def main():
# Initialization
highgui.cvNamedWindow("Guardian", 1)
signal.signal(signal.SIGINT, handler)
# Stage
#robot = playerc.playerc_client(None, "localhost", 6665)
# Corobot
robot = playerc.playerc_client(None, "corobot-w.wifi.wpi.edu", 6665)
robot.connect()
p2dproxy = playerc.playerc_position2d(robot, 0)
p2dproxy.subscribe(playerc.PLAYERC_OPEN_MODE)
p2dproxy.get_geom()
robot.read()
while True:
image = highgui.cvQueryFrame(camera)
detectObject(image)
p2dproxy.set_cmd_vel(speed[0], 0, speed[1], 0)
draw_gui(image)
highgui.cvShowImage("Guardian", image)
if highgui.cvWaitKey(20) != -1:
break
highgui.cvDestroyWindow("Guardian")
p2dproxy.set_cmd_vel(0, 0, 0, 0)
def run(self, images, display=True, verbose=False, debug=False):
left_detection, left_intensity_motion_activations, left_image, left_combined_masks = self.left_detector.detect(
images[0])
self.record(left_detection, left_image,
left_intensity_motion_activations)
right_detection, right_intensity_motion_activations, right_image, right_combined_masks = self.right_detector.detect(
images[1])
self.record(right_detection, right_image,
right_intensity_motion_activations)
if debug:
motion, intensity = self.left_detector.get_motion_intensity_images(
)
show_processed(left_image,
[left_combined_masks, motion, intensity],
left_detection, left_intensity_motion_activations,
self.left_detector)
elif display:
draw_detection(left_image, left_detection)
hg.cvShowImage('video', left_image)
if left_detection != None and right_detection != None:
if (self.expecting_correct_labels and self.expected_class == 0):
print 'EmbodiedLaserDetector: output suppressed, classified positive in both cameras.'
else:
return self.triangulate(left_detection, right_detection)
return None
def imagesc(self, im, clims=None):
"""
Display a normalized version of the image
"""
if (self.currentWindow == -1):
self.display()
# don't normalize multichannel image
#if(im.nChannels>1):
# if(im.depth!=cv.IPL_DEPTH_8U):
# im2 = cvCreateImage( cvSize(im.width, im.height), cv.IPL_DEPTH_8U, im.nChannels)
# cvScale(im, im2)
# im = im2
# cvShowImage(self.currentWindowName, im)
# return self.currentWindow
# normalize image
if clims:
[minv, maxv] = clims
else:
[minv, maxv] = cvMinMaxLoc(im)
if maxv != minv:
s = 255.0 / (maxv - minv)
shift = 255 * (-minv) / (maxv - minv)
else:
s = 1.0
shift = -maxv
im2 = array(size(im), 'uint8')
cvConvertScale(im, im2, s, shift)
cvShowImage(self.currentWindowName, im2)
def imagesc(self,im, clims=None):
"""
Display a normalized version of the image
"""
if(self.currentWindow==-1):
self.display()
# don't normalize multichannel image
#if(im.nChannels>1):
# if(im.depth!=cv.IPL_DEPTH_8U):
# im2 = cvCreateImage( cvSize(im.width, im.height), cv.IPL_DEPTH_8U, im.nChannels)
# cvScale(im, im2)
# im = im2
# cvShowImage(self.currentWindowName, im)
# return self.currentWindow
# normalize image
if clims:
[minv, maxv] = clims
else:
[minv,maxv] = cvMinMaxLoc(im)
if maxv != minv:
s = 255.0/(maxv-minv)
shift = 255*(-minv)/(maxv-minv)
else:
s = 1.0
shift = -maxv
im2 = array( size(im), 'uint8' )
cvConvertScale(im, im2, s, shift)
cvShowImage(self.currentWindowName, im2)
def display_array(iar):
left = ut.ros2cv(iar.images[0])
right = ut.ros2cv(iar.images[1])
hg.cvShowImage('channel 1', left)
hg.cvShowImage('channel 2', right)
hg.cvWaitKey(5)
def main():
print "FaceIn! an OpenCV Python Face Recognition Program"
highgui.cvNamedWindow ('Camera', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvMoveWindow ('Camera', 10, 10)
device = 0 #use first device found
capture = highgui.cvCreateCameraCapture (device)
frame = highgui.cvQueryFrame (capture)
frame_size = cv.cvGetSize (frame)
fps = 30
while 1:
frame = highgui.cvQueryFrame (capture)
detectFace(frame)
# display the frames to have a visual output
highgui.cvShowImage ('Camera', frame)
# handle events
k = highgui.cvWaitKey (5)
if k % 0x100 == 27:
# user has press the ESC key, so exit
quit()
def main():
print "FaceIn! an OpenCV Python Face Recognition Program"
highgui.cvNamedWindow('Camera', highgui.CV_WINDOW_AUTOSIZE)
