class Module(object):
"""
This is the IDM's Main class, called by mousetrap.py in the load process.
"""
def __init__(self, controller, stgs = {}):
"""
IDM's init function.
Arguments:
- self: The main object pointer.
- controller: mousetrap main class pointer. This is passed by MouseTrap's controller (mousetrap.py) when loaded.
- stgs: Possible settings loaded from the user's settings file. If there aren't settings the IDM will use the a_settings dict.
"""
# This will init the Camera class.
# This class is used to handle the camera device.
Camera.init()
# Controller instance
self.ctr = controller
# Config object
self.cfg = self.ctr.cfg
if not self.cfg.has_section("color"):
self.cfg.add_section("color")
# Capture instance
# The capture is the object containing the image
# and all the possible methods to modify it.
self.cap = None
# IDM's Settings dict
self.stgs = stgs
# Prepares the IDM using the settings.
self.prepare_config()
image = None
self.hsv = None
self.hue = None
self.mask = None
self.backproject = None
self.histimg = None
self.hist = None
backproject_mode = 0
select_object = 0
self.track_object = 0
show_hist = 1
origin = None
selection = None
self.track_window = None
self.track_box = None
self.track_comp = None
self.hdims = 16
# initial settings for value, saturation, and hue
self.vmin = c_int(10)
self.vmax = c_int(256)
self.smin = c_int(80)
self.smax = c_int(256)
self.hmin = c_int(25)
self.hmax = c_int(40) #this may have to be 180 and not 256, for whatever reason
self.h2min = c_int(170)
self.h2max = c_int(175)
def prepare_config(self):
"""
Prepares the IDM using the settings
Arguments:
- self: The main object pointer
"""
global a_settings
# If the dict is empty then
# use the default settings defined in a_settings
if not self.stgs:
self.stgs = a_settings
# For each key do something if required by the module
for key in self.stgs:
pass
def on_mouse(event, x, y, flags, param):
print "ADSFSF"
global select_object, image, selection, origin, track_object
if image is None:
return
if image.origin:
y = image.height - y
if select_object:
selection.x = min(x,origin.x)
selection.y = min(y,origin.y)
selection.width = selection.x + abs(x - origin.x)
selection.height = selection.y + abs(y - origin.y)
selection.x = max( selection.x, 0 )
selection.y = max( selection.y, 0 )
selection.width = min( selection.width, image.width )
selection.height = min( selection.height, image.height )
selection.width -= selection.x
selection.height -= selection.y
if event == CV_EVENT_LBUTTONDOWN:
origin = cvPoint(x,y)
selection = cvRect(x,y,0,0)
select_object = 1
elif event == CV_EVENT_LBUTTONUP:
select_object = 0
if selection.width > 0 and selection.height > 0:
track_object = -1
def hsv2rgb(hue):
rgb=[0,0,0]
sector_data= ((0,2,1), (1,2,0), (1,0,2), (2,0,1), (2,1,0), (0,1,2))
hue *= 0.033333333333333333333333333333333
sector = cvFloor(hue)
p = cvRound(255*(hue - sector))
p ^= 255 if bool(sector & 1) else 0
rgb[sector_data[sector][0]] = 255
rgb[sector_data[sector][1]] = 0
rgb[sector_data[sector][2]] = p
return cvScalar(rgb[2], rgb[1], rgb[0], 0)
def set_capture(self, cam):
"""
Initialize the capture and sets the main settings.
Arguments:
- self: The main object pointer
- cam: The camera device index. For Example: 0 = /dev/video0, 1 = /dev/video1
"""
# Starts the Capture using the async method.
# This means that self.cap.sync() wont be called periodically
# by the idm because the Capture syncs the image asynchronously (See dev/camera.py)
self.cap = Capture(async=True, idx=cam)
# This sets the final image default color to rgb. The default color is bgr.
self.cap.change(color="rgb")
def _convertColorDepth(self, color):
"""
Converts from 16 to 8 bit color depth. Necessary
for OpenCV functions and GDK colors to interact as the
former expects colors from 0-255 and the latter expects
0-65535.
