def detect(image):
image_size = cv.GetSize(image)
# create grayscale version
grayscale = cv.CreateImage(image_size, 8, 1)
cv.CvtColor(image, grayscale, cv.BGR2GRAY)
# create storage
storage = cv.CreateMemStorage(0)
cv.ClearMemStorage(storage)
# equalize histogram
cv.EqualizeHist(grayscale, grayscale)
# detect objects
cascade = cv.LoadHaarClassifierCascade('haarcascade_frontalface_alt.xml',
cv.Size(1, 1))
faces = cv.HaarDetectObjects(grayscale, cascade, storage, 1.2, 2,
cv.HAAR_DO_CANNY_PRUNING, cv.Size(50, 50))
if faces:
print 'face detected!'
for i in faces:
cv.Rectangle(image, cv.Point(int(i.x), int(i.y)),
cv.Point(int(i.x + i.width), int(i.y + i.height)),
cv.RGB(0, 255, 0), 3, 8, 0)
def detect(self, image):
size = cv.GetSize(image)
# create grayscale version
grayscale = cv.CreateImage(size, 8, 1)
cv.CvtColor(image, grayscale, cv.BGR2GRAY)
# create and clear storage
storage = cv.CreateMemStorage(0)
cv.ClearMemStorage(storage)
# equalize histogram
cv.EqualizeHist(grayscale, grayscale)
# detect faces
faces = cv.HaarDetectObjects(grayscale, self.face_cascade, storage,
1.2, 2, cv.HAAR_DO_CANNY_PRUNING,
self.face_size)
if faces:
# faces detected
for i in faces:
cv.Rectangle(image, cv.Point(int(i.x), int(i.y)),
cv.Point(int(i.x + i.width), int(i.y + i.height)),
cv.RGB(0, 255, 0), 3, 8, 0)
detected = True
is_face = True
else:
# detect body
bodies = cv.HaarDetectObjects(grayscale, self.body_cascade,
storage, 1.1, 3, 0, self.body_size)
if bodies:
# body detected
for i in bodies:
cv.Rectangle(
image, cv.Point(int(i.x), int(i.y)),
cv.Point(int(i.x + i.width), int(i.y + i.height)),
cv.RGB(0, 255, 0), 3, 8, 0)
detected = True
is_face = False
else:
detected = False
is_face = False
# release resources we don't need any more
cv.ReleaseImage(grayscale)
cv.ReleaseMemStorage(storage)
return (detected, is_face)
class ARSystem:
size = (320, 240)
if 'darwin' in os.uname()[0].lower():
size = (640, 480)
cvsize = cv.Size(size[0], size[1])
image = cv.CreateImage(cvsize, CVtypes.IPL_DEPTH_8U, 3)
grayImage = cv.CreateImage(cvsize, CVtypes.IPL_DEPTH_8U, 1)
maskImage = cv.CreateImage(cvsize, CVtypes.IPL_DEPTH_8U, 1)
backprojectImage = cv.CreateImage(cvsize, CVtypes.IPL_DEPTH_8U, 1)
modifiedImage = cv.CreateImage(cvsize, CVtypes.IPL_DEPTH_8U, 3)
hsvImage = cv.CreateImage(cvsize, CVtypes.IPL_DEPTH_8U, 3)
histDims = 32
histRanges = [[50, 110]]
histogram = cv.CreateHist(1, [histDims], CVtypes.CV_HIST_ARRAY, histRanges,
1)
hsvPlanes = [
cv.CreateImage(cvsize, CVtypes.IPL_DEPTH_8U, 1),
cv.CreateImage(cvsize, CVtypes.IPL_DEPTH_8U, 1),
cv.CreateImage(cvsize, CVtypes.IPL_DEPTH_8U, 1),
]
rgbPlanes = [
cv.CreateImage(cvsize, CVtypes.IPL_DEPTH_8U, 1),
cv.CreateImage(cvsize, CVtypes.IPL_DEPTH_8U, 1),
cv.CreateImage(cvsize, CVtypes.IPL_DEPTH_8U, 1),
]
work1 = []
work3 = []
cvStorage = []
for i in range(10):
work1.append(cv.CreateImage(cvsize, CVtypes.IPL_DEPTH_8U, 1))
work3.append(cv.CreateImage(cvsize, CVtypes.IPL_DEPTH_8U, 3))
cvStorage.append(cv.CreateMemStorage(0))
def __init__(self):
self.dataFiles = df = [
'data/1_2_3_4_5_6.cfg',
