckContourConvexity(result)):
s = 0
for i in range(5):
# find minimum angle between joint
# edges (maximum of cosine)
if (i >= 2):
t = abs(
self.squares_angle(result[i],
result[i - 2],
result[i - 1]))
if s < t:
s = t
# if cosines of all angles are small
# (all angles are ~90 degree) then write quandrange
# vertices to resultant sequence
if (s < 0.3):
for i in range(4):
squares.append(result[i])
i = 0
while i < squares.total:
pt = []
# read 4 vertices
pt.append(squares[i])
pt.append(squares[i + 1])
pt.append(squares[i + 2])
pt.append(squares[i + 3])
# draw the square as a closed polyline
cv.cvPolyLine(img, [pt], 1, cv.CV_RGB(0, 255, 0), 3, cv.CV_AA, 0)
i += 4
return img
def compute_saliency(image):
global thresh
global scale
saliency_scale = int(math.pow(2,scale));
bw_im1 = cv.cvCreateImage(cv.cvGetSize(image), cv.IPL_DEPTH_8U,1)
cv.cvCvtColor(image, bw_im1, cv.CV_BGR2GRAY)
bw_im = cv.cvCreateImage(cv.cvSize(saliency_scale,saliency_scale), cv.IPL_DEPTH_8U,1)
cv.cvResize(bw_im1, bw_im)
highgui.cvShowImage("BW", bw_im)
realInput = cv.cvCreateImage( cv.cvGetSize(bw_im), cv.IPL_DEPTH_32F, 1);
imaginaryInput = cv.cvCreateImage( cv.cvGetSize(bw_im), cv.IPL_DEPTH_32F, 1);
complexInput = cv.cvCreateImage( cv.cvGetSize(bw_im), cv.IPL_DEPTH_32F, 2);
cv.cvScale(bw_im, realInput, 1.0, 0.0);
cv.cvZero(imaginaryInput);
cv.cvMerge(realInput, imaginaryInput, None, None, complexInput);
dft_M = saliency_scale #cv.cvGetOptimalDFTSize( bw_im.height - 1 );
dft_N = saliency_scale #cv.cvGetOptimalDFTSize( bw_im.width - 1 );
dft_A = cv.cvCreateMat( dft_M, dft_N, cv.CV_32FC2 );
image_Re = cv.cvCreateImage( cv.cvSize(dft_N, dft_M), cv.IPL_DEPTH_32F, 1);
image_Im = cv.cvCreateImage( cv.cvSize(dft_N, dft_M), cv.IPL_DEPTH_32F, 1);
# copy A to dft_A and pad dft_A with zeros
tmp = cv.cvGetSubRect( dft_A, cv.cvRect(0,0, bw_im.width, bw_im.height));
cv.cvCopy( complexInput, tmp, None );
if(dft_A.width > bw_im.width):
tmp = cv.cvGetSubRect( dft_A, cv.cvRect(bw_im.width,0, dft_N - bw_im.width, bw_im.height));
cv.cvZero( tmp );
cv.cvDFT( dft_A, dft_A, cv.CV_DXT_FORWARD, complexInput.height );
cv.cvSplit( dft_A, image_Re, image_Im, None, None );
# Compute the phase angle
image_Mag = cv.cvCreateImage(cv.cvSize(dft_N, dft_M), cv.IPL_DEPTH_32F, 1);
image_Phase = cv.cvCreateImage(cv.cvSize(dft_N, dft_M), cv.IPL_DEPTH_32F, 1);
#compute the phase of the spectrum
cv.cvCartToPolar(image_Re, image_Im, image_Mag, image_Phase, 0)
log_mag = cv.cvCreateImage(cv.cvSize(dft_N, dft_M), cv.IPL_DEPTH_32F, 1);
cv.cvLog(image_Mag, log_mag)
#Box filter the magnitude, then take the difference
image_Mag_Filt = cv.cvCreateImage(cv.cvSize(dft_N, dft_M), cv.IPL_DEPTH_32F, 1);
filt = cv.cvCreateMat(3,3, cv.CV_32FC1);
cv.cvSet(filt,cv.cvScalarAll(-1.0/9.0))
cv.cvFilter2D(log_mag, image_Mag_Filt, filt, cv.cvPoint(-1,-1))
cv.cvAdd(log_mag, image_Mag_Filt, log_mag, None)
cv.cvExp(log_mag, log_mag)