highgui.cvMoveWindow('Camera', 10, 10)
device = 0 #use first device found
capture = highgui.cvCreateCameraCapture(device)
frame = highgui.cvQueryFrame(capture)
frame_size = cv.cvGetSize(frame)
fps = 30
while 1:
frame = highgui.cvQueryFrame(capture)
detectFace(frame)
# display the frames to have a visual output
highgui.cvShowImage('Camera', frame)
# handle events
k = highgui.cvWaitKey(5)
if k % 0x100 == 27:
# user has press the ESC key, so exit
quit()
def main():
# Initialization
highgui.cvNamedWindow("Guardian", 1)
signal.signal(signal.SIGINT, handler)
# Stage
#robot = playerc.playerc_client(None, "localhost", 6665)
# Corobot
robot = playerc.playerc_client(None, "corobot-w.wifi.wpi.edu", 6665)
robot.connect()
p2dproxy = playerc.playerc_position2d(robot, 0)
p2dproxy.subscribe(playerc.PLAYERC_OPEN_MODE)
p2dproxy.get_geom()
robot.read()
while True:
image = highgui.cvQueryFrame(camera)
detectObject(image)
p2dproxy.set_cmd_vel(speed[0], 0, speed[1], 0)
draw_gui(image)
highgui.cvShowImage("Guardian", image)
if highgui.cvWaitKey(20) != -1:
break
highgui.cvDestroyWindow("Guardian")
p2dproxy.set_cmd_vel(0, 0, 0, 0)
def on_trackbar (position):
# create the image for putting in it the founded contours
contours_image = cv.cvCreateImage (cv.cvSize (_SIZE, _SIZE), 8, 3)
# compute the real level of display, given the current position
levels = position - 3
# initialisation
_contours = contours
if levels <= 0:
# zero or negative value
# => get to the nearest face to make it look more funny
_contours = contours.h_next.h_next.h_next
# first, clear the image where we will draw contours
cv.cvSetZero (contours_image)
# draw contours in red and green
cv.cvDrawContours (contours_image, _contours,
_red, _green,
levels, 3, cv.CV_AA,
cv.cvPoint (0, 0))
# finally, show the image
highgui.cvShowImage ("contours", contours_image)
def on_trackbar(position):
# create the image for putting in it the founded contours
contours_image = cv.cvCreateImage(cv.cvSize(_SIZE, _SIZE), 8, 3)
# compute the real level of display, given the current position
levels = position - 3
# initialisation
_contours = contours
if levels <= 0:
# zero or negative value
# => get to the nearest face to make it look more funny
_contours = contours.h_next.h_next.h_next
# first, clear the image where we will draw contours
cv.cvSetZero(contours_image)
# draw contours in red and green
cv.cvDrawContours(contours_image, _contours, _red, _green, levels, 3,
cv.CV_AA, cv.cvPoint(0, 0))
# finally, show the image
highgui.cvShowImage("contours", contours_image)
def main():
usage = "%prog [options] <imgfile>"
version = "%prog 0.2\n Longbin Chen, [email protected]"
oparser = optparse.OptionParser(usage=usage, version=version)
oparser.add_option('-d', '--display', action="store_true", dest = 'display', default = False, help = 'display the image')
oparser.add_option('-m', '--drawnumber', action="store_true", dest = 'drawnumber', default = False, help = 'display the point numbers')
oparser.add_option('-n', '--number', dest = 'num', type='int',default = 200 , help = 'the number of feature points')
oparser.add_option('-t', '--threshold', dest = 'threshold', type='int',default = 100 , help = 'the threshold for image binarification')
oparser.add_option('-o', '--output', dest = 'output', default = None, help = 'output file')
oparser.add_option('-s', '--save', dest = 'save', default = None, help = 'save the img file')
(options, args) = oparser.parse_args(sys.argv)
if len(args) != 2:
oparser.parse_args([sys.argv[0], "--help"])
sys.exit(1)
ct = ExtractMSS()
ct.GetContour(args[1], options)
if (options.display):
ct.start = options.threshold
ct.DrawKeyPoints()
highgui.cvNamedWindow ("contour", 1)
highgui.cvShowImage ("contour", ct.drawimg)
highgui.cvWaitKey (0)
if (options.output):
ct.mss.save(options.output)
if (options.save):
highgui.cvSaveImage(options.save, ct.drawimg)
def show_image(window_name, img, wait=False):
hg.cvStartWindowThread()
RESIZABLE = 0
hg.cvNamedWindow(window_name, RESIZABLE)
hg.cvShowImage(window_name, img)
if wait:
print 'show_image: press any key to continue..'
