def run(self):
started = time.time()
while True:
currentframe = cv.QueryFrame(self.capture)
instant = time.time() #Get timestamp o the frame
self.processImage(currentframe) #Process the image
if not self.isRecording:
if self.somethingHasMoved():
self.trigger_time = instant #Update the trigger_time
if instant > started + 10: #Wait 5 second after the webcam start for luminosity adjusting etc..
print "Something is moving !"
if self.doRecord: #set isRecording=True only if we record a video
self.isRecording = True
cv.DrawContours(currentframe, self.currentcontours,
(0, 0, 255), (0, 255, 0), 1, 2, cv.CV_FILLED)
else:
if instant >= self.trigger_time + 10: #Record during 10 seconds
print "Stop recording"
self.isRecording = False
else:
cv.PutText(currentframe,
datetime.now().strftime("%b %d, %H:%M:%S"),
(25, 30), self.font, 0) #Put date on the frame
cv.WriteFrame(self.writer, currentframe) #Write the frame
if self.show:
cv.ShowImage("Image", currentframe)
c = cv.WaitKey(1) % 0x100
if c == 27 or c == 10: #Break if user enters 'Esc'.
break
def run(self):
started = time.time()
while True:
curframe = cv.QueryFrame(self.capture)
instant = time.time() #Get timestamp o the frame
self.processImage(curframe) #Process the image
if not self.isRecording:
if self.somethingHasMoved():
self.trigger_time = instant #Update the trigger_time
if instant > started + 5: #Wait 5 second after the webcam start for luminosity adjusting etc..
print("Something is moving !")
if self.doRecord: #set isRecording=True only if we record a video
self.isRecording = True
else:
if instant >= self.trigger_time + 10: #Record during 10 seconds
print("Stop recording")
self.isRecording = False
else:
cv.PutText(curframe,
datetime.now().strftime("%b %d, %H:%M:%S"),
(25, 30), self.font, 0) #Put date on the frame
cv.WriteFrame(self.writer, curframe) #Write the frame
if self.show:
cv.ShowImage("Image", curframe)
cv.ShowImage("Res", self.res)
cv.Copy(self.frame2gray, self.frame1gray)
c = cv.WaitKey(1)
if c == 27 or c == 1048603: #Break if user enters 'Esc'.
break
def draw_fft(self, frame, fft_data, min_bpm, max_bpm):
w = frame.width
h = int(frame.height * Annotator.FFT_HEIGHT)
x = 0
y = frame.height
max_magnitude = max(d[1][0] for d in fft_data)
def get_position(i):
point_x = int(
w *
(float(fft_data[i][0] - min_bpm) / float(max_bpm - min_bpm)))
point_y = int(y - ((h * fft_data[i][1][0]) / max_magnitude))
return point_x, point_y
line = [get_position(i) for i in range(len(fft_data))]
cv.PolyLine(frame, [line], False, self.get_colour()[0], 3)
# Label the largest bin
max_bin = max(range(len(fft_data)), key=(lambda i: fft_data[i][1][0]))
x, y = get_position(max_bin)
c = self.get_colour()
text = "%0.1f" % fft_data[max_bin][0]
cv.PutText(frame, text, (x, y), self.small_font_outline, c[1])
cv.PutText(frame, text, (x, y), self.small_font, c[0])
# Pulse ring
r = Annotator.SMALL_PULSE_SIZE
phase = int(
((fft_data[max_bin][1][1] % (2 * numpy.pi)) / numpy.pi) * 180)
cv.Ellipse(frame, (int(x - (r * 1.5)), int(y - r)), (int(r), int(r)),
0, 90, 90 - phase, c[1], Annotator.THIN + Annotator.BORDER)
cv.Ellipse(frame, (int(x - (r * 1.5)), int(y - r)), (int(r), int(r)),
0, 90, 90 - phase, c[0], Annotator.THIN)
