def detectObject(image):
grayscale = cv.cvCreateImage(size, 8, 1)
cv.cvFlip(image, None, 1)
cv.cvCvtColor(image, grayscale, cv.CV_BGR2GRAY)
storage = cv.cvCreateMemStorage(0)
cv.cvClearMemStorage(storage)
cv.cvEqualizeHist(grayscale, grayscale)
cascade = cv.cvLoadHaarClassifierCascade(haar_file, cv.cvSize(1,1))
objects = cv.cvHaarDetectObjects(grayscale, cascade, storage, 1.2, 2,
cv.CV_HAAR_DO_CANNY_PRUNING,
cv.cvSize(100,100))
# Draw dots where hands are
if objects:
for i in objects:
#cv.cvRectangle(image, cv.cvPoint( int(i.x), int(i.y)),
# cv.cvPoint(int(i.x+i.width), int(i.y+i.height)),
# cv.CV_RGB(0,255,0), 3, 8, 0)
center = cv.cvPoint(int(i.x+i.width/2), int(i.y+i.height/2))
cv.cvCircle(image, center, 10, cv.CV_RGB(0,0,0), 5,8, 0)
# Left side check
if center.x > box_forward_left[0].x and center.x < box_backwards_left[1].x and center.y > box_forward_left[0].y and center.y < box_backwards_left[1].y:
set_speed('left', center)
# Right side check
if center.x > box_forward_right[0].x and center.x < box_backwards_right[1].x and center.y > box_forward_right[0].y and center.y < box_backwards_right[1].y:
set_speed('right', center)
def detectObject(image):
grayscale = cv.cvCreateImage(size, 8, 1)
cv.cvFlip(image, None, 1)
cv.cvCvtColor(image, grayscale, cv.CV_BGR2GRAY)
storage = cv.cvCreateMemStorage(0)
cv.cvClearMemStorage(storage)
cv.cvEqualizeHist(grayscale, grayscale)
cascade = cv.cvLoadHaarClassifierCascade(haar_file, cv.cvSize(1, 1))
objects = cv.cvHaarDetectObjects(grayscale, cascade, storage, 1.2, 2,
cv.CV_HAAR_DO_CANNY_PRUNING,
cv.cvSize(100, 100))
# Draw dots where hands are
if objects:
for i in objects:
#cv.cvRectangle(image, cv.cvPoint( int(i.x), int(i.y)),
# cv.cvPoint(int(i.x+i.width), int(i.y+i.height)),
# cv.CV_RGB(0,255,0), 3, 8, 0)
center = cv.cvPoint(int(i.x + i.width / 2),
int(i.y + i.height / 2))
cv.cvCircle(image, center, 10, cv.CV_RGB(0, 0, 0), 5, 8, 0)
# Left side check
if center.x > box_forward_left[
0].x and center.x < box_backwards_left[
1].x and center.y > box_forward_left[
0].y and center.y < box_backwards_left[1].y:
set_speed('left', center)
# Right side check
if center.x > box_forward_right[
0].x and center.x < box_backwards_right[
1].x and center.y > box_forward_right[
0].y and center.y < box_backwards_right[1].y:
set_speed('right', center)
def flip(self, flip):
"""
Flips the image
Arguments:
- self: The main object pointer.
- flip: Dictionary with keys "hor" and "ver" with values True/False.
"""
if "hor" or "both" in flip:
cv.cvFlip( self.__image, self.__image, 1)
if "ver" or "both" in flip:
cv.cvFlip( self.__image, self.__image, 0)
return self.__image
def timerEvent(self, ev): # Fetch a frame from the video camera frame = highgui.cvQueryFrame(self.cap) img_orig = cv.cvCreateImage(cv.cvSize(frame.width,frame.height),cv.IPL_DEPTH_8U, frame.nChannels) if (frame.origin == cv.IPL_ORIGIN_TL): cv.cvCopy(frame, img_orig) else: cv.cvFlip(frame, img_orig, 0) # Create a grey frame to clarify data #img = self.detect_face(frame_copy) img = self.detect_squares(frame_copy) img_pil = adaptors.Ipl2PIL(img) s = StringIO() img_pil.save(s, "PNG") s.seek(0) q_img = QImage() q_img.loadFromData(s.read()) bitBlt(self, 0, 0, q_img)
def timerEvent(self, ev):
# Fetch a frame from the video camera
frame = highgui.cvQueryFrame(self.cap)
img_orig = cv.cvCreateImage(cv.cvSize(frame.width, frame.height),
cv.IPL_DEPTH_8U, frame.nChannels)
if (frame.origin == cv.IPL_ORIGIN_TL):
cv.cvCopy(frame, img_orig)
else:
cv.cvFlip(frame, img_orig, 0)
# Create a grey frame to clarify data
#img = self.detect_face(frame_copy)
img = self.detect_squares(frame_copy)
img_pil = adaptors.Ipl2PIL(img)
s = StringIO()
img_pil.save(s, "PNG")
s.seek(0)
q_img = QImage()
q_img.loadFromData(s.read())
bitBlt(self, 0, 0, q_img)
hsv = cv.cvCreateImage (frame_size, 8, 3 )
# create the histogram
hist = cv.cvCreateHist ([hdims], cv.CV_HIST_ARRAY, hranges, 1)
while 1:
# do forever
# 1. capture the current image
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
