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https://issues.apache.org/jira/browse/BEAM-9247?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17036209#comment-17036209
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Elias Djurfeldt edited comment on BEAM-9247 at 2/13/20 1:12 PM:
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How about something like this?
[https://github.com/EDjur/beam/commit/cae4f82957017df31a68de36288b74db2616fa78#diff-0cd6945eb0fdc8a93cb9d7fef0859ca0R94]
Have a look at the tests too to see how I envision it working.
This keeps a single PTransform and DoFn, but acceptsÂ
{code:java}
@typehints.with_input_types(
Union[Tuple[Union[text_type, binary_type], vision.types.ImageContext],
Union[text_type, binary_type]]){code}
Defaults the `image_context` to `None` and unpacks the tuple if needed.
Only concern I have is it might be confusing having a PTransform that accepts
either a tuple of (image, ImageContext) or just string of image. But this
reduces code duplication quite a lot.
was (Author: eliasdjur):
How about something like this?
[https://github.com/EDjur/beam/commit/cae4f82957017df31a68de36288b74db2616fa78#diff-0cd6945eb0fdc8a93cb9d7fef0859ca0R94]
This keeps a single PTransform and DoFn, but acceptsÂ
{code:java}
@typehints.with_input_types(
Union[Tuple[Union[text_type, binary_type], vision.types.ImageContext],
Union[text_type, binary_type]]){code}
Defaults the `image_context` to `None` and unpacks the tuple if needed.
Only concern I have is it might be confusing having a PTransform that accepts
either a tuple of (image, ImageContext) or just string of image. But this
reduces code duplication quite a lot.
> [Python] PTransform that integrates Cloud Vision functionality
> --------------------------------------------------------------
>
> Key: BEAM-9247
> URL: https://issues.apache.org/jira/browse/BEAM-9247
> Project: Beam
> Issue Type: Sub-task
> Components: io-py-gcp
> Reporter: Kamil Wasilewski
> Assignee: Elias Djurfeldt
> Priority: Major
>
> The goal is to create a PTransform that integrates Google Cloud Vision API
> functionality [1].
> [1] https://cloud.google.com/vision/docs/
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