def update(self, image):
self._faces = []
if utils.isGray(image):
image = cv2.equalizeHist(image)
else:
image = cv2.cvtColor(image, cv2.cv.CV_BGR2GRAY)
minSize = utils.widthHeightDividedBy(image, 8)
faceRects = self._faceClassifier.detectMultiScale(image, self.scaleFactor, self.minNeighbors, self.flags, minSize)
if faceRects is not None:
for faceRect in faceRects:
face = Face()
face.faceRect = faceRect
x, y, w, h = faceRect
searchRect = (x+w/7, y, w*2/7, h/2)
face.leftEyeRect = self._detectOneObject(self._eyeClassifier, image, searchRect, 64)
searchRect = (x+w*4/7, y, w*2/7, h/2)
face.rightEyeRect = self._detectOneObject(self._eyeClassifier, image, searchRect, 64)
searchRect = (x+w/4, y+h/4, w/2, h/2)
face.noseRect = self._detectOneObject(self._noseClassifier, image, searchRect, 32)
searchRect = (x+w/6, y+h*2/3, w*2/3, h/3)
face.mouthRect = self._detectOneObject(self._mouthClassifier, image, searchRect, 16)
self._faces.append(face)
def drawDebugRects(self, image):
"""Draw rectangles around the tracked facial features."""
if utils.isGray(image):
faceColor = 255
leftEyeColor = 255
rightEyeColor = 255
noseColor = 255
mouthColor = 255
smileColor = 255
eyepair_smallColor = 255
else:
faceColor = (255, 255, 255) # white
leftEyeColor = (0, 0, 255) # red
rightEyeColor = (0, 255, 255) # yellow
noseColor = (0, 255, 0) # green
mouthColor = (255, 0, 0) # blue
smileColor = (255, 255, 255) # white
# eyepair_smallColor = (0, 0, 255) # red
for face in self.faces:
rects.outlineRect(image, face.faceRect, faceColor)
rects.outlineRect(image, face.leftEyeRect, leftEyeColor)
rects.outlineRect(image, face.rightEyeRect, rightEyeColor)
rects.outlineRect(image, face.noseRect, noseColor)
rects.outlineRect(image, face.mouthRect, mouthColor)
rects.outlineRect(image, face.smileRect, smileColor)
def copyRect(src,
dst,
srcRect,
dstRect,
mask=None,
interpolation=cv2.INTER_LINEAR):
"""Copy part of the source to part of the destination."""
x0, y0, w0, h0 = srcRect
x1, y1, w1, h1 = dstRect
# Resize the contents of the source sub-rectangle.
# Put the result in the destination sub-rectangle.
if mask is None:
dst[y1:y1+h1, x1:x1+w1] = \
cv2.resize(src[y0:y0+h0, x0:x0+w0], (w1, h1),
interpolation = interpolation)
else:
if not utils.isGray(src):
# Convert the mask to 3 channels, like the image.
mask = mask.repeat(3).reshape(h0, w0, 3)