'data/7_8_9_10_11_12.cfg',
'data/13_14_15_16_17_18.cfg',
'data/19_20_21_22_23_24.cfg',
]
self.multiDisplayDict = mdd = {
df[0]: self.drawBottomLeft,
df[1]: self.drawTopLeft,
df[2]: self.drawBottomRight,
df[3]: self.drawTopRight,
}
_AR.Init(
width=self.size[0],
height=self.size[1],
singleDisplayDict={0: draw2},
multiDisplayDict=mdd,
initFunc=self.Init,
preRender=self.preRender,
render=self.render,
preDraw=self.preDraw,
verbosity=0,
)
def frobNorm(self, mat1, mat2):
ds = 0
for i in range(16):
d = mat1[i] - mat2[i]
ds += d * d
return numpy.sqrt(ds)
frameNumber = 0
def preDraw(self):
frameNumber += 1
self.mvMats = mvMats = [
_AR.GetMultiMV('data/1_2_3_4_5_6.cfg'),
_AR.GetMultiMV('data/7_8_9_10_11_12.cfg'),
_AR.GetMultiMV('data/13_14_15_16_17_18.cfg'),
_AR.GetMultiMV('data/19_20_21_22_23_24.cfg'),
]
norms = []
found = False
for last, current in mvMats:
if frameNumber > 10:
pass
if current != 0:
pass
if last != 0:
norms.append(self.frobNorm(current, last))
else:
norms.append(None)
#print norms
markerLeftX = 30
def drawBottomLeft(self):
glColor(0, 1, 0)
sphereSize = 10
glPushMatrix()
glTranslate(0, 0, sphereSize)
glutSolidSphere(10, 10, sphereSize)
glPopMatrix()
cubeSize = 6
glPushMatrix()
glTranslate(20, 0, cubeSize)
glutSolidCube(cubeSize)
glPopMatrix()
glColor(1, 0, 0)
glBegin(GL_QUADS)
glVertex3f(-self.markerLeftX, -self.markerLeftX, 0)
glVertex3f(-self.markerLeftX, self.markerLeftX, 0)
glVertex3f(self.markerLeftX, self.markerLeftX, 0)
glVertex3f(self.markerLeftX, -self.markerLeftX, 0)
glEnd()
def drawBottomRight(self):
glColor(0, 1, 0)
glBegin(GL_QUADS)
glVertex3f(-self.markerLeftX, -self.markerLeftX, 0)
glVertex3f(-self.markerLeftX, self.markerLeftX, 0)
glVertex3f(self.markerLeftX, self.markerLeftX, 0)
glVertex3f(self.markerLeftX, -self.markerLeftX, 0)
glEnd()
def drawTopLeft(self):
glColor(1, 0, 1)
glBegin(GL_QUADS)
glVertex3f(-self.markerLeftX, -self.markerLeftX, 0)
glVertex3f(-self.markerLeftX, self.markerLeftX, 0)
glVertex3f(self.markerLeftX, self.markerLeftX, 0)
glVertex3f(self.markerLeftX, -self.markerLeftX, 0)
glEnd()
def drawTopRight(self):
glColor(1, 1, 0)
glBegin(GL_QUADS)
glVertex3f(-self.markerLeftX, -self.markerLeftX, 0)
glVertex3f(-self.markerLeftX, self.markerLeftX, 0)
glVertex3f(self.markerLeftX, self.markerLeftX, 0)
glVertex3f(self.markerLeftX, -self.markerLeftX, 0)
glEnd()
def Run(self):
_AR.Run()
def Init(self):
glutKeyboardFunc(self.keyboard)
glutSpecialFunc(self.special)
if 'darwin' not in os.uname()[0].lower():
capture = self.getCapture()
b = 0.213794155745
c = 0.131609063828
#cv.SetCaptureProperty(capture,CVtypes.CV_CAP_PROP_BRIGHTNESS,0.514000152471)
#cv.SetCaptureProperty(capture,CVtypes.CV_CAP_PROP_CONTRAST,0.161806668155)
cv.SetCaptureProperty(capture, CVtypes.CV_CAP_PROP_BRIGHTNESS, b)
cv.SetCaptureProperty(capture, CVtypes.CV_CAP_PROP_CONTRAST, c)
displayType = 'mask'
def keyboard(self, key, x, y):
if ord(key) == 27:
sys.exit(0)
key = key.lower()
if key == 'h':
self.queHistSnap = True
elif key == 'c':
self.displayType = 'color'
elif key == 'b':
self.displayType = 'back'
