Crear un archivo de manifiesto de Lookout for Vision usando un SDK de AWS - Ejemplos de código de AWS SDK

Hay más ejemplos de AWS SDK disponibles en el repositorio de GitHub de ejemplos de AWS SDK de documentos.

Crear un archivo de manifiesto de Lookout for Vision usando un SDK de AWS

En el siguiente ejemplo de código, se muestra cómo crear un archivo de manifiesto de Lookout for Vision y cargarlo en Amazon S3.

Para obtener información, consulte .Crear un archivo de manifiesto.

Python
SDK para Python (Boto3)
nota

Hay más en GitHub. Busque el ejemplo completo y aprenda a configurar y ejecutar en el Repositorio de ejemplos de código de AWS.

class Datasets: @staticmethod def create_manifest_file_s3(s3_resource, image_s3_path, manifest_s3_path): """ Creates a manifest file and uploads to Amazon S3. :param s3_resource: A Boto3 Amazon S3 resource. :param image_s3_path: The Amazon S3 path to the images referenced by the manifest file. The images must be in an Amazon S3 bucket with the following folder structure. s3://amzn-s3-demo-bucket/<train or test>/ normal/ anomaly/ Place normal images in the normal folder and anomalous images in the anomaly folder. :param manifest_s3_path: The Amazon S3 location in which to store the created manifest file. """ output_manifest_file = "temp.manifest" try: # Current date and time in manifest file format. dttm = datetime.now().strftime("%Y-%m-%dT%H:%M:%S.%f") # Get bucket and folder from image and manifest file paths. bucket, prefix = image_s3_path.replace("s3://", "").split("/", 1) if prefix[-1] != "/": prefix += "/" manifest_bucket, manifest_prefix = manifest_s3_path.replace( "s3://", "" ).split("/", 1) with open(output_manifest_file, "w") as mfile: logger.info("Creating manifest file") src_bucket = s3_resource.Bucket(bucket) # Create JSON lines for anomalous images. for obj in src_bucket.objects.filter( Prefix=prefix + "anomaly/", Delimiter="/" ): image_path = f"s3://{src_bucket.name}/{obj.key}" manifest = Datasets.create_json_line(image_path, "anomaly", dttm) mfile.write(json.dumps(manifest) + "\n") # Create json lines for normal images. for obj in src_bucket.objects.filter( Prefix=prefix + "normal/", Delimiter="/" ): image_path = f"s3://{src_bucket.name}/{obj.key}" manifest = Datasets.create_json_line(image_path, "normal", dttm) mfile.write(json.dumps(manifest) + "\n") logger.info("Uploading manifest file to %s", manifest_s3_path) s3_resource.Bucket(manifest_bucket).upload_file( output_manifest_file, manifest_prefix ) except ClientError: logger.exception("Error uploading manifest.") raise except Exception: logger.exception("Error uploading manifest.") raise else: logger.info("Completed manifest file creation and upload.") finally: try: os.remove(output_manifest_file) except FileNotFoundError: pass @staticmethod def create_json_line(image, class_name, dttm): """ Creates a single JSON line for an image. :param image: The S3 location for the image. :param class_name: The class of the image (normal or anomaly) :param dttm: The date and time that the JSON is created. """ label = 0 if class_name == "normal": label = 0 elif class_name == "anomaly": label = 1 else: logger.error("Unexpected label value: %s for %s", label, image) raise Exception(f"Unexpected label value: {label} for {image}") manifest = { "source-ref": image, "anomaly-label": label, "anomaly-label-metadata": { "confidence": 1, "job-name": "labeling-job/anomaly-label", "class-name": class_name, "human-annotated": "yes", "creation-date": dttm, "type": "groundtruth/image-classification", }, } return manifest