Convert images to text.
(self, documents: pd.DataFrame, embeddings: np.ndarray)
| 3882 | return embeddings |
| 3883 | |
| 3884 | def _images_to_text(self, documents: pd.DataFrame, embeddings: np.ndarray) -> pd.DataFrame: |
| 3885 | """Convert images to text.""" |
| 3886 | logger.info("Images - Converting images to text. This might take a while.") |
| 3887 | if isinstance(self.representation_model, dict): |
| 3888 | for tuner in self.representation_model.values(): |
| 3889 | if getattr(tuner, "image_to_text_model", False): |
| 3890 | documents = tuner.image_to_text(documents, embeddings) |
| 3891 | elif isinstance(self.representation_model, list): |
| 3892 | for tuner in self.representation_model: |
| 3893 | if getattr(tuner, "image_to_text_model", False): |
| 3894 | documents = tuner.image_to_text(documents, embeddings) |
| 3895 | elif isinstance(self.representation_model, BaseRepresentation): |
| 3896 | if getattr(self.representation_model, "image_to_text_model", False): |
| 3897 | documents = self.representation_model.image_to_text(documents, embeddings) |
| 3898 | logger.info("Images - Completed \u2713") |
| 3899 | return documents |
| 3900 | |
| 3901 | def _map_predictions(self, predictions: List[int]) -> List[int]: |
| 3902 | """Map predictions to the correct topics if topics were reduced.""" |
no test coverage detected