# Perform the copy, with the mask applied.
dst[y1:y1+h1, x1:x1+w1] = \
numpy.where(cv2.resize(mask, (w1, h1),
interpolation = \
cv2.INTER_NEAREST),
cv2.resize(src[y0:y0+h0, x0:x0+w0], (w1, h1),
interpolation = interpolation),
dst[y1:y1+h1, x1:x1+w1])
def drawDebugRects(self, image):
"""
:param image: 全体画像
:return: None
"""
if utils.isGray(image):
faceColor = 255
leftEyeColor = 255
rightEyeColor = 255
noseColor = 255
mouthColor = 255
else:
faceColor = (255, 255, 255) # 白
leftEyeColor = (0, 0, 255) # 赤
rightEyeColor = (0, 255, 255) # 黄
noseColor = (0, 255, 0) # 緑
mouthColor = (255, 0, 0) # 青
for face in self.faces:
# rects.outlineRect(image, face.faceRect , faceColor )
# rects.outlineRect(image, face.leftEyeRect , leftEyeColor )
# rects.outlineRect(image, face.rightEyeRect, rightEyeColor)
# rects.outlineRect(image, face.noseRect , noseColor )
# rects.outlineRect(image, face.mouthRect , mouthColor )
rects.outlineRectWithTitle(image, face.faceRect, faceColor, 'Face')
rects.outlineRectWithTitle(image, face.leftEyeRect, leftEyeColor,
'Left Eye')
rects.outlineRectWithTitle(image, face.rightEyeRect, rightEyeColor,
'Right Eye')
rects.outlineRectWithTitle(image, face.noseRect, noseColor, 'Nose')
rects.outlineRectWithTitle(image, face.mouthRect, mouthColor,
'Mouth')
def copyRect(src, dst, srcRect, dstRect, mask = None,
interpolation = cv2.INTER_LINEAR):
"""Copy part of the source to part of the destination."""
x0, y0, w0, h0 = srcRect
x1, y1, w1, h1 = dstRect
# Resize the contents of the source sub-rectangle.
# Put the result in the destination sub-rectangle.
if mask is None:
dst[y1:y1+h1, x1:x1+w1] = \
cv2.resize(src[y0:y0+h0, x0:x0+w0], (w1, h1),
interpolation = interpolation)
else:
if not utils.isGray(src):
# Convert the mask to 3 channels, like the image.
mask = mask.repeat(3).reshape(h0, w0, 3)
# Perform the copy, with the mask applied.
dst[y1:y1+h1, x1:x1+w1] = \
numpy.where(cv2.resize(mask, (w1, h1),
interpolation = \
cv2.INTER_NEAREST),
cv2.resize(src[y0:y0+h0, x0:x0+w0], (w1, h1),
interpolation = interpolation),
dst[y1:y1+h1, x1:x1+w1])
def update(self, image):
self.swapfaces = []
if utils.isGray(image):
cv2.equalizeHist(image, image)
else:
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
cv2.equalizeHist(image, image)
minscale = utils.divideHeightWidth(image, 8)
facerects = self.facedetector.detectMultiScale(image, self.scale,
self.neighbour,
self.flag, minscale)
facearea = Face()
self.swapfaces.append(facerects)
if len(facerects) > 0:
for face in facerects:
facearea.face = face
x, y, w, h = face
searcharea = (x + w / 7, y, w * 2 / 7, h / 2)
facearea.lefteye = FaceDetect.detectObject(
self, self.lefteyedetector, image, searcharea, 64)
searcharea = (x + w * 4 / 7, y, w * 2 / 7, h / 2)
facearea.righteye = FaceDetect.detectObject(
self, self.righteyedetector, image, searcharea, 64)
#searcharea = (x+w/4,y+h/4,w/2,h/2)
#facearea.nose = detectObject(self.nosedetector,image,searcharea,32)
searcharea = (x + w / 3, y + h * 2 / 3, w * 2 / 3, h / 3)
facearea.smile = FaceDetect.detectObject(
self, self.smiledetector, image, searcharea, 16)
self.faces.append(facearea)
def drawLinesFromCenter(self, image):
"""Draw a line from the center of the image to the center of the tracked face."""
if utils.isGray(image):
faceColor = 255
else:
faceColor = (255, 255, 255) # white
for face in self.faces:
lines.drawLine(image, face.faceRect, faceColor)
def update(self, image):
"""Update the tracked facial features."""