path = os.path.dirname(os.path.abspath(__file__))
recognizer = cv2.face.createLBPHFaceRecognizer()
recognizer.load(path + r'\trainer\trainer.yml')
cascadePath = path + "\Classifiers\face.xml"
faceCascade = cv2.CascadeClassifier(cascadePath)
cam = cv2.VideoCapture(0)
font = cv2.CV_FONT_HERSHEY_SIMPLEX #Creates a font
while True:
ret, im = cam.read()
gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(gray,
scaleFactor=1.2,
minNeighbors=5,
minSize=(100, 100),
flags=cv2.CASCADE_SCALE_IMAGE)
for (x, y, w, h) in faces:
nbr_predicted, conf = recognizer.predict(gray[y:y + h, x:x + w])
cv2.rectangle(im, (x - 50, y - 50), (x + w + 50, y + h + 50),
(225, 0, 0), 2)
if (nbr_predicted == 7):
nbr_predicted = 'Obama'
elif (nbr_predicted == 2):
nbr_predicted = 'Anirban'
cv2.PutText(im,
str(nbr_predicted) + "--" + str(conf), (x, y + h), font,
1.1, (0, 255, 0)) #Draw the text
cv2.imshow('im', im)
cv2.waitKey(10)
recognizer.read('trainer/trainer.yml')
cascadePath = "Classifiers/face.xml"
faceCascade = cv2.CascadeClassifier(cascadePath)
path = 'dataSet'
cam = cv2.VideoCapture(0)
fontFace = cv2.FONT_HERSHEY_SIMPLEX
fontScale = 1
fontColor = (255, 255, 255)
while True:
ret, im = cam.read()
gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(gray,
scaleFactor=1.2,
minNeighbors=5,
minSize=(100, 100),
flags=cv2.CASCADE_SCALE_IMAGE)
for (x, y, w, h) in faces:
nbr_predicted, conf = recognizer.predict(gray[y:y + h, x:x + w])
cv2.rectangle(im, (x - 50, y - 50), (x + w + 50, y + h + 50),
(225, 0, 0), 2)
if (nbr_predicted == 7):
nbr_predicted = 'Obama'
elif (nbr_predicted == 2):
nbr_predicted = 'Anirban'
cv2.PutText(cv2.fromarray(im),
str(nbr_predicted) + "--" + str(conf), (x, y + h), font,
255) #Draw the text
cv2.imshow('im', im)
cv2.waitKey(10)
recognizer = cv2.face.createLBPHFaceRecognizer()
recognizer.load('recognizer/trainingData.yml')
cascadePath = "/home/tharushi/opencv-3.1.0/data/haarcascades/haarcascade_frontalcatface_default.xml"
faceCascade = cv2.CascadeClassifier(cascadePath)
cam = cv2.VideoCapture(0)
#font = cv2.InitFont(cv2.CV_FONT_HERSHEY_SIMPLEX, 1, 1, 0, 1, 1)
font = cv2.FONT_HERSHEY_SIMPLEX
while True:
ret, img = cam.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(gray, 1.2, 5)
for (x, y, w, h) in faces:
cv2.rectangle(img, (x - 50, y - 50), (x + w + 50, y + h + 50),
(255, 0, 0), 2)
Id, conf = recognizer.predict(gray[y:y + h, x:x + w])
if (conf < 50):
if (Id == 1):
Id = "Tharushi"
else:
Id = "Unknown"
cv2.PutText(cv2.cv.fromarray(img), str(Id), (x, y + h), font, 255)
cv2.imshow('image', img)
if (cv2.waitKey(10) & 0xFF == ord('q')):
break
cam.release()
cv2.destroyAllWindows()
waitKey()
#cv2.putText(frame, text, (int(x), int(y)), cv2.FONT_HERSHEY_SIMPLEX, size, color, thickness)
def run(self):
#initiate font
font = cv.InitFont(cv.CV_FONT_HERSHEY_SIMPLEX, 1, 1, 0, 3, 8)
# instantiate images
hsv_img = cv.CreateImage(cv.GetSize(cv.QueryFrame(self.capture)), 8, 3)
threshold_img1 = cv.CreateImage(cv.GetSize(hsv_img), 8, 1)
threshold_img1a = cv.CreateImage(cv.GetSize(hsv_img), 8, 1)
threshold_img2 = cv.CreateImage(cv.GetSize(hsv_img), 8, 1)
i = 0
writer = cv.CreateVideoWriter('angle_tracking.avi', cv.CV_FOURCC('M', 'J', 'P', 'G'), 30, cv.GetSize(hsv_img), 1)