cv.highgui.cvWaitKey()
def show(fr,width,height,name):
image = cv.cvCreateImage(cv.cvSize (width, height),8,1)
l = 0
for j in range(0,image.width):
for i in range(0,image.height):
cv.cvSet2D(image,i,j,int(fr[l][0]));
l=l+1
highgui.cvShowImage(name,image)
highgui.cvWaitKey(1000/29)
def image(self, im):
"""
Display image as is -- probably not what you'd expect for FP or integer images
"""
if(self.currentWindow==-1):
self.display()
cvShowImage(self.currentWindowName,im)
return self.currentWindow
def image(self, im):
"""
Display image as is -- probably not what you'd expect for FP or integer images
"""
if (self.currentWindow == -1):
self.display()
cvShowImage(self.currentWindowName, im)
return self.currentWindow
def main(argv):
# Frames per second
fps = 20
tux_pos = 5
tux_pos_min = 0.0
tux_pos_max = 9.0
try:
opts, args = getopt.getopt(argv, "fps", ["framerate=",])
except getopt.GetoptError:
sys.exit(2)
for opt, arg in opts:
if opt in ("-fps", "--framerate"):
fps = arg
camera = highgui.cvCreateCameraCapture(0)
while True:
highgui.cvNamedWindow('Camera', 1)
im = highgui.cvQueryFrame(camera)
if im is None:
break
# mirror
opencv.cv.cvFlip(im, None, 1)
# positions = face.detect(im, 'haarcascade_data/haarcascade_profileface.xml')
positions = face.detect(im, 'haarcascade_data/haarcascade_frontalface_alt2.xml')
# if not positions:
# positions = face.detect(im, 'haarcascade_data/haarcascade_frontalface_alt2.xml')
# display webcam image
highgui.cvShowImage('Camera', im)
# Division of the screen to count as "walking" motion to trigger tux
image_size = opencv.cvGetSize(im)
motion_block = image_size.width / 9
if positions:
mp = None
for position in positions:
if not mp or mp['width'] > position['width']:
mp = position
pos = (mp['x'] + (mp['width'] / 2)) / motion_block
print "tux pos: %f" % tux_pos
print "pos: %f" % pos
if pos != tux_pos:
if tux_pos > pos:
move_tux_right(tux_pos - pos)
elif tux_pos < pos:
move_tux_left(pos - tux_pos)
tux_pos = pos
if highgui.cvWaitKey(fps) >= 0:
highgui.cvDestroyWindow('Camera')
sys.exit(0)
def display(vec, name):
patch, context = reconstruct_input(vec)
patch = scale_image(patch, 5)
context = scale_image(context, 5)
hg.cvSaveImage(name + '_patch.png', patch)
hg.cvSaveImage(name + '_context.png', context)
hg.cvShowImage('image', patch)
hg.cvShowImage('context', context)
hg.cvWaitKey()
def display(vec, name):
patch, context = reconstruct_input(vec)
patch = scale_image(patch, 5)
context = scale_image(context, 5)
hg.cvSaveImage(name + '_patch.png', patch)
hg.cvSaveImage(name + '_context.png', context)
hg.cvShowImage('image', patch)
hg.cvShowImage('context', context)
hg.cvWaitKey()
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 seek_onChange(pos, capture, windowName):
'''Callback for the seek trackbar'''
print 'Seeking to frame: %d' % pos
# Set the pointer to frame pos and grab the frame
highgui.cvSetCaptureProperty(capture, highgui.CV_CAP_PROP_POS_FRAMES,
pos*3600 - 1)
frame = highgui.cvQueryFrame(capture)
# Display the frame on the window
highgui.cvShowImage(windowName, frame)
def seek_onChange(pos, capture, windowName):
'''Callback for the seek trackbar'''
print 'Seeking to frame: %d' % pos
# Set the pointer to frame pos and grab the frame
highgui.cvSetCaptureProperty(capture, highgui.CV_CAP_PROP_POS_FRAMES,
pos * 3600 - 1)
frame = highgui.cvQueryFrame(capture)
# Display the frame on the window
highgui.cvShowImage(windowName, frame)
def run(self):
"""
Consume images from the webcam at 25fps.
If visualize is True, show the result in the screen.
"""
if self.visualize:
highgui.cvNamedWindow('DucksboardFace')
while self.running:
self.image = highgui.cvQueryFrame(self.camera)
if self.visualize:
highgui.cvShowImage('DucksboardFace', self.image)
highgui.cvWaitKey(1000 / 25)
def run(self):
"""
Consume images from the webcam at 25fps.
If visualize is True, show the result in the screen.
"""
if self.visualize:
highgui.cvNamedWindow('DucksboardFace')
while self.running:
self.image = highgui.cvQueryFrame(self.camera)
if self.visualize:
highgui.cvShowImage('DucksboardFace', self.image)
highgui.cvWaitKey(1000 / 25)
def main(): # ctrl+c to end
global h,s,v,h2,v2,s2,d,e
highgui.cvNamedWindow("Camera 1", 1)
highgui.cvNamedWindow("Orig", 1)
highgui.cvCreateTrackbar("H", "Camera 1", h, 256, tb_h)
highgui.cvCreateTrackbar("S", "Camera 1", s, 256, tb_s)
highgui.cvCreateTrackbar("V", "Camera 1", v, 256, tb_v)
highgui.cvCreateTrackbar("H2", "Camera 1", h2, 256, tb_h2)
highgui.cvCreateTrackbar("S2", "Camera 1", s2, 256, tb_s2)
highgui.cvCreateTrackbar("V2", "Camera 1", v2, 256, tb_v2)