self._faces = []
if utils.isGray(image):
image = cv2.equalizeHist(image)
else:
#image = cv2.cvtColor(image, cv2.cv.CV_BGR2GRAY)
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
cv2.equalizeHist(image, image)
minSize = utils.widthHeightDividedBy(image, 8)
faceRects = self._faceClassifier.detectMultiScale(image,
self.scaleFactor,
self.minNeighbors,
self.flags,
minSize)
if faceRects is not None:
for faceRect in faceRects:
face = Face()
face.faceRect = faceRect
x, y, w, h = faceRect
# Seek an eye in the upper-left part of the face.
searchRect = (int(x+w/7), y, int(w*2/7), int(h/2))
face.leftEyeRect = self._detectOneObject(self._eyeClassifier, image, searchRect, 64)
# Seek an eye in the upper-right part of the face.
searchRect = (int(x+w*4/7), y, int(w*2/7), int(h/2))
face.rightEyeRect = self._detectOneObject(self._eyeClassifier, image, searchRect, 64)
# Seek a nose in the middle part of the face.
searchRect = (int(x+w/4), int(y+h/4), int(w/2), int(h/2))
face.noseRect = self._detectOneObject(self._noseClassifier, image, searchRect, 32)
# Seek a mouth in the lower-middle part of the face.
searchRect = (int(x+w/6), int(y+h*2/3), int(w*2/3), int(h/3))
face.mouthRect = self._detectOneObject(self._mouthClassifier, image, searchRect, 16)
# Seek a smile in the lower-middle part of the face.
searchRect = (int(x+w/6), int(y+h*2/3), int(w*2/3), int(h/3))
face.smileRect = self._detectOneObject(self._smileClassifier, image, searchRect, 16)
# Seek a eyepair_small in the left-middle part of the face.
# searchRect = (x+w/7, y, w*5/7, h/2)
# face.eyepair_smallRect = self._detectOneObject(self._eyepair_smallClassifier, image, searchRect, 16)
self._faces.append(face)
def update(self, image):
""" Update the tracked facial features """
# reset the features list
self._faces = []
# Equalize the variant. This makes the tracker more robust to variations in lighting
# Create greyscale variant of the image, if it isn't already, to improve performance
if utils.isGray(image):
image = cv2.equalizeHist(image)
else:
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
cv2.equalizeHist(image,image)
# Classify the image
minSize = utils.widthHeightDividedBy(image,8)
faceRects = self._faceClassifier.detectMultiScale(
image, self.scaleFactor, self.minNeighbours, self.flags, minSize)
# If we find viable matches, place them in the faces list
if faceRects is not None:
for faceRect in faceRects:
face = Face()
face.faceRect = faceRect
# Decompose the target feature
x,y,w,h = faceRect
# Seek an eye in the upper LHS of the face
searchRect = (x+w/7,y,w*2/7,h/2)
face.leftEyeRect = self._detectOneObject(
self._eyeClassifier, image, searchRect, 64
)
# Seek an eye in the upper RHS of the face
searchRect = (x+w*4/7,y,w*2/7,h/2)
face.rightEyeRect = self._detectOneObject(
self._eyeClassifier, image, searchRect, 64
)
# Seek a nose in the middle of the face
searchRect = (x+w/4,y+h/4,w/2,h/2)
face.noseRect = self._detectOneObject(
self._noseClassifier, image, searchRect, 32
)
# Seek a mouth in the lower third of the face
searchRect = (x+w/6,y+h*2/3,w*2/3,h/3)
face.mouthRect = self._detectOneObject(
self._eyeClassifier, image, searchRect, 16
)
self._faces.append(face)
def update(self, image):
"""Update the tracked facial features."""
self._faces = []
if utils.isGray(image):
image = cv2.equalizeHist(image)
else:
image = cv2.cvtColor(image, cv2.cv.CV_BGR2GRAY)
cv2.equalizeHist(image, image)
minSize = utils.widthHeightDividedBy(image, 8)
faceRects = self._faceClassifier.detectMultiScale(
image, self.scaleFactor, self.minNeighbors, self.flags,
minSize)
if faceRects is not None:
for faceRect in faceRects:
face = Face()
face.faceRect = faceRect
face.logging_faceZone(image)
