def frames():
camera = cv2.VideoCapture(Camera.video_source)
camera.set(3,320)
camera.set(4,240)
width = int(camera.get(3))
height = int(camera.get(4))
M = cv2.getRotationMatrix2D((width / 2, height / 2), 180, 1)
camera.set(cv2.CAP_PROP_BUFFERSIZE,1)
# camera.rotation = 180
# rawCapture = PiRGBArray(camera, size=(320, 240))
# if not camera.isOpened():
# raise RuntimeError('Could not start camera.')
start_time = time.time()
fpscount = 0
# print(cv2.useOptimized())
cv2.setUseOptimized(True)
# print(cv2.useOptimized())
while True:
# read current frame
# img = cv2.warpAffine(img, M, (640, 480))
# print(time.time()- start_time)
_, img = camera.read()
img = cv2.warpAffine(img, M, (320, 240))
img = Vilib.human_detect_func(img)
img = Vilib.color_detect_func(img)
## FPS
# fpscount += 1
# if (time.time()- start_time) >= 1:
# print(fpscount)
# start_time = time.time()
# fpscount = 0
## FPS
# start_time = time.time()
# t1 = cv2.getTickCount()
# img = Vilib.human_detect_func(img)
# t2 = cv2.getTickCount()
# print(int(1/round((t2-t1)/cv2.getTickFrequency(),2)))
# img = cv2.resize(img, (320,240), interpolation=cv2.INTER_LINEAR)
# img = Vilib.color_detect_func(img)
# encode as a jpeg image and return it
yield cv2.imencode('.jpg', img)[1].tobytes()
def frames():
with picamera.PiCamera() as camera:
# let camera warm up
# camera = PiCamera()
camera.resolution = (320, 240)
camera.framerate = 32
camera.rotation = 180
# rawCapture = PiRGBArray(camera, size=(320, 240))
# time.sleep(2)
# stream = io.BytesIO()
rawCapture = PiRGBArray(camera, size=(320, 240))
start_time = time.time()
fpscount = 0
Vilib.cdf_flag = True
Vilib.hdf_flag = True
Vilib.color_change('blue')
print(cv2.useOptimized())
cv2.setUseOptimized(True)
print(cv2.useOptimized())
for _ in camera.capture_continuous(rawCapture,
format="bgr",
use_video_port=True):
# return current frame
# stream.seek(0)
img = _.array
# img = frame.array
t1 = cv2.getTickCount()
img = Vilib.color_detect_func(img)
img = Vilib.human_detect_func(img)
t2 = cv2.getTickCount()
print(round((t2 - t1) / cv2.getTickFrequency(), 3))
# yield stream.read()
yield cv2.imencode('.jpg', img)[1].tobytes()
rawCapture.truncate(0)
# allow the camera to warmup
time.sleep(0.1)
start_time = time.time()
fpscount = 0
# capture frames from the camera
Vilib.cdf_flag = True
Vilib.hdf_flag = True
Vilib.color_change('blue')
print(cv2.useOptimized())
cv2.setUseOptimized(True)
print(cv2.useOptimized())
for frame in camera.capture_continuous(rawCapture,
format="bgr",
use_video_port=True):
# grab the raw NumPy array representing the image, then initialize the timestamp
# and occupied/unoccupied text
img = frame.array
t1 = cv2.getTickCount()
img = Vilib.color_detect_func(img)
img = Vilib.human_detect_func(img)
t2 = cv2.getTickCount()
print(round((t2 - t1) / cv2.getTickFrequency(), 3))
# cv2.imshow("Frame", image)
# key = cv2.waitKey(1) & 0xFF
# clear the stream in preparation for the next frame
rawCapture.truncate(0)
# if the `q` key was pressed, break from the loop
# if key == ord("q"):
# break