elif key == 'g':
self.displayType = 'gray'
elif key == 'm':
self.displayType = 'mask'
def special(self, key, x, y):
capture = self.getCapture()
b = cv.GetCaptureProperty(capture, CVtypes.CV_CAP_PROP_BRIGHTNESS)
c = cv.GetCaptureProperty(capture, CVtypes.CV_CAP_PROP_CONTRAST)
if key == GLUT_KEY_DOWN:
b -= .1
elif key == GLUT_KEY_UP:
b += .1
elif key == GLUT_KEY_LEFT:
c -= .01
elif key == GLUT_KEY_RIGHT:
c += .01
cv.SetCaptureProperty(capture, CVtypes.CV_CAP_PROP_BRIGHTNESS, b)
cv.SetCaptureProperty(capture, CVtypes.CV_CAP_PROP_CONTRAST, c)
b = cv.GetCaptureProperty(capture, CVtypes.CV_CAP_PROP_BRIGHTNESS)
c = cv.GetCaptureProperty(capture, CVtypes.CV_CAP_PROP_CONTRAST)
print 'Brightness:', b
print 'Contrast:', c
print
def renderFrame(self, frame):
glEnable(GL_TEXTURE_2D)
internalFormat = GL_RGB
format = GL_BGR
if frame[0].nChannels == 1:
internalFormal, format = GL_LUMINANCE, GL_LUMINANCE
glTexImage2D(GL_TEXTURE_2D, 0, internalFormat, frame[0].width,
frame[0].height, 0, format, GL_UNSIGNED_BYTE,
imageAsArray(frame))
z = 0
glMatrixMode(GL_PROJECTION)
glLoadIdentity()
glMatrixMode(GL_MODELVIEW)
glPushMatrix()
glLoadIdentity()
glBegin(GL_POLYGON)
glTexCoord2f(0.0, 1.0)
glVertex3f(-1.0, -1.0, z)
glTexCoord2f(1.0, 1.0)
glVertex3f(1.0, -1.0, z)
glTexCoord2f(1.0, 0.0)
glVertex3f(1.0, 1.0, z)
glTexCoord2f(0.0, 0.0)
glVertex3f(-1.0, 1.0, z)
glEnd()
glPopMatrix()
glFlush()
glDisable(GL_TEXTURE_2D)
def render(self):
self.renderFrame(self.modifiedImage)
#print 'here'
def getFrame(self):
p = _AR.GetFrame()
ip = cast(c_void_p(p), POINTER(CVtypes.IplImage))
return ip
def getCapture(self):
p = _AR.GetCapture()
ip = cast(c_void_p(p), POINTER(CVtypes.CvCapture))
return ip
def preRender(self):
frame = self.getFrame()
capture = self.getCapture()
#print _AR.GetMultiMV('data/19_20_21_22_23_24.cfg')
#_AR.GetMultiMV('data/13_14_15_16_17_18.cfg')
#if 'darwin' in os.uname()[0].lower():
if 0:
settings = [
cv.GetCaptureProperty(capture, CVtypes.CV_CAP_PROP_FOURCC),
cv.GetCaptureProperty(capture, CVtypes.CV_CAP_PROP_BRIGHTNESS),
cv.GetCaptureProperty(capture, CVtypes.CV_CAP_PROP_CONTRAST),
cv.GetCaptureProperty(capture, CVtypes.CV_CAP_PROP_SATURATION),
cv.GetCaptureProperty(capture, CVtypes.CV_CAP_PROP_HUE),
]
print settings
size = cv.GetSize(frame)
fsize = size.width, size.height
size = cv.GetSize(self.image)
isize = size.width, size.height
if fsize == isize:
cv.Copy(frame, self.image)
else:
cv.Resize(
frame,
self.image,
CVtypes.CV_INTER_LINEAR,
#CVtypes.CV_INTER_CUBIC,
)
cv.CvtColor(self.image, self.hsvImage, CVtypes.CV_RGB2HSV)
cv.Split(self.hsvImage, self.hsvPlanes[0], self.hsvPlanes[1],
self.hsvPlanes[2], 0)
cv.CvtColor(self.image, self.grayImage, CVtypes.CV_RGB2GRAY)
if 1:
#cv.EqualizeHist(self.hsvPlanes[0],self.hsvPlanes[0])
#cv.EqualizeHist(self.hsvPlanes[2],self.hsvPlanes[2])
#cv.Merge(self.hsvPlanes[0],self.hsvPlanes[1],
# self.hsvPlanes[2],0, self.hsvImage)
#cv.CvtColor(self.hsvImage,self.image,CVtypes.CV_HSV2RGB)
cv.EqualizeHist(self.grayImage, self.grayImage)
cv.Split(self.image, self.rgbPlanes[0], self.rgbPlanes[1],