cv.cvPolarToCart(log_mag, image_Phase, image_Re, image_Im,0);
cv.cvMerge(image_Re, image_Im, None, None, dft_A)
cv.cvDFT( dft_A, dft_A, cv.CV_DXT_INVERSE, complexInput.height)
tmp = cv.cvGetSubRect( dft_A, cv.cvRect(0,0, bw_im.width, bw_im.height));
cv.cvCopy( tmp, complexInput, None );
cv.cvSplit(complexInput, realInput, imaginaryInput, None, None)
min, max = cv.cvMinMaxLoc(realInput);
#cv.cvScale(realInput, realInput, 1.0/(max-min), 1.0*(-min)/(max-min));
cv.cvSmooth(realInput, realInput);
threshold = thresh/100.0*cv.cvAvg(realInput)[0]
cv.cvThreshold(realInput, realInput, threshold, 1.0, cv.CV_THRESH_BINARY)
tmp_img = cv.cvCreateImage(cv.cvGetSize(bw_im1),cv.IPL_DEPTH_32F, 1)
cv.cvResize(realInput,tmp_img)
cv.cvScale(tmp_img, bw_im1, 255,0)
return bw_im1
def main(args):
global capture
global hmax, hmin
global stats, startTime
highgui.cvNamedWindow('Camera', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Red Hue', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Green Hue', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Value', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Red Laser', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvNamedWindow('Green Laser', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvMoveWindow('Camera', 0, 10)
highgui.cvMoveWindow('Value', 10, 420)
highgui.cvMoveWindow('Red Laser', 360, 10)
highgui.cvMoveWindow('Green Laser', 360, 360)
highgui.cvMoveWindow('Red Hue',700, 10 )
highgui.cvMoveWindow('Green Hue',700, 420)
highgui.cvCreateTrackbar("Brightness Trackbar","Camera",0,255, change_brightness);
highgui.cvCreateTrackbar("vmin Trackbar","Value",vmin,255, change_vmin);
highgui.cvCreateTrackbar("vmax Trackbar","Value",vmax,255, change_vmax);
highgui.cvCreateTrackbar("red hmin Trackbar","Red Hue",red_hmin,180, change_red_hmin);
highgui.cvCreateTrackbar("red hmax Trackbar","Red Hue",red_hmax,180, change_red_hmax);
highgui.cvCreateTrackbar("green hmin Trackbar","Green Hue",green_hmin,180, change_green_hmin);
highgui.cvCreateTrackbar("green hmax Trackbar","Green Hue",green_hmax,180, change_green_hmax);
print "grabbing camera"
capture = highgui.cvCreateCameraCapture(0)
print "found camera"
highgui.cvSetCaptureProperty(capture,highgui.CV_CAP_PROP_FRAME_WIDTH, iwidth)
highgui.cvSetCaptureProperty(capture,highgui.CV_CAP_PROP_FRAME_HEIGHT, iheight)
frame = highgui.cvQueryFrame(capture)
frameSize = cv.cvGetSize(frame)
hsv = cv.cvCreateImage(frameSize,8,3)
mask = cv.cvCreateImage(frameSize,8,1)
red_hue = cv.cvCreateImage(frameSize,8,1)
green_hue = cv.cvCreateImage(frameSize,8,1)
saturation = cv.cvCreateImage(frameSize,8,1)
value = cv.cvCreateImage(frameSize,8,1)
red_laser = cv.cvCreateImage(frameSize,8,1)
green_laser = cv.cvCreateImage(frameSize,8,1)
turret = FuzzyController(frameSize.width,frameSize.height,True)
while 1:
frame = highgui.cvQueryFrame(capture)
cv.cvCvtColor(frame, hsv, cv.CV_BGR2HSV)
cv.cvSplit(hsv,red_hue,saturation,value,None)
