class PersonDetector():
def __init__(self, usePiCamera, width, height, camPort):
self.ct = CentroidTracker()
self.targetID = -1000000
self.targetCentroid = []
self.radius = 20
self.cap = VideoStream(usePiCamera, width, height, camPort).start()
self.haar_cascade = cv2.CascadeClassifier("data/HS.xml")
self.frameCount = 0
self.frameCaptureNumber = 7
self.thresholdX = int(width / 2)
self.thresholdY = (int)(height / 2)
self.width = width
self.height = height
def frameAdd(self):
self.frameCount += 1
def checkFrameCount(self):
if self.frameCount % self.frameCaptureNumber == 0:
return True
return False
def robotMoveDirection(self, centroid, center):
print(centroid, " ", center)
cX = center[0]
cY = center[1]
targetX = centroid[0]
targetY = centroid[1]
diffX = cX - targetX
diffY = cY - targetY
hors = "Move: "
verts = " and "
if targetX < cX - self.radius:
hors += "Left " + str(np.abs(diffX)) + " pixels"
elif targetX > cX + self.radius:
hors += "Right " + str(np.abs(diffX)) + " pixels"
else:
hors = ""
verts = "Move: "
if targetY < cY - self.radius:
verts += "Up " + str(np.abs(diffY)) + " pixels"
elif targetY > cY + self.radius:
verts += "Down " + str(np.abs(diffY)) + " pixels"
else:
verts = ""
return hors + verts
def updateObjectIDs(self, upper_body):
return self.ct.update(upper_body)
def detectPerson(self):
capturedframe = self.cap.getFrame()
frame = capturedframe[0:self.height, 0:int(self.width / 2)]
centerX = -10000
centerY = -100000
cColor = (0, 0, 255)
if self.checkFrameCount():
try:
# using a greyscale picture, also for faster detection
gray = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
upper_body = self.haar_cascade.detectMultiScale(
gray,
scaleFactor=1.1,
minNeighbors=12,
# Min size for valid detection, changes according to video size or body size in the video.
minSize=(50, 100),
flags=cv2.CASCADE_SCALE_IMAGE)
if len(upper_body) > 0:
(x, y, w, h) = upper_body[0]
# creates green color rectangle with a thickness size of 1
centerX = (int)(x + w / 2)
centerY = (int)(y + h / 2)
cv2.rectangle(capturedframe, (x, y), (x + w, y + h),
(0, 255, 0), 1)
cv2.line(capturedframe, (centerX, y), (centerX, y + h),
(255, 0, 0), 1)
cv2.line(capturedframe, (x, centerY), (x + w, centerY),
(255, 0, 0), 1)
cv2.circle(capturedframe, (centerX, centerY), 1,
(0, 0, 255), 1)
# creates green color text with text size of 0.5 & thickness size of 2
cv2.putText(capturedframe, "Head and Shoulders Detected",
(x + 5, y + 15), cv2.FONT_HERSHEY_SIMPLEX, 0.5,
(0, 255, 0), 2)
if np.abs(centerX - self.thresholdX) <= 20 and np.abs(
centerY - self.thresholdY) <= 20:
cColor = (0, 255, 0)
else:
cColor = (0, 0, 255)
objects = self.updateObjectIDs(upper_body)
# checking if the id is the same as the one detected
if len(list(objects.items())) > 0:
targetID = list(objects.items())[0][0]
targetCentroid = list(objects.items())[0][1]
if targetCentroid[0] == centerX and targetCentroid[
1] == centerY:
cv2.putText(capturedframe, str(targetID),
(targetCentroid[0], targetCentroid[1]),
cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0),
2)
cv2.circle(capturedframe,
(targetCentroid[0], targetCentroid[1]), 4,
(0, 255, 0), -1)
else:
targetID = -100000
targetCentroid = []
print(
self.robotMoveDirection(targetCentroid,
(self.width / 2, self.height / 2)))
except Exception as e:
print(str(e))
return capturedframe
#threshold center lines
cv2.circle(capturedframe, (self.thresholdX, self.thresholdY),
self.radius, cColor, 3)
return capturedframe
def release(self):
self.cap.release()
ap.add_argument("-s", "--source", type=str, default='-1',
help='indicies of cameras to use')
# parse arguments
args = vars(ap.parse_args())
# create a list of video streams to reference in generate()
vslist = []
# find up to 10 attached cameras and try and start streams on them
if args['source'] == '-1':
print('shotgun approach')
for i in range(0, 9):
vs = VideoStream(i, 'vs{}'.format(i+1), args['resolution'])
if vs.stream.isOpened() is False:
vs.release()
else:
if maxframesize is None:
maxframesize = vs.width
vslist.append(vs)
# open cameras based on arguments passed
else:
sources = parseindicies(args['source'])
print('opening ' + args['source'])
for i in sources:
vs = VideoStream(i, 'vs{}'.format(i+1), args['resolution'])
if vs.stream.isOpened() is False:
vs.release()
else:
if maxframesize is None:
maxframesize = vs.width