Arguments:
- self: The main object pointer
- color: The integer color value to convert to 0-255
"""
return (int)(color / 65535.0) * 255
def get_image(self):
"""
Gets the last queried and formated image.
Function used by the mousetrap/ui/main.py
to get the output image
Arguments:
- self: The main object pointer
returns self.cap.resize(200, 160, True)
"""
"""argc = len(argv)
if argc == 1 or (argc == 2 and argv[1].isdigit()):
capture = cvCaptureFromCAM( int(argv[1]) if argc == 2 else 0 )
elif argc == 2:
capture = cvCaptureFromAVI( argv[1] )
else:
capture = None
if not capture:
print "Could not initialize capturing..."
exit(-1)
#HOTT KEYS!!!!1
print "Hot keys: \n" \
"\tESC - quit the program\n" \
"\tc - stop the tracking\n" \
"\tb - switch to/from backprojection view\n" \
"\th - show/hide object histogram\n" \
"To initialize tracking, select the object with mouse\n"
#what windows do we want?"""
cvNamedWindow( "Histogram", 1 )
cvNamedWindow( "CamShiftDemo", 1 ) #main image
cvNamedWindow( "Mask", 1 )
#cvNamedWindow( "Backproject", 1)
#cvNamedWindow( "Hue", 1)
#enables mouse event monitoring in the main image window
cvSetMouseCallback( "CamShiftDemo", self.on_mouse )
cvCreateTrackbar( "Vmin", "CamShiftDemo", self.vmin, 256 )
cvCreateTrackbar( "Vmax", "CamShiftDemo", self.vmax, 256 )
cvCreateTrackbar( "Smin", "CamShiftDemo", self.smin, 256 )
cvCreateTrackbar( "Smax", "CamShiftDemo", self.smax, 256 )
#select the ranges of hues you want to track
cvCreateTrackbar( "Hmin", "CamShiftDemo", self.hmin, 180 )
cvCreateTrackbar( "Hmax", "CamShiftDemo", self.hmax, 180 )
#cvCreateTrackbar( "H2min", "CamShiftDemo", h2min, 180 )
#cvCreateTrackbar( "H2max", "CamShiftDemo", h2max, 180 )
#loop
"""while True:
#get next frame
frame = cvQueryFrame( self.cap.image )
if not frame:
break
if not image:
# allocate all the buffers
image = cvCreateImage( cvGetSize(frame), 8, 3 )
image.origin = frame.origin
hsv = cvCreateImage( cvGetSize(frame), 8, 3 )"""
self.hue = cvCreateImage( cvSize(640,480), 8, 1 )
self.mask = cvCreateImage( cvSize(640,480), 8, 1 )
"""mask2 = cvCreateImage( cvGetSize(frame), 8, 1 )
maskcombo = cvCreateImage( cvGetSize(frame), 8, 1 )"""
self.backproject = cvCreateImage( cvSize(640,480), 8, 1 )
self.hist = cvCreateHist( [self.hdims], CV_HIST_ARRAY, [[0, 180]] )
self.histimg = cvCreateImage( cvSize(320,200), 8, 3 )
cvZero( self.histimg )
self.cap.sync()
print(type(self.cap.image()))
#cvCopy(frame, image)
self.hsv = self.cap.color("hsv", channel=3, copy=True) #make the image hsv
#cvCvtColor( self.cap.image, self.hsv, CV_BGR2HSV )
self.track_object=-1
print "ABOUT TO GOT IN"
if self.track_object != 0:
print "GOT IN"
#updates the hsv values to be masked
print type(self.hsv)
scalar1=cvScalar(self.hmin.value,self.smin.value,min(self.vmin.value,self.vmax.value),0)
scalar2=cvScalar(self.hmax.value,self.smax.value,max(self.vmin.value,self.vmax.value),0)
cvInRangeS( self.hsv, scalar1, scalar2, self.mask )
#cvInRangeS( self.hsv, cvScalar(h2min.value,smin.value,min(vmin.value,vmax.value),0),
# cvScalar(h2max.value,smax.value,max(vmin.value,vmax.value),0), mask2 )
cvSplit(self.hsv, self.hue) #extract hue information?
