def process_results()

in sample-apps/custom-model/code/application.py [0:0]

• 8 lines of code
• 7 McCabe index (conditional complexity)

    def process_results(self, batch_set, output_media):
        """Processes output tensors from a computer vision model and annotates a video frame."""
        # Model outputs (classes, probabilities, bounding boxes) are collected in
        # the BatchSet returned by model.get_result
        # Each output is a Batch of arrays, one for each input in the batch
        classes = batch_set.get(0)
        # Each batch only has one image; save results for that image
        classes.get(0, self.class_array)
        for ix, prob in enumerate(self.class_array[0]):
            if prob >= self.threshold:
                logger.info('Detected: class {} ({}%)'.format(ix,int(prob*100)))
                output_media.add_label('Class {} ({}%)'.format(ix,int(prob*100)), 0.02, 0.9)
        # Filter out results beneath confidence threshold
        # prob_person_indices = [i for i in person_indices if self.prob_array[0][i] >= self.threshold]
        return output_media