x, y, w, h = faceRect
# Seek an eye in the upper-left part of the face.
searchRect = (x+w/7, y, w*2/7, h/2)
face.leftEyeRect = self._detectOneObject(
self._eyeClassifier, image, searchRect, 64)
# Seek an eye in the upper-right part of the face.
searchRect = (x+w*4/7, y, w*2/7, h/2)
face.rightEyeRect = self._detectOneObject(
self._eyeClassifier, image, searchRect, 64)
# Seek a nose in the middle part of the face.
searchRect = (x+w/4, y+h/4, w/2, h/2)
face.noseRect = self._detectOneObject(
self._noseClassifier, image, searchRect, 32)
# Seek a mouth in the lower-middle part of the face.
searchRect = (x+w/6, y+h*2/3, w*2/3, h/3)
face.mouthRect = self._detectOneObject(
self._mouthClassifier, image, searchRect, 16)
if(face.detectOrganCount>=1):
self._faces.append(face)
def extractSiftFeatures(image):
""" detect interest points in an image """
if not isGray(image):
# convert RGB image to gray image
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
sift = cv2.SIFT()
# kps: a list of keypoints
# des: numpy array of shape [Number_of_Keypoints x 128]
# each row represents an observation
kps, des = sift.detectAndCompute(image, None)
return des
def drawDebugRects(self, image):
"""Draw rectangles around the tracked facial features."""
if utils.isGray(image):
faceColor = 255
leftEyeColor = 255
rightEyeColor = 255
else:
faceColor = (255, 255, 255) # white
leftEyeColor = (0, 0, 255) # red
rightEyeColor = (0, 255, 255) # yellow
for face in self.faces:
rects.outlineRect(image, face.faceRect, faceColor)
rects.outlineRect(image, face.leftEyeRect, leftEyeColor)
rects.outlineRect(image, face.rightEyeRect,
rightEyeColor)
def update(self, image):
"""Update the tracked facial features."""
self._faces = []
if utils.isGray(image):
image = cv2.equalizeHist(image)
else:
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
cv2.equalizeHist(image, image)
minSize = utils.widthHeightDividedBy(image, 8)
print(minSize)
faceRects = self._faceClassifier.detectMultiScale(
image, self.scaleFactor, self.minNeighbors, self.flags, minSize)
print(faceRects)
if faceRects is not None:
for faceRect in faceRects:
face = Face()
face.faceRect = faceRect
x, y, w, h = faceRect
# Seek an eye in the upper-left part of the face.
searchRect = (x + w / 7, y, w * 2 / 7, h / 2)
face.leftEyeRect = self._detectOneObject(
self._eyeClassifier, image, searchRect, 64)
# Seek an eye in the upper-right part of the face.
searchRect = (x + w * 4 / 7, y, w * 2 / 7, h / 2)
face.rightEyeRect = self._detectOneObject(
self._eyeClassifier, image, searchRect, 64)
# Seek a nose in the middle part of the face.
searchRect = (x + w / 4, y + h / 4, w / 2, h / 2)
face.noseRect = self._detectOneObject(self._noseClassifier,
image, searchRect, 32)