#cvOr(mask, mask2, maskcombo) #combine the masks so that EITHER color is accepted
selection=cvRect(10,10,20,20)
if track_object < 0: #OH OKAY negative means it's tracking so... make a histogram
cvSetImageROI( self.hue, selection )
cvSetImageROI( self.mask, selection )
cvCalcHist( [self.hue], self.hist, 0, self.mask );
min_val, max_val = cvGetMinMaxHistValue(hist)
hbins = self.hist.bins[0]
cvConvertScale( hbins, hbins, 255. / max_val if max_val else 0., 0 )
cvResetImageROI( self.hue ) # ^ hisogram stuff, v tracking stuff
cvResetImageROI( self.mask )
track_window = selection #the original window to track is your mouse selection
track_object = 1 #now objects are being tracked
#more histogram stuff -- now we're displaying it
cvZero( self.histimg )
bin_w = self.histimg.width / self.hdims
for i in xrange(self.hdims):
val = cvRound( cvGetReal1D(hbins,i)*self.histimg.height/255 )
color = self.hsv2rgb(i*180./self.hdims)
cvRectangle( self.histimg, cvPoint(i*bin_w,self.histimg.height),
cvPoint((i+1)*bin_w,self.histimg.height - val),
color, -1, 8, 0 )
#calculate the back projection (dunno what this is)
cvCalcBackProject( [self.hue], self.backproject, self.hist )
#mask the backprojection (why? who knows)
cvAnd(self.backproject, self.mask, self.backproject)
#CAMSHIFT HAPPENS
niter, self.track_comp, self.track_box = cvCamShift( self.backproject, self.track_window,
cvTermCriteria( CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 10, 1 ))
track_window = track_comp.rect #no idea
if self.backproject_mode:
cvCvtColor( self.backproject, self.cap.image, CV_GRAY2BGR ) #why??
if not self.cap.image.origin:
track_box.angle = -track_box.angle #why??
# Make sure its a number.
if math.isnan(self.track_box.size.height):
self.track_box.size.height = 0
if math.isnan(track_box.size.width):
self.track_box.size.width = 0
#draws an ellipse around it. the ellipse is GREEN!!!!
cvEllipseBox( self.cap.image, self.track_box, CV_RGB(0,255,0), 3, CV_AA, 0 )
#still lost
if bool(select_object) and selection.width > 0 and selection.height > 0:
cvSetImageROI( self.cap.image, selection )
cvXorS( self.cap.image, cvScalarAll(255), self.cap.image )
cvResetImageROI( self.cap.image )
#hey let's show some stuff in those empty windows!!"""
print "Showing the windows"
print type(self.hsv)
print type(self.histimg)
print type(self.mask)
cvShowImage( "CamShiftDemo", self.hsv )
cvShowImage( "Histogram", self.histimg )
cvShowImage( "Mask", self.mask )
#cvShowImage( "Backproject", backproject)
#cvShowImage( "Hue", hue)
#HOTT KEYS!!!!1
"""c = '%c' % (cvWaitKey(10) & 255)
if c == '\x1b':
break
elif c == 'b':
backproject_mode ^= 1
elif c =='c':
track_object = 0
cvZero( histimg )
elif c =='h':
show_hist ^= 1
if not show_hist:
cvDestroyWindow( "Histogram" )
else:
cvNamedWindow( "Histogram", 1 )
print "Hoiahdfoiahs"
return image
# Calls the resize method passing the new with, height
# specifying that the new image has to be a copy of the original
# so, self.cap.resize will copy the original instead of modifying it."""
return self.cap.resize(200, 160, True)
def get_pointer(self):
"""
Returns the new MousePosition.
