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Initialize the decoder vocabulary for table structure recognition.
Builds a character dictionary mapping HTML table structure tokens (e.g., ``, `
`, `
`, colspan/
rowspan attributes) to integer indices. The dictionary includes special `"sos"` (start-of-sequence) and
`"eos"` (end-of-sequence) tokens. Merged `
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` tokens
when applicable.
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Post-process the raw model outputs to decode the predicted table structure into an HTML token sequence.
Converts the model's predicted probability distributions over the structure vocabulary into a sequence of
HTML tokens representing the table structure. The decoded tokens are wrapped with ``, ``, and
`
` tags to form a complete HTML table structure.
Args:
outputs ([`SLANeXtForTableRecognitionOutput`]):
Raw outputs from the SLANeXt model. The `last_hidden_state` field contains the predicted probability
distributions over the structure vocabulary at each decoding step, with shape
`(batch_size, max_text_length, num_classes)`.
Returns:
`dict`: A dictionary containing:
- **structure** (`list[str]`): The predicted HTML table structure as a list of tokens, wrapped with
``, ``, and `
` tags.
- **structure_score** (`float`): The mean confidence score across all predicted tokens.
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