def found_face(self):
# global frame_copy
if (not self.camera_is_on()) or (not self.find_face_is_on()):
return False
self.flushCameraBuffer() # this reduces the frame delay
frame = cv.QueryFrame(self.capture)
if frame is None:
self.close_camera()
return False
if not frame:
cv.WaitKey(0)
if not self.frame_copy:
self.frame_copy = cv.CreateImage((frame.width, frame.height),
cv.IPL_DEPTH_8U, frame.nChannels)
if frame.origin == cv.IPL_ORIGIN_TL:
cv.Copy(frame, self.frame_copy)
else:
cv.Flip(frame, self.frame_copy, 0)
if self.showVideo:
result = self.detect_and_draw(self.frame_copy)
else:
result = self.detect_no_draw(self.frame_copy)
cv.WaitKey(10)
return result
def _build_image(self, frame):
if not self._frame:
self._frame = cv2.CreateImage((frame.width, frame.height), cv.IPL_DEPTH_8U, frame.nChannels)
if frame.origin == cv2.IPL_ORIGIN_TL:
cv2.Copy(frame, self._frame)
else:
cv2.Flip(frame, self._frame, 0)
return IplQImage(self._frame)
def detect_and_draw(img, cascade):
t = cv2.GetTickCount() ## start counter
cv2.CvtColor(img, gray, cv2.CV_BGR2GRAY)
cv2.Resize(gray, small_img, cv2.CV_INTER_LINEAR)
#Ages all trackedFaces
for f in trackedFaces:
f.updateLife()
#Remove expired faces
for f in trackedFaces:
if (f.isTooOld()):
trackedFaces.remove(f)
faces = cv2.HaarDetectObjects(small_img, cascade, storage, haar_scale,
min_neighbors, haar_flags, min_size)
drawline = 0
if faces:
#found a face
for ((x, y, w, h), n) in faces:
matchedFace = False
pt1 = (int(x * image_scale), int(y * image_scale))
pt2 = (int((x + w) * image_scale), int((y + h) * image_scale))
pt3 = (int(x * image_scale) + int(
((x + w) * image_scale - x * image_scale) / 3),
int(y * image_scale))
pt4 = (int((x + w) * image_scale) - int(
((x + w) * image_scale - x * image_scale) / 3),
int((y * image_scale) + int((
(y + h) * image_scale) - int(y * image_scale)) / 3))
#check if there are trackedFaces
if (len(trackedFaces) > 0):
#each face being tracked
for f in trackedFaces:
#the face is found (small movement)
if ((abs(f.xpt - pt1[0]) < FACE_MAX_MOVEMENT)
and (abs(f.ypt - pt1[1]) < FACE_MAX_MOVEMENT)):
matchedFace = True
f.updateFace(int(w * image_scale),
int(h * image_scale), pt1[0], pt1[1])
mf = f
break
#if face not found, add a new face
if (matchedFace == False):
f = Face(0, int(w * image_scale), int(h * image_scale),
pt1[0], pt1[1], 0)
trackedFaces.append(f)
mf = f
#No tracked faces: adding one
else:
f = Face(0, int(w * image_scale), int(h * image_scale), pt1[0],
pt1[1], 0)
trackedFaces.append(f)
mf = f
#where to draw face and properties
if (mf.age > 5):
#draw attention line
lnpt1 = (int(mf.xpt * scale), int(mf.ypt * scale - 5) - 5)
if (mf.age > mf.width):
lnpt2 = (int(mf.xpt * scale + mf.width),
int(mf.ypt * scale - 5))
else:
lnpt2 = (int(mf.xpt * scale + mf.age),
int(mf.ypt * scale - 5))
cv2.Rectangle(img, lnpt1, lnpt2, RED, 4, 8,
0) ## drawing bolded attention line
### draw eyes
cv2.Rectangle(img, mf.eyeLeft1, mf.eyeLeft2, MAGENTA, 3, 8, 0)
cv2.Rectangle(img, mf.eyeRight1, mf.eyeRight2, MAGENTA, 3, 8,
0)
#
### draw mouth
cv2.Rectangle(img, mf.mouthTopLeft, mf.mouthBotRight, ORANGE,
3, 8, 0)
#
### draw face
cv2.Rectangle(img, pt1, pt2, getColor(mf), 3, 8, 0)
#cv2.Rectangle( img, pt3, pt4, MAGENTA, 1, 8, 0 ) #forehead
drawline = mf.age
if (CAPTURING): saveAsJPG(img)
if (osName == "nt"): cv2.Flip(img, img, 0)
cv2.ShowImage('Camera', img)
t = cv2.GetTickCount() - t ## counter for FPS