Function used to pass the Mouse Pointer position
to the Scripts.
Arguments:
- self: The main object pointer
"""
# The return value has to be a Point() type object
# Following the forehad IDM, The return is self.cap.forehead
# which is created in the get_forehead function as an attribute
# of self.cap
self.cap.pointer=Point("point", "color", ( 1, 2 ), parent=self.cap, follow=True)
class Module(object):
"""
This is the IDM's Main class, called by mousetrap.py in the load process.
"""
def __init__(self, controller, stgs = {}):
"""
IDM's init function.
Arguments:
- self: The main object pointer.
- controller: mousetrap main class pointer. This is passed by MouseTrap's controller (mousetrap.py) when loaded.
- stgs: Possible settings loaded from the user's settings file. If there aren't settings the IDM will use the a_settings dict.
"""
# Controller instance
self.ctr = controller
self.cfg = self.ctr.cfg
if not self.cfg.has_section("color"):
self.cfg.add_section("color")
# Capture instance
# The capture is the object containing the image
# and all the possible methods to modify it.
self.cap = None
# IDM's Settings dict
self.stgs = stgs
# Prepares the IDM using the settings.
self.prepare_config()
#TODO: ADD CONDITIONAL TO ENSURE SETTINGS ARE SET EVEN IF YOU HAVE AN OLD CONFIG FILE
# Initialization of variables needed for color tracking CAMshift algorithm.
self.image = None
self.hsv = None
self.first_time=True # To keep track of whether or not we have initalized image objects
self.select_object = 0
self.track_object = 0
self.origin = None #needed?
self.selection = None
self.track_window = None
self.track_box = None
self.track_comp = None
self.hdims = 16 #Number of columns in the histogram
# Variables to control the ranges for the color mask.
self.vmin = c_int(10) # Value
self.vmax = c_int(256)
self.smin = c_int(80) # Saturation
self.smax = c_int(256)
self.hmin = c_int(0) # Hue
self.hmax = c_int(180) # out of 180, not 256
def prepare_config(self):
"""
Prepares the IDM using the settings
Arguments:
- self: The main object pointer
"""
global a_settings
self.debugLevel = self.ctr.cfg.getint("main", "debugLevel")
print self.debugLevel
# If the dict is empty then
# use the default settings defined in a_settings
if not self.stgs:
self.stgs = a_settings
# For each key do something if required by the module
for key in self.stgs:
pass
def hsv2rgb(self, hue):
"""
Converts an HSV hue to RGB.
Arguments:
- self: The main object pointer
- hue: the hue to convert to RGB.
"""
rgb=[0,0,0]
sector_data= ((0,2,1), (1,2,0), (1,0,2), (2,0,1), (2,1,0), (0,1,2))
hue *= 0.033333333333333333333333333333333
sector = co.cv.cvFloor(hue)
p = co.cv.cvRound(255*(hue - sector))
p ^= 255 if bool(sector & 1) else 0
rgb[sector_data[sector][0]] = 255
rgb[sector_data[sector][1]] = 0
rgb[sector_data[sector][2]] = p
return co.cv.cvScalar(rgb[2], rgb[1], rgb[0], 0)
def set_capture(self, cam):
"""
Initialize the capture and sets the main settings.
