get_statistics

get_statistics.py

           predicted_label_id = str(result[0])
            if config.is_comparison:
                predictions[model_name] = id2label[predicted_label_id]
            print(f"{model_name} Predicted Label: {str(id2label[predicted_label_id])}")
            f1_metric = model_data['metrics']['f1']
            acc_metric = model_data['metrics']['acc']
            f1_metric.add_batch(
                predictions=[int(predicted_label_id)],
                references=[int(actual_label_id)]
            )
            acc_metric.add_batch(
                predictions=[int(predicted_label_id)],
                references=[int(actual_label_id)]
            )

            model_data['stats'] = get_multi_class_stats(
                model_data['stats'],
                predicted_label_id,
                actual_label_id,
                id2label
            )

        print("--------------------------------------------\n")
        if config.is_comparison:
            add_counts_to_comparison(comparison_stats, predictions, ground_truth_label)
    if config.is_comparison:
        calc_most_common_fps(comparison_stats)
        upload_comparison(comparison_stats, config)
    process_statistics(model_containers, config)