fix: UnboundLocalError in predict_dummy when no bboxes are detected

[pdoup]

Description

This PR fixes an UnboundLocalError that occurs in the predict_dummy method of tf_predictor.py when the model fails to predict any bounding boxes.

Currently, the variable tf_output is initialized and assigned only within the if len(prediction["bboxes"]) > 0: block. If the model does not populate prediction["bboxes"], this block is skipped, and the subsequent return tf_output, matching_details statement raises a "cannot access local variable" error because tf_output has not been defined.

The fix initializes tf_output as an empty list [] prior to the conditional block, ensuring the variable is always defined and the method returns a valid empty result when no predictions are found.

Changes

• Modified tf_predictor.py: Added initialization of tf_output = [] in predict_dummy to handle cases with no predicted bounding boxes.

Checklist:

• Documentation has been updated, if necessary.
• Examples have been added, if necessary.
• Tests have been added, if necessary.

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[pdoup]

Hi @nikos-livathinos and @cau-git, just wanted to check in on this PR when you have a moment. I’m happy to make any adjustments or provide more context if needed. Thanks for your time!

[nikos-livathinos]

Looks good to me

[pdoup]

added newline at the end to fix black formatter error

[codecov]

Codecov Report

❌ Patch coverage is 0% with 1 line in your changes missing coverage. Please review.

Files with missing lines	Patch %	Lines
...models/tableformer/data_management/tf_predictor.py	0.00%	1 Missing ⚠️

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[pdoup]

Hi @cau-git, just checking in on this PR when you have a moment. Since it's been a couple of months, I'm happy to update the branch or make any changes you need to get this ready for merge.