Arguments:
- self: The main object pointer
- cam: The camera device index. For Example: 0 = /dev/video0, 1 = /dev/video1
"""
# Starts the Capture using the async method.
# This means that self.cap.sync() wont be called periodically
# by the idm because the Capture syncs the image asynchronously (See dev/camera.py)
self.cap = Capture(async=False, idx=cam, backend="OcvfwCtypes")
#for some reason this is necessary! why?!?
co.hg.cvNamedWindow( "Histogram", 1 )
if(self.debugLevel >= 30):
co.hg.cvNamedWindow( "Mask", 1 )
co.hg.cvCreateTrackbar( "Vmin", "Mask", self.vmin, 256 )
co.hg.cvCreateTrackbar( "Vmax", "Mask", self.vmax, 256 )
co.hg.cvCreateTrackbar( "Smin", "Mask", self.smin, 256 )
co.hg.cvCreateTrackbar( "Smax", "Mask", self.smax, 256 )
co.hg.cvCreateTrackbar( "Hmin", "Mask", self.hmin, 180 )
co.hg.cvCreateTrackbar( "Hmax", "Mask", self.hmax, 180 )
# This sets the final image default color to rgb. The default color is bgr.
self.cap.change(color="rgb")
self.cap.set_camera("lk_swap", True)
def _convertColorDepth(self, color):
"""
Converts from 16 to 8 bit color depth. Necessary
for OpenCV functions and GDK colors to interact as the
former expects colors from 0-255 and the latter expects
0-65535.
Arguments:
- self: The main object pointer
- color: The integer color value to convert to 0-255
"""
return int((color / 65535.0) * 255)
def rgb2hue(self, red, green, blue):
"""
Converts the rgb values from the config file into the corresponding hue value.
This method was stolen from the gtk source!
"""
hue = 0.0
if (red > green):
if (red > blue):
cmax = red
else:
cmax = blue
if (green < blue):
cmin = green
else:
cmin = blue;
else:
if (green > blue):
cmax = green
else:
cmax = blue
if (red < blue):
cmin = red
else:
cmin = blue
val = cmax
if (cmax != 0.0):
sat = (cmax - cmin) / cmax
else:
sat = 0.0
if (sat == 0.0):
hue = 0.0
else:
delta = cmax - cmin
if (red == cmax):
hue = (green - blue) / delta
elif (green == cmax):
hue = 2 + (blue - red) / delta
elif (blue == cmax):
hue = 4 + (red - green) / delta
hue /= 6.0;
if (hue < 0.0):
hue += 1.0
elif (hue > 1.0):
hue -= 1.0
return (hue * 360) / 2
def update_hue_range(self, *args):
"""
WARNING: HACK by Ryan
This method is used as a callback connected to the color picker
save button's click event. I had to do this because we need to update
the hue min/max in this idm whenever the user saves a new color.
However, we can't poll a file's status to see if it's changed, so
we routed the event to two callbacks.
Suggestion: Maybe use a dictionary for configure settings and
serialize it on quit. This would trivialize querying a settings
structure and allow us comparatively free use of the data. Right now
we're forced to keep in mind how often we query settings because
hard drives are SLOW.
"""
temphue = self.rgb2hue(float(self.cfg.get("color", "red")), float(self.cfg.get("color", "green")), float(self.cfg.get("color", "blue")))
hrange = int(self.cfg.get("color","hrange")) / 2
self.hmin.value = int(max(temphue - hrange, 0))
self.hmax.value = int(min(temphue + hrange, 180))
def histogram_init(self):
"""
Initializes and displays a color histogram of the selected area
Arguments:
- self: The main object pointer
"""
co.cv.cvCalcHist( [self.hue], self.hist, 0, self.mask )
min_val, max_val = co.cv.cvGetMinMaxHistValue(self.hist)
hbins = self.hist.bins[0]
co.cv.cvConvertScale( hbins, hbins, 255. / max_val if max_val else 0., 0 )
co.cv.cvZero( self.histimg )
bin_w = self.histimg.width / self.hdims
for i in xrange(self.hdims):
val = co.cv.cvRound( co.cv.cvGetReal1D(hbins,i)*self.histimg.height/255 )
color = self.hsv2rgb(i*180./self.hdims)
co.cv.cvRectangle( self.histimg, co.cv.cvPoint(i*bin_w,self.histimg.height),
co.cv.cvPoint((i+1)*bin_w,self.histimg.height - val),
color, -1, 8, 0 )
if(self.debugLevel >= 30):
co.hg.cvShowImage( "Histogram", self.histimg )
def get_capture(self):
"""
Gets the last queried and formated image.