self.rgbPlanes[2], 0)
cv.Copy(self.image, self.modifiedImage)
#cv.CvtColor(self.grayImage,self.modifiedImage,CVtypes.CV_GRAY2RGB)
#self.backProject()
#self.getContours()
queHistSnap = False
histSnapTaken = False
def backProject(self):
work = self.work1[0]
#cv.Smooth(self.hsvImage,self.hsvImage,CVtypes.CV_GAUSSIAN,7,7);
cv.InRangeS(self.hsvImage, cv.Scalar(0, 30, 200, 0),
cv.Scalar(180, 256, 256, 0), self.maskImage)
cv.InRangeS(self.hsvImage, cv.Scalar(0, 30, 100, 0),
cv.Scalar(180, 256, 256, 0), work)
if self.queHistSnap:
cv.CalcHist([self.hsvPlanes[0]], self.histogram, 0, self.maskImage)
values = cv.GetMinMaxHistValue(self.histogram)
self.histSnapTaken = True
self.queHistSnap = False
if self.histSnapTaken:
cv.CalcBackProject([self.hsvPlanes[0]], self.backprojectImage,
self.histogram)
cv.And(self.backprojectImage, work, self.backprojectImage, 0)
if self.displayType == 'color':
cv.Copy(self.image, self.modifiedImage)
elif self.displayType == 'back':
cv.CvtColor(self.backprojectImage, self.modifiedImage,
CVtypes.CV_GRAY2RGB)
elif self.displayType == 'gray':
cv.CvtColor(self.grayImage, self.modifiedImage,
CVtypes.CV_GRAY2RGB)
elif self.displayType == 'mask':
cv.CvtColor(self.maskImage, self.modifiedImage,
CVtypes.CV_GRAY2RGB)
self.getContours(self.backprojectImage)
#self.getContours(self.maskImage)
def getContours(self, image):
cv.Smooth(image, image, CVtypes.CV_GAUSSIAN, 17, 17)
#cv.CvtColor(image,self.modifiedImage,CVtypes.CV_GRAY2RGB);
cv.Threshold(image, image, 128, 255, CVtypes.CV_THRESH_BINARY)
#cv.CvtColor(image,self.modifiedImage,CVtypes.CV_GRAY2RGB);
cv.Canny(image, image, 50, 200)
#cv.CvtColor(image,self.modifiedImage,CVtypes.CV_GRAY2RGB);
#cv.CvtColor(self.grayImage,self.modifiedImage,CVtypes.CV_GRAY2RGB);
#cv.Copy(frame,self.modifiedImage)
#return
contour = POINTER(cv.Seq)()
if 1:
cv.FindContours(
image,
#self.grayImage,
self.cvStorage[0],
byref(contour),
sizeof(cv.Contour),
CVtypes.CV_RETR_CCOMP,
CVtypes.CV_CHAIN_APPROX_SIMPLE,
cv.Point(0, 0),
)
contourBlocks = []
if contour:
cSeq = cast(contour, POINTER(cv.Seq))
ellipses = []
while cSeq:
contours = []
total = cSeq[0].total
if total >= 6:
box = cv.FitEllipse2(cSeq)
ellipses.append(box)
#print
#print
for i in range(total):
next = CVtypes.CV_GET_SEQ_ELEM(cv.Seq, cSeq, i)
nContour = cast(next, POINTER(cv.Contour))
rect = nContour[0].rect
contours.append(rect)
#print rect
contourBlocks.append(contours)
cSeq = cast(cSeq[0].h_next, POINTER(cv.Seq))
#print ellipses[0]
#print
if 1:
if contourBlocks:
bboxes = []
for contours in contourBlocks:
c0 = contours[0]
bbox = [self.size[0] + 1, self.size[1] + 1, -1, -1]
for i, c in enumerate(contours):
#if i==(len(contours)-1): break
x0, y0, x1, y1 = c.x, c.y, c.width, c.height
if ((x0 > self.size[0]) or (x1 > self.size[0])
or (y0 > self.size[1]) or (y1 > self.size[1])
or (x0 <= 0) or (x1 <= 0) or (y0 <= 0)
or (y1 <= 0)):
x0, y0, x1, y1 = c0.x, c0.y, c0.width, c0.height
continue
if x0 < bbox[0]: bbox[0] = x0
if x1 < bbox[0]: bbox[0] = x0
if x0 > bbox[2]: bbox[2] = x0