# Seek a mouth in the lower-middle part of the face.
searchRect = (x + w / 6, y + h * 2 / 3, w * 2 / 3, h / 3)
face.mouthRect = self._detectOneObject(self._mouthClassifier,
image, searchRect, 16)
self._faces.append(face)
def drawRects(self, image):
"""Draw rectangles around the tracked facial feature"""
#White rectangles in a grayscale image
if utils.isGray(image):
faceColor = 255
else:
faceColor = (255, 255, 255) #White
for face in self._faces:
(x, y, w, h) = face.faceRect
cv2.rectangle(image, (x,y), (x+w, y+h), faceColor, 2)
for eyeRect in face.eyeRects:
(ex, ey, ew, eh) = eyeRect
cv2.rectangle(image, (x+ex, y+ey), (x+ex+ew, y+ey+eh), (0,255,0), 2)
def update(self, image):
self._faces = []
if utils.isGray(image):
image = cv2.equalizeHist(image)
else:
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
cv2.equalizeHist(image, image)
minSize = utils.widthHeightDividedBy(image, 8)
minSize = (int(minSize[0]), int(minSize[1]))
faceRects = self._faceClassifier.detectMultiScale(
image, self.scaleFactor, self.minNeighbors, self.flags, minSize)
if faceRects is not None:
for faceRect in faceRects:
face = Face()
face.faceRect = faceRect
x, y, w, h = faceRect
#buscar o olho e atualizar o lado esquerdo da face
searchRect = (x + w / 7, y, w * 2 / 7, h / 2)
face.leftEyeRect = self._detectOneObject(
self._eyeClassifier, image, searchRect, 64)
#buscar o olho e atualizar o lado direito da face
searchRect = (x + w * 4 / 7, y, w * 2 / 7, h / 2)
face.rightEyeRect = self._detectOneObject(
self._eyeClassifier, image, searchRect, 64)
#buscar nariz
searchRect = (x + w / 4, y + h / 4, w / 2, h / 2)
face.noseRect = self._detectOneObject(self._noseClassifier,
image, searchRect, 32)
#buscar boca
searchRect = (x + w / 6, y + h * 2 / 3, w * 2 / 3, h / 3)
face.mouthRect = self._detectOneObject(self._mouthClassifier,
image, searchRect, 16)
self._faces.append(face)
def copyRect(src,
dst,
srcRect,
dstRect,
mask=None,
interpolation=cv2.INTER_LINEAR):
x0, y0, w0, h0 = srcRect
x1, y1, w1, h1 = dstRect
if mask is None:
dst[y1:y1 + h1, x1:x1 + w1] = cv2.resize(src[y0:y0 + h0, x0:x0 + w0],
(w1, h1),
interpolation=interpolation)
else:
if not utils.isGray(src):
mask = mask.repeat(3).reshape(h0, w0, 3)
dst[y1:y1 + h1, x1:x1 + w1] = numpy.where(
cv2.resize(mask, (w1, h1), interpolation=cv2.INTER_NEAREST),
cv2.resize(src[y0:y0 + h0, x0:x0 + w0], (w1, h1),
interpolation=interpolation), dst[y1:y1 + h1, x1:x1 + w1])
def drawRect(self, image):
if utils.isGray(image):
faceColor = 255
leftEyeColor = 255
rightEyeColor = 255
noseColor = 255
mouthColor = 255
else:
faceColor = (255, 255, 255) # white
leftEyeColor = (0, 0, 255) # red
rightEyeColor = (0, 255, 255) # yellow
#noseColor = (0, 255, 0) # green
mouthColor = (255, 0, 0) # blue
for face in self.faces:
rects.outlineRect(image, faceColor, face.face)
rects.outlineRect(image, leftEyeColor, face.lefteye)
rects.outlineRect(image, rightEyeColor, face.righteye)
#rects.outlineRect(image, face.noseRect, noseColor)
rects.outlineRect(image, mouthColor, face.smile)
self.faces = []
def update(self, image):
self._faces = []
if not utils.isGray(image):
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
image = cv2.equalizeHist(image)
minFaceSize = utils.sizeDividedBy(image, 8)
faceRects = self._faceClassifier.detectMultiScale(
image, self.scaleFactor, self.minNeighbors, self.flags,
minFaceSize)
if faceRects is not None:
for faceRect in faceRects:
face = Face()
face.faceRect = faceRect
self._faces.append(face)
def show(self, frame):
# Find the frame's dimensions in (w, h) format.
frameSize = frame.shape[1::-1]
# Convert the frame to RGB, which Pygame requires.
if utils.isGray(frame):
conversionType = cv2.COLOR_GRAY2RGB
else:
conversionType = cv2.COLOR_BGR2RGB
rgbFrame = cv2.cvtColor(frame, conversionType)
