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Update getting starting page with a minimal example & link to flytesnacks #682
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Co-authored-by: Yee Hing Tong <[email protected]>
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parsed_image.set(output_file) | ||
@task | ||
def edge_detection_canny(image_location:str) -> FlyteFile: |
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I would like the image_location to be a Flytefile ?
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i guess we can do that as a follow up
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are we keeping this opencv example?
PTAL @kumare3 |
create_first | ||
examples |
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?
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you asked to change the order?
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git clone [email protected]:lyft/flytesnacks.git myflyteproject | ||
git clone [email protected]:lyft/flytekit-python-template.git myflyteproject | ||
cd myflyteproject | ||
rm -rf .git | ||
git init | ||
cd python |
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cd python | |
cd myflyteproject |
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i'll just remove. we should already be in myflyteproject
* A :py:class:`flytekit.types.file.FlyteFile` is a Flytekit type that represents binary data. It is used to offload data to a storage location like S3. Here we use it to store an image. | ||
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You can call this task ``edge_detection_canny(image_location="https://images.unsplash.com/photo-1512289984044-071903207f5e?ixid=MXwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHw%3D&ixlib=rb-1.2.1&auto=format&fit=crop&w=2250&q=80")`` and iterate locally before adding it to part of a larger overall workflow. |
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better to make this a
.. code-block::
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If you have the flyte sandbox installed on your local machine, the image will be accessible to your Flyte system. If you're running a remote Flyte instance, you'll need to upload this image to a remote registry such as Dockerhub, Amazon ECR, or Google Container Registry, so that it can be used by the Flyte system. | ||
You can call this workflow ``EdgeDetectorWf(image_input=...)`` and iterate locally before moving on to register it with Flyte. |
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same here, reason this is easy copy-pastable
Co-authored-by: Ketan Umare <[email protected]>
Signed-off-by: Yee Hing Tong <[email protected]>
#677