if x1 > bbox[2]: bbox[2] = x0
if y0 < bbox[1]: bbox[1] = y0
if y1 < bbox[1]: bbox[1] = y0
if y0 > bbox[3]: bbox[3] = y0
if y1 > bbox[3]: bbox[3] = y0
cv.Line(
self.modifiedImage,
cv.Point(x0, y0),
cv.Point(x1, y1),
#cv.Point(contours[i+1].x,contours[i+1].y),
CVtypes.CV_RGB(255, 0, 0),
1,
1,
)
bboxes.append(bbox)
for bbox in bboxes:
cv.Rectangle(
self.modifiedImage,
cv.Point(bbox[0], bbox[1]),
cv.Point(bbox[2], bbox[3]),
CVtypes.CV_RGB(0, 255, 255),
1,
8,
)
cx, cy = 0, 0
num = 0
for e in ellipses:
x = e.center.x
y = e.center.y
center = cv.Point(int(x), int(y))
size = cv.Size(int(e.size.width), int(e.size.height))
if size.width > self.size[0] or size.height > self.size[1]:
continue
cx += x
cy += y
num += 1
angle = -e.angle
cv.Ellipse(
self.modifiedImage,
center,
size,
angle,
0,
360,
CVtypes.CV_RGB(0, 255, 255),
)
if num:
cx /= num
cy /= num
cv.Circle(
self.modifiedImage,
cv.Point(int(cx), int(cy)),
20,
CVtypes.CV_RGB(255, 255, 0),
)
cv.DrawContours(
self.modifiedImage,
contour,
CVtypes.CV_RGB(255, 0, 0),
CVtypes.CV_RGB(0, 255, 0),
1,
1,
)
RIGHT = 3 UP = 4 DOWN = 5 #Color donstant definitions RED = cv.RGB(255,0,0) GREEN = cv.RGB (0,220,0) BLUE = cv.RGB (0,0,255) YELLOW = cv.RGB(255,255,0); ORANGE = cv.RGB(255,127,0); MAGENTA = cv.RGB(255,0,255); # other constants scale = 1 cascade = None storage = cv.CreateMemStorage(0) cascade_name = "xml/haarcascade_frontalface_alt.xml" min_size = cv.Size(FACE_MIN_SIZE,FACE_MIN_SIZE) image_scale = 1.3 haar_scale = 1.2 min_neighbors = 2 haar_flags = cv.HAAR_DO_CANNY_PRUNING age = 0 trackedFaces = [] IPL_DEPTH_8U = 8 gray = 0 small_img = 0 osName = os.name fname_temp="" ### end of Face detection constants
def detect(image):
image_size = cv.GetSize(image)
# create grayscale version
grayscale = cv.CreateImage(image_size, 8, 1)
cv.CvtColor(image, grayscale, cv.BGR2GRAY)
# create storage
storage = cv.CreateMemStorage(0)
cv.ClearMemStorage(storage)
# equalize histogram
cv.EqualizeHist(grayscale, grayscale)
# detect objects
cascade = cv.LoadHaarClassifierCascade('haarcascade_frontalface_alt.xml',
cv.Size(1, 1))
faces = cv.HaarDetectObjects(grayscale, cascade, storage, 1.2, 2,
cv.HAAR_DO_CANNY_PRUNING, cv.Size(50, 50))
if faces:
print 'face detected!'
for i in faces:
cv.Rectangle(image, cv.Point(int(i.x), int(i.y)),
cv.Point(int(i.x + i.width), int(i.y + i.height)),
cv.RGB(0, 255, 0), 3, 8, 0)
# create windows
cv.NamedWindow('Camera', cv.WINDOW_AUTOSIZE)
# create capture device
device = 0 # assume we want first device
capture = cv.CreateCameraCapture(0)
cv.SetCaptureProperty(capture, cv.CAP_PROP_FRAME_WIDTH, 640)
cv.SetCaptureProperty(capture, cv.CAP_PROP_FRAME_HEIGHT, 480)
# check if capture device is OK
if not capture:
print "Error opening capture device"
sys.exit(1)
while 1:
# do forever
# capture the current frame
frame = cv.QueryFrame(capture)
if frame is None:
break
# mirror
cv.Flip(frame, None, 1)
# face detection
detect(frame)
# display webcam image
cv.ShowImage('Camera', frame)
# handle events
k = cv.WaitKey(10)
if k == 0x1b: # ESC
print 'ESC pressed. Exiting ...'
break