# Convert the frame to Pygame's Surface type.
pygameFrame = pygame.image.frombuffer(
rgbFrame.tostring(), frameSize, 'RGB')
# Resize the window to match the frame.
displaySurface = pygame.display.set_mode(frameSize)
# Blit and display the frame.
displaySurface.blit(pygameFrame, (0, 0))
pygame.display.flip()
def drawDebugRects(self, image):
""" Draw rectangles around the tracked facial features """
if utils.isGray(image):
faceColor = 255
leftEyeColor = 255
rightEyeColor = 255
noseColor = 255
mouthColor = 255
else:
faceColor = (255,255,255)
leftEyeColor = (0,0,255)
rightEyeColor = (0,255,255)
noseColor = (0,255,0)
mouthColor = (255,0,0)
for face in self.faces:
rects.outlineRect(image, face.faceRect, faceColor)
rects.outlineRect(image, face.leftEyeRect, leftEyeColor)
rects.outlineRect(image, face.rightEyeRect, rightEyeColor)
rects.outlineRect(image, face.noseRect, noseColor)
rects.outlineRect(image, face.mouthRect, mouthColor)
def drawDebugRects(self, image):
if utils.isGray(image):
faceColor = 255
leftEyeColor = 255
rightEyeColor = 255
noseColor = 255
mouthColor = 255
else:
faceColor = (255, 255, 255) # white
leftEyeColor = (0, 0, 255) # red
rightEyeColor = (0, 255, 255) # yellow
noseColor = (0, 255, 0) # green
mouthColor = (255, 0, 0) # blue
for face in self.faces:
rects.outlineRect(image, face.faceRect, faceColor)
rects.outlineRect(image, face.leftEyeRect, leftEyeColor)
rects.outlineRect(image, face.rightEyeRect, rightEyeColor)
rects.outlineRect(image, face.noseRect, noseColor)
rects.outlineRect(image, face.mouthRect, mouthColor)
def show(self, frame):
# Find the frame's dimensions in (w, h) format.
frameSize = frame.shape[1::-1]
# Convert the frame to RGB, which Pygame requires.
if utils.isGray(frame):
conversionType = cv2.COLOR_GRAY2RGB
else:
conversionType = cv2.COLOR_BGR2RGB
rgbFrame = cv2.cvtColor(frame, conversionType)
# Convert the frame to Pygame's Surface type.
pygameFrame = pygame.image.frombuffer(
rgbFrame.tostring(), frameSize, 'RGB')
# Resize the window to match the frame.
displaySurface = pygame.display.set_mode(frameSize)
# Blit and display the frame.
displaySurface.blit(pygameFrame, (0, 0))
pygame.display.flip()
def drawDebugRects(self, image):
''' Draw rectanbles around the tracked facial features'''
if utils.isGray(image):
faceColor = 255
leftEyeColor = 255
rightEyeColor = 255
noseColor = 255
mouthColor = 255
else:
faceColor = (255, 255, 255) # White
leftEyeColor = (0, 0, 255) # Red
rightEyeColor = (0, 255, 255) # yellow
noseColor = (0, 255, 0) # green
mouthColor = (255, 0, 0) # blue
for face in self.faces:
rects.outlineRect(image, face.faceRect, faceColor)
rects.outlineRect(image, face.leftEyeRect, leftEyeColor)
rects.outlineRect(image, face.rightEyeRect, rightEyeColor)
rects.outlineRect(image, face.noseRect, noseColor)
rects.outlineRect(image, face.mouthRect, mouthColor)
def drawDebugRects(self, image):
"""Draw rectangles around the tracked facial features."""
