def set_frame(self,frame):
#This function sets the picture to a desired frame size
#self - object of this class
#frame - captured frame
jpegPIL = Image.fromstring("RGB",(640,480),frame,"jpeg","RGB","raw")
cv_im = cv2.createImage((640,480),cv.IPL_DEPTH_8U,3)
cv2.setData(cv_im,jpegPIL.tostring())
cv2.showImage(self.name,cv_im)
def run(self):
hist = cv2.createHist([180], cv2.CV_HIST_ARRAY, [(0,180)], 1 )
backproject_mode = True
while True:
frame = cv2.QueryFrame( self.capture )
# Convert to HSV and keep the hue
hsv = cv2.createImage(cv2.GetSize(frame), 8, 3)
cv2.cvtColor(frame, hsv, cv2.CV_BGR2HSV)
self.hue = cv2.createImage(cv2.GetSize(frame), 8, 1)
cv2.split(hsv, self.hue, None, None, None)
# Compute back projection
backproject = cv2.createImage(cv2.GetSize(frame), 8, 1)
cv2.calcArrBackProject( [self.hue], backproject, hist )
# Run the cam-shift (if the a window is set and != 0)
if self.track_window and is_rect_nonzero(self.track_window):
crit = ( cv2.CV_TERMCRIT_EPS | cv2.CV_TERMCRIT_ITER, 10, 1)
(iters, (area, value, rect), track_box) = cv2.camShift(backproject, self.track_window, crit) #Call the camshift !!
self.track_window = rect #Put the current rectangle as the tracked area
# If mouse is pressed, highlight the current selected rectangle and recompute histogram
if self.drag_start and is_rect_nonzero(self.selection):
sub = cv2.getSubRect(frame, self.selection) #Get specified area
#Make the effect of background shadow when selecting a window
save = cv2.cloneMat(sub)
cv2.convertScale(frame, frame, 0.5)
cv2.copy(save, sub)
#Draw temporary rectangle
x,y,w,h = self.selection
cv2.rectangle(frame, (x,y), (x+w,y+h), (255,255,255))
#Take the same area but in hue image to calculate histogram
sel = cv2.getSubRect(self.hue, self.selection )
cv2.calcArrHist( [sel], hist, 0)
#Used to rescale the histogram with the max value (to draw it later on)
(_, max_val, _, _) = cv2.getMinMaxHistValue( hist)
if max_val != 0:
cv2.convertScale(hist.bins, hist.bins, 255. / max_val)
elif self.track_window and is_rect_nonzero(self.track_window): #If window set draw an elipseBox
cv2.ellipseBox( frame, track_box, cv2.CV_RGB(255,0,0), 3, cv2.CV_AA, 0 )
cv2.showImage( "CamShiftDemo", frame )
cv2.showImage( "Backprojection", backproject)
cv2.showImage( "Histogram", self.hue_histogram_as_image(hist))
c = cv2.waitKey(7) % 0x100
if c == 27:
break
def invoke(self, arg, from_tty):
args = gdb.string_to_argv(arg)
# generally, we type "plot someimage" in the GDB commandline
# where "someimage" is an instance of cv::Mat
v = gdb.parse_and_eval(args[0])
# the value v is a gdb.Value object of C++
# code's cv::Mat, we need to translate to
# a python object under cv2.cv
image_size = (v['cols'], v['rows'])
# print v
# these two below lines do not work. I don't know why
# channel = gdb.execute("call "+ args[0] + ".channels()", False, True)
# channel = v.channels();
CV_8U = 0
CV_8S = 1
CV_16U = 2
CV_16S = 3
CV_32S = 4
CV_32F = 5
CV_64F = 6
CV_USRTYPE1 = 7
CV_CN_MAX = 512
CV_CN_SHIFT = 3
CV_MAT_CN_MASK = (CV_CN_MAX - 1) << CV_CN_SHIFT
flags = v['flags']
channel = (((flags) & CV_MAT_CN_MASK) >> CV_CN_SHIFT) + 1
CV_DEPTH_MAX = (1 << CV_CN_SHIFT)
CV_MAT_DEPTH_MASK = CV_DEPTH_MAX - 1
depth = (flags) & CV_MAT_DEPTH_MASK
IPL_DEPTH_SIGN = 0x80000000
cv_elem_size = (((4 << 28) | 0x8442211) >> depth * 4) & 15
if (depth == CV_8S or depth == CV_16S or depth == CV_32S):
mask = IPL_DEPTH_SIGN
else:
mask = 0
ipl_depth = cv_elem_size * 8 | mask
img = cv2.createImageHeader(image_size, ipl_depth, channel)
# conver the v['data'] type to "char*" type
char_type = gdb.lookup_type("char")
char_pointer_type = char_type.pointer()
buffer = v['data'].cast(char_pointer_type)
# read bytes from inferior's memory, because
# we run the opencv-python module in GDB's own process
# otherwise, we use memory corss processes
buf = v['step']['buf']
bytes = buf[0] * v['rows'] # buf[0] is the step? Not quite sure.
inferior = gdb.selected_inferior()
mem = inferior.read_memory(buffer, bytes)
# set the img's raw data
cv2.setData(img, mem)
# create a window, and show the image
cv2.startWindowThread()
cv2.namedWindow('viewer')
cv2.showImage('viewer', img)
# the below statement is necessory, otherwise, the Window
# will hang
cv2.waitKey(0)
cv2.destroyWindow('viewer')