while True:
# capture the image from the cam
img = cv.QueryFrame(self.capture)
# convert the image to HSV
cv.CvtColor(img, hsv_img, cv.CV_BGR2HSV)
# threshold the image to isolate two colors
cv.InRangeS(hsv_img, (165, 145, 100), (250, 210, 160), threshold_img1) # red
cv.InRangeS(hsv_img, (0, 145, 100), (10, 210, 160), threshold_img1a) # red again
cv.Add(threshold_img1, threshold_img1a, threshold_img1) # this is combining the two limits for red
cv.InRangeS(hsv_img, (105, 180, 40), (120, 260, 100), threshold_img2) # blue
# determine the moments of the two objects
threshold_img1 = cv.GetMat(threshold_img1)
threshold_img2 = cv.GetMat(threshold_img2)
moments1 = cv.Moments(threshold_img1, 0)
moments2 = cv.Moments(threshold_img2, 0)
area1 = cv.GetCentralMoment(moments1, 0, 0)
area2 = cv.GetCentralMoment(moments2, 0, 0)
# initialize x and y
x1, y1, x2, y2 = (1, 2, 3, 4)
coord_list = [x1, y1, x2, y2]
for x in coord_list:
x = 0
# there can be noise in the video so ignore objects with small areas
if (area1 > 200000):
# x and y coordinates of the center of the object is found by dividing the 1,0 and 0,1 moments by the area
x1 = int(cv.GetSpatialMoment(moments1, 1, 0) / area1)
y1 = int(cv.GetSpatialMoment(moments1, 0, 1) / area1)
# draw circle
cv.Circle(img, (x1, y1), 2, (0, 255, 0), 20)
# write x and y position
cv.PutText(img, str(x1) +', '+str(y1), (x1, y1 + 20), font, 255) # Draw the text
if (area2 > 100000):
# x and y coordinates of the center of the object is found by dividing the 1,0 and 0,1 moments by the area
x2 = int(cv.GetSpatialMoment(moments2, 1, 0) / area2)
y2 = int(cv.GetSpatialMoment(moments2, 0, 1) / area2)
# draw circle
cv.Circle(img, (x2, y2), 2, (0, 255, 0), 20)
cv.PutText(img, str(x2) +', '+str(y2), (x2, y2 + 20), font, 255) # Draw the text
cv.Line(img, (x1, y1), (x2, y2), (0, 255, 0), 4, cv.CV_AA)
# draw line and angle
cv.Line(img, (x1, y1), (cv.GetSize(img)[0], y1), (100, 100, 100, 100), 4, cv.CV_AA)
x1 = float(x1)
y1 = float(y1)
x2 = float(x2)
y2 = float(y2)
angle = int(math.atan((y1 - y2) / (x2 - x1)) * 180 / math.pi)
cv.PutText(img, str(angle), (int(x1) + 50, (int(y2) + int(y1)) / 2), font, 255)
# cv.WriteFrame(writer,img)
# display frames to users
cv.ShowImage('Target', img)
cv.ShowImage('Threshold1', threshold_img1)
cv.ShowImage('Threshold2', threshold_img2)
cv.ShowImage('hsv', hsv_img)
# Listen for ESC or ENTER key
c = cv.WaitKey(7) % 0x100
if c == 27 or c == 10:
break
cv.DestroyAllWindows()
while 1:
ret, img = cap.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.5, 5)
#faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
id, conf = rec.predict(gray[y:y + h, x:x + w])
if (id == 2):
id = "Gayatri"
if id == 1:
id = "alok"
if id == 3:
id = "anjali"
if id == 4:
id = "Gaurav"
if id == 5:
id = 'rahul'
if id == 6:
id = "akshay"
cv2.PutText(img, str(id), (x, y + h), font, fontscale, fontcolor)
cv2.imshow('img', img)
if cv2.waitKey(1) == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
def draw_bpm(self, frame, bpm):
x, y, w, h = self.metrics
c = self.get_colour()
cv.PutText(frame, "%0.0f" % bpm, (x, y), self.large_font_outline, c[1])
cv.PutText(frame, "%0.0f" % bpm, (x, y), self.large_font, c[0])