highgui.cvCreateTrackbar("Dilate", "Camera 1", d, 30, tb_d)
highgui.cvCreateTrackbar("Erode", "Camera 1", e, 30, tb_e)
cap = highgui.cvCreateCameraCapture(1)
highgui.cvSetCaptureProperty(cap, highgui.CV_CAP_PROP_FRAME_WIDTH, IMGW)
highgui.cvSetCaptureProperty(cap, highgui.CV_CAP_PROP_FRAME_HEIGHT, IMGH)
c = 0
t1 = tdraw = time.clock()
t = 1
font = cv.cvInitFont(cv.CV_FONT_HERSHEY_PLAIN, 1, 1)
while c != 0x27:
image = highgui.cvQueryFrame(cap)
if not image:
print "capture failed"
break
thresh = cv.cvCreateImage(cv.cvSize(IMGW,IMGH),8,1)
cv.cvSetZero(thresh)
cv.cvCvtColor(image,image,cv.CV_RGB2HSV)
cv.cvInRangeS(image, (h,s,v,0), (h2,s2,v2,0), thresh)
result = cv.cvCreateImage(cv.cvSize(IMGW,IMGH),8,3)
cv.cvSetZero(result)
cv.cvOr(image,image,result,thresh)
for i in range(1,e):
cv.cvErode(result,result)
for i in range(1,d):
cv.cvDilate(result,result)
# floodfill objects back in, allowing threshold differences outwards
t2 = time.clock()
if t2 > tdraw+0.3:
t = t2-t1
tdraw=t2
cv.cvPutText(result, "FPS: " + str(1 / (t)), (0,25), font, (255,255,255))
t1 = t2
highgui.cvShowImage("Orig", image)
highgui.cvShowImage("Camera 1", result)
c = highgui.cvWaitKey(10)
def show_processed(image, masks, detection, blobs, detector):
masker = Mask(image)
splitter = SplitColors(image)
r, g, b = splitter.split(image)
thresholded_image = masker.mask(masks[0], r, g, b)
draw_detection(thresholded_image, detection)
hg.cvShowImage('thresholded', thresholded_image)
draw_detection(image, detection)
draw_blobs(image, blobs)
make_visible_binary_image(masks[0])
draw_detection(masks[0], detection)
make_visible_binary_image(masks[1])
make_visible_binary_image(masks[2])
hg.cvShowImage("video", image)
hg.cvShowImage('motion', masks[1])
hg.cvShowImage('intensity', masks[2])
key = hg.cvWaitKey(10)
if detector != None:
if key == 'T': #down
detector.intensity_filter.thres_high = detector.intensity_filter.thres_high - 5
print 'detector.intensity_filter.thres =', detector.intensity_filter.thres_high
if key == 'R':
detector.intensity_filter.thres_high = detector.intensity_filter.thres_high + 5
print 'detector.intensity_filter.thres =', detector.intensity_filter.thres_high
if key == ' ':
hg.cvWaitKey()
def main():
"""
Just the test
This method is a god resource on how to handle the results
"""
filename = sys.argv[1]
image = highgui.cvLoadImage (filename)
print "DO NOT EXPECT THE RUNNING TIME OF THIS TEST TO BE REPRESENTATIVE!"
print ""
print "THRESHOLDS AND EVERYTHING ELSE ARE HARDCODED!"
cutRatios = [0.6667, lib.PHI, 0.6]
settings = Settings(cutRatios)
# Run the analysis with the above settings
comps = naiveMethod.analyzeImage(image, settings)
# This is just for drawing the results
# The below methods can probably be combined but don't bother
# {{{
# Get and draw the cuts
cuts = {}
for ratio in settings.cutRatios:
cuts[str(ratio)] = lib.findMeans(cv.cvGetSize(image), ratio)
for ratio in cuts:
lib.drawLines(image, None, cuts[ratio], lib.getRandomColor())
# Get and draw the components
for ratio in comps:
for cut in comps[ratio]:
lib.drawBoundingBoxes(image, comps[ratio][cut])
# }}}
winname = "Failure"
highgui.cvNamedWindow (winname, highgui.CV_WINDOW_AUTOSIZE)
while True:
highgui.cvShowImage (winname, image)
c = highgui.cvWaitKey(0)
if c == 'q':
print "Exiting ..."
print ""
sys.exit(0)
def showImage(image, name): """Helper method for displaying an image""" winname = name highgui.cvNamedWindow (winname, highgui.CV_WINDOW_AUTOSIZE) while True: highgui.cvShowImage (winname, image) c = highgui.cvWaitKey(0) if c == 'q': print "Exiting ..." print "" sys.exit(0)
def on_trackbar (position):
#下面两句应该是没什么用的
cv.cvSmooth (gray, edge, cv.CV_BLUR, 3, 3, 0) #图像平滑
cv.cvNot (gray, edge) #计算数组元素的按位取反
# run the edge dector on gray scale
cv.cvCanny (gray, edge, position, position * 3, 3) #采用 Canny 算法做边缘检测
# reset
cv.cvSetZero (col_edge) #清空数组
# copy edge points
cv.cvCopy (image, col_edge, edge) #参数edge影响拷贝的结果
# show the image
highgui.cvShowImage (win_name, col_edge)
def on_trackbar (position):
cv.cvSmooth (gray, edge, cv.CV_BLUR, 3, 3, 0)
cv.cvNot (gray, edge)
# run the edge dector on gray scale
cv.cvCanny (gray, edge, position, position * 3, 3)
# reset
cv.cvSetZero (col_edge)
# copy edge points
cv.cvCopy (image, col_edge, edge)
# show the image
highgui.cvShowImage (win_name, col_edge)
def on_trackbar(position):
cv.cvSmooth(gray, edge, cv.CV_BLUR, 3, 3, 0)
cv.cvNot(gray, edge)
# run the edge dector on gray scale
cv.cvCanny(gray, edge, position, position * 3, 3)
# reset
cv.cvSetZero(col_edge)
# copy edge points
cv.cvCopy(image, col_edge, edge)
# show the image
highgui.cvShowImage(win_name, col_edge)
