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add(tutorials): exporting yolo world model #803
add(tutorials): exporting yolo world model #803
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This allows us to export yolo world onnx model which can be later used in mobile inference.
@microsoft-github-policy-service agree |
tutorials/yolov8_world_e2e.py
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parser.add_argument( | ||
"--classes", | ||
type=Path, | ||
default="classes.json", | ||
help="JSON file containing list of classes that will be set as yolo world prompt.", | ||
) |
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Where should a user get this file from in order to run the script?
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In yolo world you specify prompts to the model. So, it's just a list of text/classes that you will prompt the model for zero-shot detection. So, it's user specified. The user has to create the list of prompts.
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Ideally a tutorial is self-contained with default inputs that allow running it end-to-end. We want it to make it as simple as possible for the user to see it working.
Is there an example classes.json that could be added that works with the default --test_image
value of data/stormtroopers.jpg?
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I can add something. Should I create a file and commit it or have user pass in a list of values as classes and we can set default example classes for the argument?
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I have provided default values for classes as requested. Please review @skottmckay
/azp run onnxruntime-extensions.CI |
Azure Pipelines could not run because the pipeline triggers exclude this branch/path. |
This allows us to export yolo world onnx model which can be later used in mobile inference.