if utils.isGray(image):
faceColor = 0
leftEyeColor = 0
rightEyeColor = 0
noseColor = 0
mouthColor = 0
else:
faceColor = (255, 255, 255) # white
leftEyeColor = (0, 0, 255) # red
rightEyeColor = (0, 255, 255) # yellow
noseColor = (0, 255, 0) # green
mouthColor = (255, 0, 0) # blue
for face in self.faces:
rects.outlineRect(image, face.faceRect, faceColor)
rects.outlineRect(image, face.leftEyeRect, leftEyeColor)
rects.outlineRect(image, face.rightEyeRect,
rightEyeColor)
rects.outlineRect(image, face.noseRect, noseColor)
rects.outlineRect(image, face.mouthRect, mouthColor)
def drawDebugRects(self, image):
if utils.isGray(image):
faceColor = 255
leftEyeColor = 255
rightEyeColor = 255
noseColor = 255
mouthColor = 255
else:
faceColor = (255, 255, 255)
leftEyeColor = (0, 0, 255)
rightEyeColor = (0, 255, 255)
noseColor = (0, 255, 0)
mouthColor = (255, 0, 0)
white = (255, 255, 255)
for face in self.faces:
rects.outlineRect(image, face.faceRect, faceColor)
rects.outlineRect(image, face.leftEyeRect, leftEyeColor)
rects.outlineRect(image, face.rightEyeRect, rightEyeColor)
rects.outlineRect(image, face.noseRect, noseColor)
rects.outlineRect(image, face.mouthRect, mouthColor)
k = 5
leftEye = None
rightEye = None
mouth = None
nose = None
if face.leftEyeRect is not None:
leftEye = (face.leftEyeRect[0] + int(face.leftEyeRect[2] / 2),
face.leftEyeRect[1] + int(face.leftEyeRect[3] / 2))
rect = (leftEye[0] - k, leftEye[1] - k, 2 * k, 2 * k)
rects.outlineRect(image, rect, white)
if face.rightEyeRect is not None:
rightEye = (face.rightEyeRect[0] +
int(face.rightEyeRect[2] / 2),
face.rightEyeRect[1] +
int(face.rightEyeRect[3] / 2))
rect = (rightEye[0] - k, rightEye[1] - k, 2 * k, 2 * k)
rects.outlineRect(image, rect, white)
if face.mouthRect is not None:
mouth = (face.mouthRect[0] + int(face.mouthRect[2] / 2),
face.mouthRect[1] + int(face.mouthRect[3] / 2))
rect = (mouth[0] - k, mouth[1] - k, 2 * k, 2 * k)
rects.outlineRect(image, rect, white)
if face.noseRect is not None:
nose = (face.noseRect[0] + int(face.noseRect[2] / 2),
face.noseRect[1] + int(face.noseRect[3] / 2))
rect = (nose[0] - k, nose[1] - k, 2 * k, 2 * k)
rects.outlineRect(image, rect, white)
if leftEye and rightEye and nose and mouth is not None:
cv2.line(image, leftEye, rightEye, white, 1)
cv2.line(image, leftEye, mouth, white, 1)
cv2.line(image, mouth, rightEye, white, 1)
cv2.line(image, nose, rightEye, white, 1)
cv2.line(image, nose, leftEye, white, 1)
cv2.line(image, nose, mouth, white, 1)
# Descritores
distEyes = utils.dist(leftEye, rightEye)
distLeftEyeToNose = utils.dist(leftEye, nose)
distRightEyeToNose = utils.dist(rightEye, nose)
distLeftEyeToMouth = utils.dist(leftEye, mouth)
distRightEyeToMouth = utils.dist(rightEye, mouth)
distNoseToMouth = utils.dist(nose, mouth)
#print(distEyes, distLeftEyeToNose, distRightEyeToNose, distLeftEyeToMouth, distRightEyeToMouth, distNoseToMouth)
print(distEyes/distLeftEyeToNose, distEyes/distRightEyeToNose, distEyes/distLeftEyeToMouth, distEyes/distRightEyeToMouth, \
distLeftEyeToNose/distLeftEyeToMouth, distRightEyeToNose/distRightEyeToMouth)
# Gerando caracterizadores faciais
#print(">> Face: ",face.faceRect)
#print(">> Left eye: ",face.leftEyeRect)
#print(">> Right eye: ",face.rightEyeRect)
#print(">> Nose: ", face.noseRect)
#print(">> Mouth: ",face.mouthRect)
def update(self, image):
"""
:param image:
:return:
"""
self._faces = []
if utils.isGray(image):
image = cv2.equalizeHist(image)
