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https://issues.apache.org/jira/browse/BEAM-9247?focusedWorklogId=392668&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-392668
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ASF GitHub Bot logged work on BEAM-9247:
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Author: ASF GitHub Bot
Created on: 25/Feb/20 16:13
Start Date: 25/Feb/20 16:13
Worklog Time Spent: 10m
Work Description: kamilwu commented on issue #10959: [BEAM-9247]
Integrate GCP Vision API functionality
URL: https://github.com/apache/beam/pull/10959#issuecomment-590947582
Cool, nice to hear that!
One more thing that came to my mind.
Would it be possible to merge `AnnotateImage` and `BatchAnnotateImage`
transforms? I think the user has little interest in configuring
`min_batch_size` and `max_batch_size`, because, at the end, responses are
flatten (output PCollection is of type `AnnotateImageResponse`, not
`List[AnnotateImageResponse]`). Also, I expect that `batch_annotate_images`
with `len(requests) == 1` works the same way as `annotate_images`. But maybe
I'm wrong.
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Issue Time Tracking
-------------------
Worklog Id: (was: 392668)
Time Spent: 3h (was: 2h 50m)
> [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
> Time Spent: 3h
> Remaining Estimate: 0h
>
> 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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