my_grayscale = cv.cvCreateImage(frame_size, 8, 1)
mask = cv.cvCreateImage(frame_size, 8, 1)
cv.cvSet(mask, 1)
blob_overlay = False
while True:
# 1. capture the current image
frame = highgui.cvQueryFrame(capture)
if frame is None:
# no image captured... end the processing
break
# mirror the captured image
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):
def timerEvent(self, ev): # Fetch a frame from the video camera frame = highgui.cvQueryFrame(self.cap) img_orig = cv.cvCreateImage(cv.cvSize(frame.width,frame.height),cv.IPL_DEPTH_8U, frame.nChannels) if (frame.origin == cv.IPL_ORIGIN_TL): cv.cvCopy(frame, img_orig) else: cv.cvFlip(frame, img_orig, 0) # Create a grey frame to clarify data img_grey = cv.cvCreateImage(cv.cvSize(img_orig.width,img_orig.height), 8, 1) cv.cvCvtColor(img_orig, img_grey, cv.CV_BGR2GRAY) # Detect objects within the frame self.faces_storage = cv.cvCreateMemStorage(0) faces = self.detect_faces(img_grey) self.circles_storage = cv.cvCreateMemStorage(0) circles = self.detect_circles(img_grey) self.squares_storage = cv.cvCreateMemStorage(0) squares = self.detect_squares(img_grey, img_orig) self.lines_storage = cv.cvCreateMemStorage(0) lines = self.detect_lines(img_grey, img_orig) # Draw faces if faces: for face in faces: pt1, pt2 = self.face_points(face) cv.cvRectangle(img_orig, pt1, pt2, cv.CV_RGB(255,0,0), 3, 8, 0) # Draw lines if lines: for line in lines: cv.cvLine(img_orig, line[0], line[1], cv.CV_RGB(255,255,0), 3, 8) # Draw circles if circles: for circle in circles: cv.cvCircle(img_orig, cv.cvPoint(cv.cvRound(circle[0]),cv.cvRound(circle[1])),cv.cvRound(circle[2]),cv.CV_RGB(0,0,255),3,8,0) # Draw squares if squares: 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_orig, [pt], 1, cv.CV_RGB(0,255,0), 3, cv.CV_AA, 0) i += 4 # Resize the image to display properly within the window # CV_INTER_NN - nearest-neigbor interpolation, # CV_INTER_LINEAR - bilinear interpolation (used by default) # CV_INTER_AREA - resampling using pixel area relation. (preferred for image decimation) # CV_INTER_CUBIC - bicubic interpolation. img_display = cv.cvCreateImage(cv.cvSize(self.width(),self.height()), 8, 3) cv.cvResize(img_orig, img_display, cv.CV_INTER_NN) img_pil = adaptors.Ipl2PIL(img_display) s = StringIO() img_pil.save(s, "PNG") s.seek(0) q_img = QImage() q_img.loadFromData(s.read()) bitBlt(self, 0, 0, q_img)
def read(self): '''Flip the cvMat obtained from input using the flip_mode setting''' flip=self.input.read() if self.enabled: cv.cvFlip(flip,None,self.flip_mode) return flip
def timerEvent(self, ev):
# Fetch a frame from the video camera
frame = highgui.cvQueryFrame(self.cap)
img_orig = cv.cvCreateImage(cv.cvSize(frame.width, frame.height),
cv.IPL_DEPTH_8U, frame.nChannels)
if (frame.origin == cv.IPL_ORIGIN_TL):
cv.cvCopy(frame, img_orig)
else:
cv.cvFlip(frame, img_orig, 0)
# Create a grey frame to clarify data
img_grey = cv.cvCreateImage(cv.cvSize(img_orig.width, img_orig.height),
8, 1)
cv.cvCvtColor(img_orig, img_grey, cv.CV_BGR2GRAY)
# Detect objects within the frame
self.faces_storage = cv.cvCreateMemStorage(0)
faces = self.detect_faces(img_grey)
self.circles_storage = cv.cvCreateMemStorage(0)
circles = self.detect_circles(img_grey)
self.squares_storage = cv.cvCreateMemStorage(0)
squares = self.detect_squares(img_grey, img_orig)
self.lines_storage = cv.cvCreateMemStorage(0)
lines = self.detect_lines(img_grey, img_orig)
# Draw faces
if faces:
for face in faces:
pt1, pt2 = self.face_points(face)
cv.cvRectangle(img_orig, pt1, pt2, cv.CV_RGB(255, 0, 0), 3, 8,
0)
# Draw lines
if lines:
for line in lines:
cv.cvLine(img_orig, line[0], line[1], cv.CV_RGB(255, 255, 0),
3, 8)
# Draw circles
if circles:
for circle in circles:
cv.cvCircle(
img_orig,
cv.cvPoint(cv.cvRound(circle[0]), cv.cvRound(circle[1])),
cv.cvRound(circle[2]), cv.CV_RGB(0, 0, 255), 3, 8, 0)
# Draw squares
if squares:
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_orig, [pt], 1, cv.CV_RGB(0, 255, 0), 3,
cv.CV_AA, 0)
