Python API predict using custom AutoML model and Google Storage image object

[Peter Retief]

I am trying to write a python script to predict labels using a custom model which we have trained.  The example in the tutorial works fine, using a sample image on my local disk, where:

    # Read the image and assign to payload.

    with open(file_path, "rb") as image_file:

        content = image_file.read()

    payload = {"image": {"image_bytes": content}}

I would like to submit a sample image stored in Google Storage.  This is the sample code I have tried:

    payload = {

      "thumbnailUri": "",

      "inputConfig" : {

          "gcsSource": {

               "inputUris" : {

"gs://photogrammetry/180919/STA0001-20180828-1316-26682-CAM000003.jpg"

                             }

                        }

                    }

                }

I get this error: "ValueError: Protocol message ExamplePayload has no "inputConfig" field."

What am I doing wrong?

Does anyone have a sample Python script which predicts from a Google Storage image?

[Amruth (Cloud Platform Support)]

For Cloud Vision API, ‘inputConfig’, only pdf and tiff are supported [1]. Also, I found some sample examples in Python for Vision API [2], though the examples are not specific to Cloud Storage.

[1] https://cloud.google.com/vision/docs/reference/rpc/google.cloud.vision.v1p2beta1#google.cloud.vision.v1p2beta1.InputConfig.FIELDS-table

[2] https://cloud.google.com/vision/docs/samples

[AutoML Vision Feedback]

Hi,

Thank you for using the product and your feedback.

AutoML Predict API doesn't support GCS input at the moment. 

We will keep this feature request in mind when working on product improvements.

AutoML Team

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