def recognize_face():
try:
argsnum=len(sys.argv)
print "args:",argsnum
#if(argsnum<5):
# print "usage:python pyfaces.py imgname dirname numofeigenfaces threshold "
# sys.exit(2)
#imgname=sys.argv[1]
#dirname=sys.argv[2]
#egfaces=int(sys.argv[3])
#thrshld=float(sys.argv[4])
capture=hg.cvCreateCameraCapture(0)
hg.cvNamedWindow("Snapshot")
i=0
#time.sleep(1)
myframe=0
imgname='sample.png'
dirname='images'
egfaces=5
thrshld=0.3
#frame=0
while 1:
frame=hg.cvQueryFrame(capture)
#print type(frame)
hg.cvShowImage("Snapshot",frame)
key = hg.cvWaitKey(5)
if key=='c' or key=='C':
hg.cvDestroyWindow("Snapshot")
hg.cvSaveImage(imgname,frame)
global_frame=frame
break
#print frame
#sys.exit(0)
pyf=PyFaces(imgname,dirname,egfaces,thrshld,frame)
#if pyfaces returns false then save this image into images folder
hg.cvReleaseCapture(capture)
return pyf.getFileName()
except Exception,detail:
print detail
print "usage:python pyfaces.py imgname dirname numofeigenfaces threshold "
def compareImages(img1, img2, name1, name2): # Do NOT save images to disk in this method winname1 = name1 winname2 = name2 highgui.cvNamedWindow (winname1, highgui.CV_WINDOW_AUTOSIZE) highgui.cvNamedWindow (winname2, highgui.CV_WINDOW_AUTOSIZE) while True: highgui.cvShowImage (winname1, img1) highgui.cvShowImage (winname2, img2) c = highgui.cvWaitKey(0) if c == 'q': print "Exiting ..." print "" sys.exit(0)
def main():
usage = "%s [options] <imgfile> " % (sys.argv[0])
version = "%prog 0.2\n Longbin Chen, [email protected]"
oparser = optparse.OptionParser(usage=usage, version=version)
oparser.add_option('-d', '--display', action="store_true", dest = 'display', default = False, help = 'display the image')
oparser.add_option('-c','--contour', action="store_true", dest = 'contour', default = False, help = 'show object contour')
oparser.add_option('-i','--image', action="store_true", dest = 'image', default = False, help = 'show original images')
oparser.add_option('-n', '--number', dest = 'num', type='int', default = 200 , help = 'the number of feature points')
oparser.add_option('-x','--enlarge', dest = 'enlarge', default = 1.0 , type = float, help = 'resize images, default:1.0')
oparser.add_option('-o', '--output', dest = 'output', default = None, help = 'output file')
oparser.add_option('-p', '--pointfile', dest = 'pointfile', default = None, help = 'use pointfile ')
oparser.add_option('-r', '--harris', dest = 'harris', default = False, action = "store_true", help = 'use harris detector')
oparser.add_option('-s', '--save', dest = 'save', default = None, help = 'save the img file')
(options, args) = oparser.parse_args(sys.argv)
if len(args) != 2:
oparser.parse_args([sys.argv[0], "--help"])
sys.exit(1)
if (options.pointfile == None and options.harris == None):
print >> sys.stderr, "either of pointfile and harris can be valid"
sys.exit(1)
highgui.cvNamedWindow ("Corner1", 1)
ct = Linker(options.contour, options.image, options.enlarge, options.num)
if (options.pointfile):
ct.LoadPoints(options.pointfile)
ct.LinkPoints(args[1])
else:
ct.HarrisPoints(args[1])
ct.LinkPoints(args[1])
highgui.cvShowImage ("Corner1", ct.drawimg)
highgui.cvWaitKey (0)
if (options.save):
highgui.cvSaveImage(options.save, ct.drawimg)
if (options.output):
f = open(options.output, "w")
f.write(OUT.getvalue())
f.close()
OUT.close()
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 run(self, images, display=True, verbose=False, debug=False):
left_detection, left_intensity_motion_activations, left_image, left_combined_masks = self.left_detector.detect(images[0])
self.record(left_detection, left_image, left_intensity_motion_activations)
right_detection, right_intensity_motion_activations, right_image, right_combined_masks = self.right_detector.detect(images[1])
self.record(right_detection, right_image, right_intensity_motion_activations)
if debug:
motion, intensity = self.left_detector.get_motion_intensity_images()
show_processed(left_image, [left_combined_masks, motion, intensity],
left_detection, left_intensity_motion_activations, self.left_detector)
elif display:
draw_detection(left_image, left_detection)
hg.cvShowImage('video', left_image)
if left_detection != None and right_detection != None:
if (self.expecting_correct_labels and self.expected_class == 0):
print 'EmbodiedLaserDetector: output suppressed, classified positive in both cameras.'
else:
return self.triangulate(left_detection, right_detection)
return None
def opencvSnap(dev,size):
"""
An example use of the "camera" taking a single picture frame using opencv's cvMat as the return method.
"""