i += 4
# Resize the image to display properly within the window
# CV_INTER_NN - nearest-neigbor interpolation,
# CV_INTER_LINEAR - bilinear interpolation (used by default)
# CV_INTER_AREA - resampling using pixel area relation. (preferred for image decimation)
# CV_INTER_CUBIC - bicubic interpolation.
img_display = cv.cvCreateImage(cv.cvSize(self.width(), self.height()),
8, 3)
cv.cvResize(img_orig, img_display, cv.CV_INTER_NN)
img_pil = adaptors.Ipl2PIL(img_display)
s = StringIO()
img_pil.save(s, "PNG")
s.seek(0)
q_img = QImage()
q_img.loadFromData(s.read())
bitBlt(self, 0, 0, q_img)
if frame is None:
# no image captured... end the processing
break
if image is None:
# create the images we need
image = cv.cvCreateImage (cv.cvGetSize (frame), 8, 3)
image.origin = frame.origin
hsv = cv.cvCreateImage( cv.cvGetSize(frame), 8, 3 )
hue = cv.cvCreateImage( cv.cvGetSize(frame), 8, 1 )
mask = cv.cvCreateImage( cv.cvGetSize(frame), 8, 1 )
backproject = cv.cvCreateImage( cv.cvGetSize(frame), 8, 1 )
hist = cv.cvCreateHist( [hdims], cv.CV_HIST_ARRAY, hranges, 1 )
# flip the image
cv.cvFlip (frame, image, 1)
cv.cvCvtColor( image, hsv, cv.CV_BGR2HSV)
cv.cvLine(image, cv.cvPoint(0, image.height/2), cv.cvPoint(image.width, image.height/2),
cv.CV_RGB(0,255,0), 2, 8, 0 )
cv.cvLine(image, cv.cvPoint(image.width/2, 0), cv.cvPoint(image.width/2, image.height),
cv.CV_RGB(0,255,0), 2, 8, 0 )
if track_object:
_vmin = vmin
_vmax = vmax
cv.cvInRangeS( hsv,
cv.cvScalar( 0, smin,min(_vmin,_vmax),0),
highgui.cvNamedWindow (win_name, highgui.CV_WINDOW_AUTOSIZE)
# create the trackbar
highgui.cvCreateTrackbar (trackbar_name, win_name, 1, 100, on_trackbar)
# show the image
on_trackbar (0)
frame_copy = None
while True:
image = highgui.cvQueryFrame( capture );
if( not image ):
break;
if( not frame_copy ):
frame_copy = cv.cvCreateImage( cv.cvSize(image.width,image.height),
cv.IPL_DEPTH_8U, image.nChannels );
if( image.origin == cv.IPL_ORIGIN_TL ):
cv.cvCopy( image, frame_copy );
else:
cv.cvFlip( image, frame_copy, 0 );
gray = cv.cvCreateImage (cv.cvSize (image.width, image.height), 8, 1)
edge = cv.cvCreateImage (cv.cvSize (image.width, image.height), 8, 1)
cv.cvCvtColor (image, gray, cv.CV_BGR2GRAY)
highgui.cvShowImage (win_name, col_edge)
cv.cvFlip( image, frame_copy, 0 );
if( highgui.cvWaitKey( 10 ) >= 0 ):
break;
if frame is None:
# no image captured... end the processing
break
if image is None:
# create the images we need
image = cv.cvCreateImage(cv.cvGetSize(frame), 8, 3)
image.origin = frame.origin
hsv = cv.cvCreateImage(cv.cvGetSize(frame), 8, 3)
hue = cv.cvCreateImage(cv.cvGetSize(frame), 8, 1)
mask = cv.cvCreateImage(cv.cvGetSize(frame), 8, 1)
backproject = cv.cvCreateImage(cv.cvGetSize(frame), 8, 1)
hist = cv.cvCreateHist([hdims], cv.CV_HIST_ARRAY, hranges, 1)
# flip the image
cv.cvFlip(frame, image, 1)
cv.cvCvtColor(image, hsv, cv.CV_BGR2HSV)
cv.cvLine(image, cv.cvPoint(0, image.height / 2),
cv.cvPoint(image.width, image.height / 2),
cv.CV_RGB(0, 255, 0), 2, 8, 0)
cv.cvLine(image, cv.cvPoint(image.width / 2, 0),
cv.cvPoint(image.width / 2, image.height),
cv.CV_RGB(0, 255, 0), 2, 8, 0)
if track_object:
_vmin = vmin
_vmax = vmax