Function used by the mousetrap/ui/main.py
to get the output image
Arguments:
- self: The main object pointer
returns self.cap.resize(200, 160, True)
"""
# Called to update image with latest frame from webcam
self.cap.sync()
#self.image = self.cap.image().origin needed??
self.image = self.cap.image()
if self.first_time:
# Initialization of images. Only needs to happen once.
# TODO: What is a better way to get the image size?
self.hue = co.cv.cvCreateImage( co.cv.cvGetSize(self.image), 8, 1 )
self.mask = co.cv.cvCreateImage( co.cv.cvGetSize(self.image), 8, 1 )
self.backproject = co.cv.cvCreateImage( co.cv.cvGetSize(self.image), 8, 1 )
self.hist = co.cv.cvCreateHist( [self.hdims], co.cv.CV_HIST_ARRAY, [[0, 180]] )
self.histimg = co.cv.cvCreateImage( co.cv.cvSize(320,200), 8, 3 )
self.temp = co.cv.cvCreateImage( co.cv.cvGetSize(self.image), 8, 3) #needed?
co.cv.cvZero( self.histimg )
#Initialization of hue range from config file.
temphue = self.rgb2hue(float(self.cfg.get("color", "red")), float(self.cfg.get("color", "green")), float(self.cfg.get("color", "blue")))
hrange = int(self.cfg.get("color","hrange")) / 2
self.hmin.value = int(max(temphue - hrange, 0))
self.hmax.value = int(min(temphue + hrange, 180))
#Creates object selection box
self.origin = co.cv.cvPoint(self.image.width / 2, self.image.height / 2)
self.selection = co.cv.cvRect(self.origin.x-50,self.origin.y-50,100,100)
self.first_time=False
self.hsv = self.cap.color("hsv", channel=3, copy=True) # Convert to HSV
# If tracking
if self.track_object != 0:
#Masks pixels that fall outside desired range
scalar1=co.cv.cvScalar(self.hmin.value,self.smin.value,min(self.vmin.value,self.vmax.value),0)
scalar2=co.cv.cvScalar(self.hmax.value,self.smax.value,max(self.vmin.value,self.vmax.value),0)
co.cv.cvInRangeS( self.hsv, scalar1, scalar2, self.mask )
co.cv.cvSplit(self.hsv, self.hue)
# If tracking, first time
if self.track_object < 0:
co.cv.cvSetImageROI( self.hue, self.selection)
co.cv.cvSetImageROI( self.mask, self.selection)
self.histogram_init()
co.cv.cvResetImageROI( self.hue )
co.cv.cvResetImageROI( self.mask )
self.track_window = self.selection
self.track_object = 1
co.cv.cvCalcBackProject( [self.hue], self.backproject, self.hist )
co.cv.cvAnd(self.backproject, self.mask, self.backproject)
#CamShift algorithm is called
niter, self.track_comp, self.track_box = co.cv.cvCamShift( self.backproject, self.track_window,
co.cv.cvTermCriteria( co.cv.CV_TERMCRIT_EPS | co.cv.CV_TERMCRIT_ITER, 10, 1 ))
self.track_window = self.track_comp.rect
if not self.origin:
self.track_box.angle = -self.track_box.angle
# Ensures that track_box size is always at least 0x0
if math.isnan(self.track_box.size.height):
self.track_box.size.height = 0
if math.isnan(self.track_box.size.width):
self.track_box.size.width = 0
#Creates the ellipse around the tracked object
co.cv.cvEllipseBox( self.image, self.track_box, co.cv.CV_RGB(0,255,0), 3, co.cv.CV_AA, 0 )
#Updates cursor location information
if (not hasattr(self.cap, "obj_center")):
self.cap.add(Point("point", "obj_center", ( int(self.track_box.center.x), int(self.track_box.center.y )), parent=self.cap, follow=False))
else:
self.cap.obj_center.set_opencv(co.cv.cvPoint(int(self.track_box.center.x), int(self.track_box.center.y)))
#Displays selection box before tracking starts
if not self.track_object:
co.cv.cvSetImageROI( self.image, self.selection )
co.cv.cvXorS( self.image, co.cv.cvScalarAll(255), self.image )
co.cv.cvResetImageROI( self.image )
if(self.debugLevel >= 30):
co.hg.cvShowImage( "Mask", self.mask)
self.cap.color("rgb", channel=3, copy=True)