# First lets take a picture using opencv, and display it using opencv...
cvWin = hg.cvNamedWindow( "Opencv Rendering and Capture", 0 )
print("Opening device %s, with video size (%s,%s)" % (dev,size[0],size[1]))
# creates the camera of the specified size and in RGB colorspace
cam = Camera(dev, size, "RGB")
a = cam.get_image()
hg.cvShowImage ('Opencv Rendering and Capture', a)
# close the capture stream to avoid problems later, should see the camera turn off
hg.cvReleaseCapture(cam.capture)
del cam
# Wait for any key then clean up
print("Press any key to continue")
k = hg.cvWaitKey()
hg.cvDestroyWindow("Opencv Rendering and Capture")
def display_images(image_list, max_x=1200, max_y=1000, save_images=False):
"""
Display a list of OpenCV images tiled across the screen
with maximum width of max_x and maximum height of max_y
save_images - will save the images(with timestamp)
"""
curtime = time.localtime()
date_name = time.strftime('%Y_%m_%d_%I%M%S', curtime)
loc_x, loc_y = 0, 0
wins = []
for i, im in enumerate(image_list):
if save_images:
if im.nChannels == 1 and im.depth == cv.IPL_DEPTH_32F:
clr = cv.cvCreateImage(cv.cvSize(im.width, im.height),
cv.IPL_DEPTH_8U, 1)
cv.cvConvertScale(im, clr, 255.0)
im = clr
highgui.cvSaveImage('image%d_' % i + date_name + '.png', im)
window_name = 'image %d' % i
wins.append((window_name, im))
highgui.cvNamedWindow(window_name, highgui.CV_WINDOW_AUTOSIZE)
highgui.cvMoveWindow(window_name, loc_x, loc_y)
loc_x = loc_x + im.width
if loc_x > max_x:
loc_x = 0
loc_y = loc_y + im.height
if loc_y > max_y:
loc_y = 0
while True:
for name, im in wins:
highgui.cvShowImage(name, im)
keypress = highgui.cvWaitKey(10)
if keypress == '\x1b':
break
def visualize(eigens):
l1 = eigens[:, :, 0]
l2 = eigens[:, :, 1]
m1 = np.min(l1)
m2 = np.min(l2)
r1 = np.max(l1) - m1
r2 = np.max(l2) - m2
if r1 == 0:
r1 = 1
if r2 == 0:
r2 = 1
l1cv = ut.np2cv(np.array((1 - ((l1 - m1) / r1)) * 255, dtype="uint8"))
l2cv = ut.np2cv(np.array((1 - ((l2 - m2) / r2)) * 255, dtype="uint8"))
hg.cvNamedWindow("eigen value 1", 1)
hg.cvNamedWindow("eigen value 2", 1)
hg.cvShowImage("eigen value 1", l1cv)
hg.cvShowImage("eigen value 2", l2cv)
while True:
k = hg.cvWaitKey(33)
if k == " ":
return
if k == "x":
exit()
def opencvSnap(dev, size):
"""
An example use of the "camera" taking a single picture frame using opencv's cvMat as the return method.
"""
# First lets take a picture using opencv, and display it using opencv...
cvWin = hg.cvNamedWindow("Opencv Rendering and Capture", 0)
print("Opening device %s, with video size (%s,%s)" %
(dev, size[0], size[1]))
# creates the camera of the specified size and in RGB colorspace
cam = Camera(dev, size, "RGB")
a = cam.get_image()
hg.cvShowImage('Opencv Rendering and Capture', a)
# close the capture stream to avoid problems later, should see the camera turn off
hg.cvReleaseCapture(cam.capture)
del cam
# Wait for any key then clean up
print("Press any key to continue")
k = hg.cvWaitKey()
hg.cvDestroyWindow("Opencv Rendering and Capture")
def visualize(eigens):
l1 = eigens[:,:,0]
l2 = eigens[:,:,1]
m1 = np.min(l1)
m2 = np.min(l2)
r1 = np.max(l1) - m1
r2 = np.max(l2) - m2
if r1 == 0:
r1 = 1
if r2 == 0:
r2 = 1
l1cv = ut.np2cv(np.array( (1 - ((l1-m1) / r1)) * 255, dtype='uint8'))
l2cv = ut.np2cv(np.array( (1 - ((l2-m2) / r2)) * 255, dtype='uint8'))
hg.cvNamedWindow('eigen value 1', 1)
hg.cvNamedWindow('eigen value 2', 1)
hg.cvShowImage('eigen value 1', l1cv)
hg.cvShowImage('eigen value 2', l2cv)
while True:
k = hg.cvWaitKey(33)
if k == ' ':
return
if k == 'x':
exit()
def main():
ct = Corner()
usage = "%s [options] <imgfile>" % (sys.argv[0])
version = "%prog 0.2\n Longbin Chen, [email protected]"
oparser = optparse.OptionParser(usage=usage, version=version)
oparser.add_option('-d', '--display', action="store_true", dest = 'display', default = False, help = 'display the image')
oparser.add_option('-n', '--number', dest = 'num', type='int',default = 200 , help = 'the number of feature points')
oparser.add_option('-o', '--output', dest = 'output', default = None, help = 'output file')
oparser.add_option('-s', '--save', dest = 'save', default = None, help = 'save the img file')
(options, args) = oparser.parse_args(sys.argv)
if len(args) != 2:
oparser.parse_args([sys.argv[0], "--help"])
sys.exit(1)
ct.GetCorner(args[1], options.num)
if (options.display):
ct.DrawKeyPoints()
highgui.cvNamedWindow ("Corner1", 1)
highgui.cvShowImage ("Corner1", ct.drawimg)
highgui.cvWaitKey (0)
if (options.save):
highgui.cvSaveImage(options.save, ct.drawimg)
def display_images(image_list, max_x = 1200, max_y = 1000, save_images=False):
"""
Display a list of OpenCV images tiled across the screen
with maximum width of max_x and maximum height of max_y
save_images - will save the images(with timestamp)
"""
curtime=time.localtime()
date_name = time.strftime('%Y_%m_%d_%I%M%S', curtime)
loc_x, loc_y = 0, 0
wins = []
for i, im in enumerate(image_list):
if save_images:
if im.nChannels == 1 and im.depth == cv.IPL_DEPTH_32F:
clr = cv.cvCreateImage(cv.cvSize(im.width, im.height), cv.IPL_DEPTH_8U, 1)
cv.cvConvertScale(im, clr, 255.0)
im = clr
highgui.cvSaveImage('image%d_'%i+date_name+'.png', im)
window_name = 'image %d' % i
wins.append((window_name, im))
highgui.cvNamedWindow(window_name, highgui.CV_WINDOW_AUTOSIZE)
highgui.cvMoveWindow(window_name, loc_x, loc_y)
loc_x = loc_x + im.width
if loc_x > max_x:
loc_x = 0
loc_y = loc_y + im.height
if loc_y > max_y:
loc_y = 0
while True:
for name, im in wins:
highgui.cvShowImage(name, im)
keypress = highgui.cvWaitKey(10)
if keypress == '\x1b':
break
def process(self, take_new_image=True):
"""We will take a snapshot, optionally do some arbitrary process (eg in numpy/scipy)
then display it. If a frame is given use that instead of taking a new image.