# The algorithm normalizes the brightness and increases the contrast of the image.
# 明るさをノーマライズしコントラストを強める
else:
# グレースケール画像に変換する
image = cv2.cvtColor(image, cv2.cv.CV_BGR2GRAY)
image = cv2.equalizeHist(image)
# まず顔を検出する
# 画像の1/8 * 1/8 = 1/64より小さい顔は認識しない
minSize = utils.widthHeightDividedBy(image, 8) # => (w, h)
faceRects = self._faceClassifier.detectMultiScale(
image, self.scaleFactor, self.minNeighbors, self.flags, minSize)
""":type : list[tuple]"""
# => (x, y, w, h)
#
# void CascadeClassifier::detectMultiScale(
# const Mat& image, vector<Rect>& objects, double scaleFactor=1.1, int minNeighbors=3,
# int flags=0, Size minSize=Size()
# )
# 入力画像中から異なるサイズのオブジェクトを検出します．検出されたオブジェクトは，矩形のリストとして返されます．
#
# パラメタ:
# image – CV_8U 型の行列．ここに格納されている画像中からオブジェクトが検出されます
# objects – 矩形を要素とするベクトル．それぞれの矩形は，検出したオブジェクトを含みます
# scaleFactor – 各画像スケールにおける縮小量を表します
# minNeighbors – オブジェクト候補となる矩形は，最低でもこの数だけの近傍矩形を含む必要があります
# flags – このパラメータは，新しいカスケードでは利用されません．
# 古いカスケードに対しては，cvHaarDetectObjects 関数の場合と同じ意味を持ちます
# minSize – オブジェクトが取り得る最小サイズ．これよりも小さいオブジェクトは無視されます
# 顔を検出できたら・・・
if faceRects is not None:
# 顔ごとに・・・
for faceRect in faceRects:
# faceオブジェクトをつくる
face = Face()
face.faceRect = faceRect
x, y, w, h = faceRect
# 左目を探す
searchRect = (x + w / 7, y, w * 2 / 7, h / 2)
# □■■□□□□
# □■■□□□□
# □□□□□□□
# □□□□□□□
face.leftEyeRect = self._detectOneObject(
self._eyeClassifier, image, searchRect, 64)
# 1/64 * 1/64より小さいオブジェクトを無視する
# if face.leftEyeRect == None:
# print("Left Eye detect failed")
# 右目を探す
searchRect = (x + w * 4 / 7, y, w * 2 / 7, h / 2)
# □□□□■■□
# □□□□■■□
# □□□□□□□
# □□□□□□□
face.rightEyeRect = self._detectOneObject(
self._eyeClassifier, image, searchRect, 64)
# 鼻を探す
searchRect = (x + w / 4, y + h / 4, w / 2, h / 2)
# □□□□□□□
# □□■■■□□
# □□■■■□□
# □□□□□□□
face.noseRect = self._detectOneObject(self._noseClassifier,
image, searchRect, 32)
# 1/32 * 1/32より小さいオブジェクトを無視する
# 口を探す
searchRect = (x + w / 6, y + h * 2 / 3, w * 2 / 3, h / 3)
# □□□□□□□
# □□□□□□□
# □■■■■■□
# □■■■■■□
face.mouthRect = self._detectOneObject(self._mouthClassifier,
image, searchRect, 16)
# 1/16 * 1/16より小さいオブジェクトを無視する
self._faces.append(face)
