Adjust Roboflow models to primarily use base64 payloads
#798
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PawelPeczek-Roboflow
requested review from
grzegorz-roboflow,
yeldarby,
probicheaux and
hansent
as code owners
yeldarby
reviewed
Nov 12, 2024
| @@ -375,7 +375,7 @@ def base64_image(self) -> str: | |||
| return self._base64_image | |||
| numpy_image = self.numpy_image | |||
| self._base64_image = base64.b64encode( | |||
| encode_image_to_jpeg_bytes(numpy_image) | |||
| encode_image_to_jpeg_bytes(numpy_image, jpeg_quality=95) | |||
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Probably want to do whatever we do during the export process for training. I think it’s quality 70
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Description
Currently, running Roboflow model blocks against hosted API we take
numpy_imageand serialise it tobase64- usually following the path of decoding input image (which is sent inbase64) just to encode it back.Sometimes it has detrimental effect - valid payloads that are sent to the fromtend API may get decoded into numpy and encoded to JPEG base64 - which explodes the size.
There may be good and bad side-effects of this change:
jpeg_qualityinWorkflowImageDatato match the behaviour of inference HTTP client (which uses opencv default)Type of change
Please delete options that are not relevant.
How has this change been tested, please provide a testcase or example of how you tested the change?
Any specific deployment considerations
For example, documentation changes, usability, usage/costs, secrets, etc.
Docs