print("%i fps." % (cv2.GetTickFrequency() * 1000000. / t)) ## print FPS
gray = cv2.CreateImage(frame_size, 8, 1)
small_img = cv2.CreateImage(
(int(frame_size[0] / image_scale), int(frame_size[1] / image_scale)),
8, 1)
cascade = cv2.Load(cascade_name)
#
while 1: # do forever
# capture the current image
frame = cv2.QueryFrame(capture)
if frame is None:
# no image captured... end the processing
break
#
### check OS
if (osName == "nt"):
cv2.Flip(frame, frame, 0)
else:
cv2.Flip(frame, None, 1)
#
### detecting faces here
detect_and_draw(frame, cascade)
#
### handle key events
k = cv2.WaitKey(5)
if k % 0x100 == 27:
# user has press the ESC key, so exit
cv2.DestroyWindow('Camera')
break
import numpy as np
import cv2
topmost = i
temp = 2
return (leftmost, rightmost, topmost, bottommost)
capture = cv.VideoCapture(0)
cv.SetCaptureProperty(capture, cv.CV_CAP_PROP_FRAME_WIDTH, 1280)
cv.SetCaptureProperty(capture, cv.CV_CAP_PROP_FRAME_HEIGHT, 720)
frame = cv.QueryFrame(capture)
test = cv.CreateImage(cv.GetSize(frame), 8, 3)
cv.NamedWindow("output")
previous_x = 0
previous_y = 0
while (1):
frame = cv.QueryFrame(capture)
cv.Flip(frame, frame, 1)
# we make all drawings on imdraw.
imdraw = cv.CreateImage(cv.GetSize(frame), 8, 3)
# we get coordinates from imgyellowthresh
imgyellowthresh = getthresholdedimg(frame)
# eroding removes small noises
cv.Erode(imgyellowthresh, imgyellowthresh, None, 1)
(leftmost, rightmost, topmost, bottommost) = getpositions(imgyellowthresh)
if (leftmost - rightmost != 0) or (topmost - bottommost != 0):
lastx = posx
lasty = posy
posx = cv.Round((rightmost + leftmost) / 2)
posy = cv.Round((bottommost + topmost) / 2)
if lastx != 0 and lasty != 0:
win32api.SetCursorPos((posx, posy))
if cap:
frame_copy = None
while (True):
# Capture frame-by-frame
result, frame = capture.read()
#frame = cv.QueryFrame(cap)
if not frame:
cv.waitKey(0)
break
if not frame_copy:
frame_copy = cv.CreateImage((frame.width, frame.height),
cv.IPL_DEPTH_8U, frame.nChannels)
if frame.origin == cv.IPL_ORIGIN_TL:
cv.Flip(frame, frame, -1)
# Our operations on the frame come here
gray = cv.CreateImage((frame.width, frame.height), 8, 1)
small_img = cv.CreateImage((cv.Round(
frame.width / image_scale), cv.Round(frame.height / image_scale)), 8,
1)
# convert color input image to grayscale
cv.CvtColor(frame, gray, cv.CV_BGR2GRAY)
# scale input image for faster processing
cv.Resize(gray, small_img, cv.CV_INTER_LINEAR)
cv.EqualizeHist(small_img, small_img)
ap.add_argument("-f", "--face", required = True, help = "caminho para um classificador de faces")
ap.add_argument("-v", "--video", help = " caminho para um arquivo de vídeo")
args = vars( ap.parse_args() )
fd = FaceDetector( args["face"] )
if ( not args.get("video", False) ):
camera = cv2.VideoCapture( 0 )
else:
camera = cv2.VideoCapture( args["video"] )
while (True):
(grabbed, frame) = camera.read()
if ( args.get("video") and not grabbed ):
break
frame = imutils.resize(frame, width = 300)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray = cv2.Flip(gray, flipMode=-1)
faceRects = fd.detect(gray, scaleFactor = 1.1, minNeighbors = 3, minSize = (30, 30))
frameClone = frame.copy()
for (fX, fY, fW, fH) in faceRects:
cv2.rectangle(frameClone, (fX, fY), (fX + fW, fY + fH), (0, 255, 0), 2)
cv2.imshow("Face", frameClone)
if ( cv2.waitKey(1) & 0xFF == ord("q") ):
break
camera.release()
cv2.destroyAllWindows()