panorama-application-stub.py

import panoramasdk
import numpy as np

class Application(panoramasdk.node):
    def __init__(self, logger):
        super().__init__()
        self.logger = logger
        self.threshold = 0.
        self.MODEL_NODE = 'model_node'
        self.MODEL_INPUT_NAME = 'images'
        self.MODEL_INPUT_SIZE = (640, 640)
        
        try:
            # Get parameter values
            self.logger.info('Getting parameters')
            self.threshold = self.inputs.threshold.get()
        except:
            self.logger.exception('Error during initialization.')
        finally:
            self.logger.info('Initialiation complete.')
            self.logger.info('Threshold: {}'.format(self.threshold))

    def process_streams(self):
        streams = self.inputs.video_in.get()
        for stream in streams:
            self.process_media(stream)
        self.outputs.video_out.put(streams)

    def process_media(self, stream):
        image_data, ratio = self.preprocess(stream.image, self.MODEL_INPUT_SIZE)
        inference_results = self.call(
            { self.MODEL_INPUT_NAME: image_data }, 
            self.MODEL_NODE
        )
        self.postprocess(inference_results, stream, ratio)

    def preprocess(self, img, size):
         return ((np.ones((size[0], size[1], 3), dtype=np.uint8) * 114), 1.0)

    def postprocess(self, inference_results, stream, ratio):
        pass