"""
try:
if take_new_image:
logging.debug("capturing an image")
self.snapshot = cv.cvCloneMat(hg.cvQueryFrame(self.camera))
if self.processFunction is not None:
logging.debug("Sending image to process function")
res = self.processFunction(self.snapshot)
logging.debug("Received result from processing function")
assert isinstance(res, cv.CvMat), "Not CvMat"
self.snapshot = res
if self.show:
hg.cvShowImage(self.title, self.snapshot)
except Exception, e:
# If something goes wrong make sure we close the window
logging.error("Error in processing image: %s" % e)
hg.cvDestroyWindow(self.title)
raise SystemExit
def process(self, take_new_image=True):
"""We will take a snapshot, optionally do some arbitrary process (eg in numpy/scipy)
then display it. If a frame is given use that instead of taking a new image.
"""
try:
if take_new_image:
logging.debug("capturing an image")
self.snapshot = cv.cvCloneMat( hg.cvQueryFrame( self.camera) )
if self.processFunction is not None:
logging.debug("Sending image to process function")
res = self.processFunction(self.snapshot)
logging.debug("Received result from processing function")
assert isinstance(res,cv.CvMat), "Not CvMat"
self.snapshot = res
if self.show:
hg.cvShowImage( self.title, self.snapshot )
except Exception, e:
# If something goes wrong make sure we close the window
logging.error("Error in processing image: %s" % e)
hg.cvDestroyWindow(self.title)
raise SystemExit
def main(): if len(sys.argv)<2: print "throw a image my way" sys.exit(-1) print "Im testing" class Phony(): pass tmp = Phony() setattr(tmp, 'id', 1) setattr(tmp, 'location', sys.argv[1]) test = Painting(tmp) print test.getWidth() print test.getHeight() winname ="Test" highgui.cvNamedWindow(winname, highgui.CV_WINDOW_AUTOSIZE) while True: highgui.cvShowImage(winname,test.getImage()) c = highgui.cvWaitKey(0) if c == 'q': sys.exit(0)
def show_processed(image, masks, detection, blobs, detector):
masker = Mask(image)
splitter = SplitColors(image)
r, g, b = splitter.split(image)
thresholded_image = masker.mask(masks[0], r, g, b)
draw_detection(thresholded_image, detection)
hg.cvShowImage('thresholded', thresholded_image)
draw_detection(image, detection)
draw_blobs(image, blobs)
make_visible_binary_image(masks[0])
draw_detection(masks[0], detection)
make_visible_binary_image(masks[1])
make_visible_binary_image(masks[2])
hg.cvShowImage("video", image)
hg.cvShowImage('motion', masks[1])
hg.cvShowImage('intensity', masks[2])
#if not writer:
# print "Error opening writer"
# sys.exit (1)
print "starting loop"
while 1:
# do forever
# 1. capture the current image
frame = highgui.cvQueryFrame(capture)
frame = highgui.cvRetrieveFrame(capture)
#frame = highgui.cvGrabFrame (capture)
#img = highgui.cvRetrieveFrame (capture)
#cvGrabFrame(capture); // capture a frame
#img=cvRetrieveFrame(capture); // retrieve the captured frame
#cvWriteFrame(writer,img); // add the frame to the file
highgui.cvShowImage('Camera', frame)
# handle events
#k = highgui.cvWaitKey ()
#print
for event in pygame.event.get():
if event.type == pygame.QUIT:
highgui.cvReleaseVideoWriter(writer)
highgui.cvDestroyAllWindows()
highgui.cvReleaseCapture(capture)
pygame.quit()
#sys.exit()
break
keyinput = pygame.key.get_pressed()
cv.cvFlip(frame, None, 1)
cv.cvCvtColor(frame, my_grayscale, cv.CV_RGB2GRAY)
cv.cvThreshold(my_grayscale, my_grayscale, 128, 255,
cv.CV_THRESH_BINARY)
if not blob_overlay:
# Convert black-and-white version back into three-color representation
cv.cvCvtColor(my_grayscale, frame, cv.CV_GRAY2RGB)
myblobs = CBlobResult(my_grayscale, mask, 100, True)
myblobs.filter_blobs(10, 10000)
blob_count = myblobs.GetNumBlobs()
for i in range(blob_count):
my_enumerated_blob = myblobs.GetBlob(i)
# print "%d: Area = %d" % (i, my_enumerated_blob.Area())
my_enumerated_blob.FillBlob(frame, hsv2rgb(i * 180.0 / blob_count),
0, 0)
# we can now display the images
highgui.cvShowImage('Blob View', frame)
# handle events
k = highgui.cvWaitKey(10)
if k == '\x1b':
# user has press the ESC key, so exit
break
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 run(exposure, video=None, display=False, debug=False):
