fix: use dynamic label names for inference to match training dataset#2403
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Mani-Babapour wants to merge 1 commit intotensorflow:masterfrom
Open
fix: use dynamic label names for inference to match training dataset#2403Mani-Babapour wants to merge 1 commit intotensorflow:masterfrom
Mani-Babapour wants to merge 1 commit intotensorflow:masterfrom
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Previously, the inference section used a hardcoded list of labels: ['no', 'yes', 'down', 'go', 'left', 'up', 'right', 'stop'], which may not match the order of class names in `train_ds.class_names`. This could lead to incorrect labeling in prediction visualizations. This commit replaces the hardcoded labels with `label_names` from the training dataset to ensure the model's outputs are correctly mapped to their respective labels.
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Thanks for the positive feedback!
…On Mon, Dec 8, 2025 at 1:26 PM Dhanush Pillay ***@***.***> wrote:
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Good, nice work
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Previously, the inference section used a hardcoded list of labels:
['no', 'yes', 'down', 'go', 'left', 'up', 'right', 'stop'],
which may not match the order of class names in
train_ds.class_names.This could lead to incorrect labeling in prediction visualizations.
This commit replaces the hardcoded labels with
label_namesfrom the training dataset to ensure the model's outputs are correctly mapped to their respective labels.