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fix: use dynamic label names for inference to match training dataset

Open Mani-Babapour opened this issue 4 weeks ago • 3 comments

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.

Mani-Babapour avatar Nov 30 '25 11:11 Mani-Babapour

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google-cla[bot] avatar Nov 30 '25 11:11 google-cla[bot]

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github-actions[bot] avatar Nov 30 '25 11:11 github-actions[bot]

Thanks for the positive feedback!

On Mon, Dec 8, 2025 at 1:26 PM Dhanush Pillay @.***> wrote:

@.**** commented on this pull request.

Good, nice work

— Reply to this email directly, view it on GitHub https://github.com/tensorflow/docs/pull/2403#pullrequestreview-3551156233, or unsubscribe https://github.com/notifications/unsubscribe-auth/AQZAV6N5IOOUEF4MGE2OWVD4AVDOVAVCNFSM6AAAAACNS2RKACVHI2DSMVQWIX3LMV43YUDVNRWFEZLROVSXG5CSMV3GSZLXHMZTKNJRGE2TMMRTGM . You are receiving this because you authored the thread.Message ID: @.***>

Mani-Babapour avatar Dec 08 '25 15:12 Mani-Babapour