cv.cvSplit(hsv,green_hue,saturation,value,None)
cv.cvInRangeS(red_hue, cv.cvScalar(red_hmin), cv.cvScalar(red_hmax), red_hue)
cv.cvInRangeS(green_hue, cv.cvScalar(green_hmin), cv.cvScalar(green_hmax), green_hue)
cv.cvInRangeS(value, cv.cvScalar(vmin), cv.cvScalar(vmax), value)
cv.cvAnd(red_hue, value, red_laser)
cv.cvAnd(green_hue, value, green_laser)
green_cenX,green_cenY = averageWhitePoints(green_laser)
draw_target(frame, green_cenX, green_cenY, "GREEN")
red_cenX, red_cenY = averageWhitePoints(red_laser)
draw_target(frame, red_cenX, red_cenY, "RED")
if(green_cenX >= 0 and green_cenY >= 0):# and move_count <= 0):
turret.update(green_cenX,green_cenY)
highgui.cvShowImage('Camera',frame)
highgui.cvShowImage('Red Hue', red_hue)
highgui.cvShowImage('Green Hue', green_hue)
highgui.cvShowImage('Value',value)
highgui.cvShowImage('Red Laser',red_laser)
highgui.cvShowImage('Green Laser',green_laser)
if stats:
printRunningStats((green_cenX, green_cenY), (red_cenX, red_cenY))
k = highgui.cvWaitKey(10)
if k == '\x1b' or k == 'q':
sys.exit()
if k == 'p':
if stats:
printTotalStats()
stats = False
else:
startTime = time()
stats = True
cv.cvZero(img_h)
cv.cvZero(img_s)
cv.cvZero(img_v)
cv.cvZero(thresh_mask)
highgui.cvShowImage("Input", img)
# 5x5 Gaussian Blur
cv.cvSmooth(img, img, cv.CV_GAUSSIAN, 5, 5)
# convert to HSV
cv.cvCvtColor(img, img, cv.CV_BGR2HSV)
# threshold bad values
cv.cvInRangeS(img, hsv_min, hsv_max, thresh_mask)
cv.cvAnd(thresh_mask, mask_bw, thresh_mask)
# Hue(0,180), Saturation(0,255), Value(0,255)
cv.cvSplit(img, img_h, img_s, img_v, 0)
# calculate histogram
cv.cvCalcHist(img_h, h_hue, 0, thresh_mask)
cv.cvCalcHist(img_s, h_sat, 0, thresh_mask)
cv.cvCalcHist(img_v, h_val, 0, thresh_mask)
# Don't normalize, use total mask pixels to calculate relative importance
# cv.cvNormalizeHist(h_hue, 180)
# cv.cvNormalizeHist(h_sat, 255)
# cv.cvNormalizeHist(h_val, 255)
# minv,maxv,minp,maxp = cv.cvMinMaxLoc(img_h)
# print minv,maxv
cv.cvZero(hist_hue_img)
# hue_min,hue_max,min_loc,max_loc = cv.cvGetMinMaxHistValue(h_hue)
red = cv.cvCreateImage(frame_size, 8, 1)
green = cv.cvCreateImage(frame_size, 8, 1)
blue = cv.cvCreateImage(frame_size, 8, 1)
while 1:
# 1. capture the current image
frame = highgui.cvQueryFrame (capture)
if frame is None:
# no image captured... end the processing
break
# compute the hsv version of the image
cv.cvCvtColor(frame, hsv, cv.CV_BGR2HSV)
# compute the hue/sat/value from the hsv image
cv.cvSplit(hsv, hue, saturation, value, None)
cv.cvSplit(frame, blue, green, red, None);
cv.cvCvtScale(value, val_scale, 1/100.);
cv.cvCvtScale(val_scale, value, 1);
# handle events
k = highgui.cvWaitKey (10)
# we can now display the images
highgui.cvShowImage('Camera', frame)
highgui.cvShowImage('HUE', hue)
highgui.cvShowImage('SATURATION', saturation)
highgui.cvShowImage('VALUE', value)
highgui.cvShowImage('RED', red)
highgui.cvShowImage('GREEN', green)