# Calls the resize method passing the new with, height
# specifying that the new image has to be a copy of the original
# so, self.cap.resize will copy the original instead of modifying it.
return self.cap
def startTracking(self):
"""
Starts the tracking algorithm. This exists because
we set up keyboard input in the main view to start
and stop tracking. Maybe generalize this functionality
to all idms?
Arguments:
- self: The main object pointer
Raises:
- ValueError: If either the selection height or width are less
than or equal to zero.
"""
if (self.selection.width and self.selection.height <= 0):
raise ValueError()
self.track_object = -1
def stopTracking(self):
"""
Stops the tracking algorithm. This exists because
we set up keyboard input in the main view to start
and stop tracking. Maybe generalize this functionality
to all idms?
Arguments:
- self: The main object pointer
"""
self.track_object = 0
def selSizeUp(self):
"""
Increases the size of the selection window.
Arguments:
- self: The main object pointer
"""
if 6 <= self.selection.x <=self.image.width-self.selection.width-6 and 6 <= self.selection.y <= self.image.height-self.selection.height-6:
self.selection = co.cv.cvRect(self.selection.x-5,self.selection.y-5,self.selection.width+10,self.selection.height+10)
def selSizeDown(self):
"""
Decreases the size of the selection window.
Arguments:
- self: The main object pointer
"""
if self.selection.width > 10 and self.selection.height > 10:
self.selection = co.cv.cvRect(self.selection.x+5,self.selection.y+5,self.selection.width-10,self.selection.height-10)
def selPositionLeft(self):
"""
Changes the location of the selection window.
Arguments:
- self: The main object pointer
"""
if 6 <= self.selection.x <= self.image.width:
self.selection=co.cv.cvRect(self.selection.x-5,self.selection.y,self.selection.width,self.selection.height)
def selPositionRight(self):
"""
Changes the location of the selection window.
Arguments:
- self: The main object pointer
"""
if 0 <= self.selection.x <= self.image.width-self.selection.width-6:
self.selection=co.cv.cvRect(self.selection.x+5,self.selection.y,self.selection.width,self.selection.height)
def selPositionUp(self):
"""
Changes the location of the selection window.
Arguments:
- self: The main object pointer
"""
if 6 <= self.selection.y <= self.image.height:
self.selection=co.cv.cvRect(self.selection.x,self.selection.y-5,self.selection.width,self.selection.height)
def selPositionDown(self):
"""
Changes the location of the selection window.
Arguments:
- self: The main object pointer
"""
if 0 <= self.selection.y <= self.image.height-self.selection.height-6:
self.selection=co.cv.cvRect(self.selection.x,self.selection.y+5,self.selection.width,self.selection.height)
def get_pointer(self):
"""
Returns the new MousePosition.
Function used to pass the Mouse Pointer position
to the Scripts.
Arguments:
- self: The main object pointer
"""
# The return value has to be a Point() type object
# Following the forehad IDM, The return is self.cap.obj_center
# which is created in the get_image function as an attribute
# of self.cap
if hasattr(self.cap, "obj_center"):
return self.cap.obj_center
else:
class Module(object):
"""
This is the IDM's Main class, called by mousetrap.py in the load process.
"""
def __init__(self, controller, stgs = {}):
"""
IDM's init function.
