def __init__(self, inst: NetworkTablesInstance = NetworkTables) -> None:
inst.initialize(server=RIO_IP)
self.inst = inst
nt = inst.getTable("/vision")
self.entry = nt.getEntry("data")
self.ping = nt.getEntry("ping")
self.raspi_pong = nt.getEntry("raspi_pong")
self.rio_pong = nt.getEntry("rio_pong")
self.last_ping_time = 0.0
self.time_to_pong = 0.00000001
self._get_time = time.monotonic
def main():
global tableInstance
pipeline = TapeRecognitionPipeline()
#cs = CameraServer.getInstance()
# Capture from the first USB Camera on the system
#camera = UsbCamera(name="Camera rPi Camera 0",path="/dev/video0")
#server = cs.startAutomaticCapture(camera=camera,return_server=True)
#camera.setConnectionStrategy(VideoSource.ConnectionStrategy.kKeepOpen)
#camera.setResolution(320, 240)
capture = cv2.VideoCapture(0)
capture.set(cv2.CAP_PROP_FRAME_WIDTH, 320)
capture.set(cv2.CAP_PROP_FRAME_HEIGHT, 240)
tableInstance = NetworkTablesInstance()
tableInstance.initialize(server="roboRIO-3319-FRC.local")
print(tableInstance.isConnected())
# Get a CvSink. This will capture images from the camera
#cvSink = cs.getVideo()
#cvSink.setEnabled(True)
# Allocating new images is very expensive, always try to preallocate
img = numpy.zeros(shape=(240, 320, 3), dtype=numpy.uint8)
while True:
# Tell the CvSink to grab a frame from the camera and put it
# in the source image. If there is an error notify the output.
retval, img = capture.read(img)
#
# Insert your image processing logic here!
#
pipeline.process(img)