if display:
hg.cvNamedWindow("video", 1)
hg.cvMoveWindow("video", 0, 0)
if debug:
hg.cvNamedWindow('right', 1)
hg.cvMoveWindow("right", 800, 0)
hg.cvNamedWindow("thresholded", 1)
hg.cvNamedWindow('motion', 1)
hg.cvNamedWindow('intensity', 1)
hg.cvMoveWindow("thresholded", 800, 0)
hg.cvMoveWindow("intensity", 0, 600)
hg.cvMoveWindow("motion", 800, 600)
if video is None:
#video = cam.VidereStereo(0, gain=96, exposure=exposure)
video = cam.StereoFile('measuring_tape_red_left.avi','measuring_tape_red_right.avi')
frames = video.next()
detector = LaserPointerDetector(frames[0], LaserPointerDetector.SUN_EXPOSURE,
use_color=False, use_learning=True)
detector_right = LaserPointerDetector(frames[1], LaserPointerDetector.SUN_EXPOSURE,
use_color=False, use_learning=True, classifier=detector.classifier)
stereo_cam = cam.KNOWN_CAMERAS['videre_stereo2']
for i in xrange(10):
frames = video.next()
detector.detect(frames[0])
detector_right.detect(frames[1])
lt = cv.cvCreateImage(cv.cvSize(640,480), 8, 3)
rt = cv.cvCreateImage(cv.cvSize(640,480), 8, 3)
for l, r in video:
start_time = time.time()
#l = stereo_cam.camera_left.undistort_img(l)
#r = stereo_cam.camera_right.undistort_img(r)
cv.cvCopy(l, lt)
cv.cvCopy(r, rt)
l = lt
r = rt
undistort_time = time.time()
_, _, right_cam_detection, stats = detector_right.detect(r)
if debug:
draw_blobs(r, stats)
draw_detection(r, right_cam_detection)
hg.cvShowImage('right', r)
image, combined, left_cam_detection, stats = detector.detect(l)
detect_time = time.time()
if debug:
motion, intensity = detector.get_motion_intensity_images()
show_processed(l, [combined, motion, intensity], left_cam_detection, stats, detector)
elif display:
#draw_blobs(l, stats)
draw_detection(l, left_cam_detection)
hg.cvShowImage('video', l)
hg.cvWaitKey(10)
if right_cam_detection != None and left_cam_detection != None:
x = np.matrix(left_cam_detection['centroid']).T
xp = np.matrix(right_cam_detection['centroid']).T
result = stereo_cam.triangulate_3d(x, xp)
print '3D point located at', result['point'].T,
print 'distance %.2f error %.3f' % (np.linalg.norm(result['point']), result['error'])
triangulation_time = time.time()
diff = time.time() - start_time
print 'Main: Running at %.2f fps, took %.4f s' % (1.0 / diff, diff)
#! /usr/bin/env python
import opencv
from opencv import highgui
cap = highgui.cvCreateFileCapture("../c/tree.avi")
img = highgui.cvQueryFrame(cap)
print "Got frame of dimensions (", img.width, " x ", img.height, " )"
highgui.cvNamedWindow("win", highgui.CV_WINDOW_AUTOSIZE)
highgui.cvShowImage("win", img)
highgui.cvMoveWindow("win", 200, 200)
highgui.cvWaitKey(0)
cv.cvCalcBackProject(hue, backproject, obj_hist)
cv.cvAnd(backproject, mask, backproject)
#niter, track_comp, track_box =
cv.cvCamShift(
backproject, track_window,
cv.cvTermCriteria(cv.CV_TERMCRIT_EPS | cv.CV_TERMCRIT_ITER, 10,
1), track_comp, track_box)
track_window = track_comp.rect
#if backproject_mode:
# cvCvtColor( backproject, image, CV_GRAY2BGR )
if not frame.origin:
track_box.angle = -track_box.angle
cv.cvEllipseBox(frame, track_box, cv.CV_RGB(255, 0, 0), 3,
cv.CV_AA, 0)
# we can now display the images
highgui.cvShowImage('Camera', frame)
highgui.cvShowImage('Histogram', histimg)
# handle events
k = highgui.cvWaitKey(10)
if k == '\x1b':
# user has press the ESC key, so exit
break
highgui.cvReleaseCapture(capture)
def callback_image(im):
t = time.time()
cvim = pyrob.util.ros2cv(im)
hg.cvShowImage('left', cvim)
hg.cvWaitKey(5)
print 'total', time.time() - t
# -*- coding:utf8 -*-
import opencv
from opencv import highgui as hg
capture = hg.cvCreateCameraCapture(0)
hg.cvNamedWindow("Snapshot")
frames = []
for i in range(10):
frame = hg.cvQueryFrame(capture)
frames.append(opencv.cvClone(frame))
hg.cvShowImage("Snapshot", frame)
hg.cvWaitKey(1000)
hg.cvNamedWindow("hello")
for i in range(10):
hg.cvShowImage("hello", frames[i])
hg.cvWaitKey(1000)
"""
import copy
dst=copy.copy(frames[1])
opencv.cvSub(frames[2], frames[1], dst)
hg.cvShowImage("Snapshot", dst)
from IPython.Shell import IPShellEmbed
IPShellEmbed()()
hg.cvWaitKey(10000)
"""
