def METHOD_NAME(csv_file, manifest_file, s3_path):
    """
    Read a CSV file and create an Amazon Lookout for Vision classification manifest file.
    :param csv_file: The source CSV file.
    :param manifest_file: The name of the manifest file to create.
    :param s3_path: The Amazon S3 path to the folder that contains the images.
    """
    logger.info("Processing CSV file %s.", csv_file)
    image_count = 0
    anomalous_count = 0
    with open(csv_file, newline='', encoding="UTF-8") as csvfile,\
        open(manifest_file, "w", encoding="UTF-8") as output_file:
        image_classifications = csv.reader(
            csvfile, delimiter=',', quotechar='|')
        # Process each row (image) in the CSV file.
        for row in image_classifications:
            # Skip empty lines.
            if not ''.join(row).strip():
                continue
            source_ref = str(s3_path) + row[0]
            classification = 0
            if row[1].lower() == 'anomaly':
                classification = 1
                anomalous_count += 1
           # Create the JSON line.
            json_line = {}
            json_line['source-ref'] = source_ref
            json_line['anomaly-label'] = str(classification)
            metadata = {}
            metadata['confidence'] = 1
            metadata['job-name'] = "labeling-job/anomaly-classification"
            metadata['class-name'] = row[1]
            metadata['human-annotated'] = "yes"
            metadata['creation-date'] = datetime.now(timezone.utc).strftime('%Y-%m-%dT%H:%M:%S.%f')
            metadata['type'] = "groundtruth/image-classification"
            json_line['anomaly-label-metadata'] = metadata
            output_file.write(json.dumps(json_line))
            output_file.write('\n')
            image_count += 1
    logger.info("Finished creating manifest file %s.\n"
                "Images: %s\nAnomalous: %s",
                manifest_file,
                image_count,
                anomalous_count)
    return image_count, anomalous_count