Arguments:
- self: The main object pointer.
- controller: mousetrap main class pointer. This is passed by MouseTrap's controller (mousetrap.py) when loaded.
- stgs: Possible settings loaded from the user's settings file. If there aren't settings the IDM will use the a_settings dict.
"""
debug.debug("ocvfw.idm", "Starting %s idm" % a_name)
self.img = None
self.ctr = controller
self.cap = None
self.stgs = stgs
##############################
# MOTION RELATED VARIABLES #
##############################
self.fel = eye_locator(FEL_NAME)
##############################
# ACTION POINTS #
##############################
self.mpPointer = None
##############################
# CLICK RELATED VARIABLES #
##############################
self.isMoving = False
self.prepare_config()
debug.info("ocvfw.idm", "Forhead Algorithm loaded")
def prepare_config(self):
"""
Prepares the IDM using the settings
Arguments:
- self: The main object pointer
"""
global a_settings
for key in self.stgs:
pass
def set_capture(self, cam):
"""
Initialize the capture and sets the main settings.
Arguments:
- self: The main object pointer
- cam: The camera device index. For Example: 0 = /dev/video0, 1 = /dev/video1
"""
debug.debug("ocvfw.idm", "Setting Capture")
self.cap = Capture(async=False, idx=cam, backend="OcvfwPython")
self.cap.change(color="rgb")
self.cap.set_camera("lk_swap", True)
def calc_motion(self):
if not hasattr(self.cap, "forehead"):
self.get_forehead()
def get_capture(self):
"""
Sets the forehead point if needed and returns the formated image.
Arguments:
- self: The main object pointer
returns self.cap.image()
"""
self.cap.sync()
if not hasattr(self.cap, "leye") or not hasattr(self.cap, "reye"):
self.get_eye()
return self.cap
def get_pointer(self):
"""
Returns the new MousePosition
Arguments:
- self: The main object pointer
"""
return True
def get_eye(self):
eyes = False
face = self.cap.get_area(commons.haar_cds['Face'])
if face:
cvtile = cv.cvCreateMat(128,128,cv.CV_8UC3)
bwtile = cv.cvCreateMat(128,128,cv.CV_8U)
areas = [ (pt[1].x - pt[0].x)*(pt[1].y - pt[0].y) for pt in face ]
startF = face[areas.index(max(areas))][0]
endF = face[areas.index(max(areas))][1]
facerect = self.cap.rect(startF.x, startF.y, endF.x - startF.x, endF.y - startF.y)
if not facerect:
return
cv.cvResize(facerect, cvtile)
cv.cvCvtColor( cvtile, bwtile, cv.CV_BGR2GRAY )
leye,reye,lcp,rcp = self.fel.locateEyes(bwtile)
leye = pv.Point(leye)
reye = pv.Point(reye)
leye_x = int((float(leye.X())*facerect.width/cvtile.width) + startF.x)
leye_y = int((float(leye.Y())*facerect.height/cvtile.height) + startF.y)
reye_x = int((float(reye.X())*facerect.width/cvtile.width) + startF.x)
reye_y = int((float(reye.Y())*facerect.height/cvtile.height) + startF.y)
eye_rect = { "startX" : leye_x - 5,
"startY" : leye_y - 5,
"endX" : leye_x + 5,
"endY" : leye_y + 5}
#self.cap.image(self.cap.rect(leye_x - 5, leye_y - 5, 20, 20))
if not hasattr(self.cap, "leye"):
self.cap.add( Point("point", "leye", [int(leye_x), int(leye_y)], parent=self.cap, follow=True) )
else:
self.cap.add( Point("point", "reye", [int(reye_x), int(reye_y)], parent=self.cap, follow=True) )
# Shows the face rectangle
#self.cap.add( Graphic("rect", "Face", ( startF.x, startF.y ), (endF.x, endF.y), parent=self.cap) )
self.foreheadOrig = None
return False