U 9%es+@s`dZddlZddlmZddlZddlmZddlm Z ddl m Z m Z m Z Gdd d eZdS) z( Image/Text processor class for OWL-ViT N)List)ProcessorMixin) BatchEncoding)is_flax_availableis_tf_availableis_torch_availablecs|eZdZdZddgZdZdZdfdd Zdd d Zd dZ ddZ ddZ ddZ ddZ eddZeddZZS)OwlViTProcessora Constructs an OWL-ViT processor which wraps [`OwlViTImageProcessor`] and [`CLIPTokenizer`]/[`CLIPTokenizerFast`] into a single processor that interits both the image processor and tokenizer functionalities. See the [`~OwlViTProcessor.__call__`] and [`~OwlViTProcessor.decode`] for more information. Args: image_processor ([`OwlViTImageProcessor`]): The image processor is a required input. tokenizer ([`CLIPTokenizer`, `CLIPTokenizerFast`]): The tokenizer is a required input. image_processor tokenizerZOwlViTImageProcessor)Z CLIPTokenizerZCLIPTokenizerFastNc sdd}d|kr"tdt|d}|dk r.|n|}|dkrBtd|dkrRtdt||dS)Nfeature_extractorzhThe `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor` instead.z)You need to specify an `image_processor`.z"You need to specify a `tokenizer`.)warningswarn FutureWarningpop ValueErrorsuper__init__)selfr r kwargsr  __class__k/var/www/html/Darija-Ai-API/env/lib/python3.8/site-packages/transformers/models/owlvit/processing_owlvit.pyr-s zOwlViTProcessor.__init__ max_lengthnpcKs|dkr |dkr |dkr td|dk r0t|tsLt|trht|dtsh|j|f||d|g}nt|trt|dtrg}tdd|D}|D]H} t| |kr| dg|t| } |j| f||d|} || qntd|d kr*t j d d|Ddd } t j d d|Ddd } n|d krzt rzddl m } | j dd|Ddd } | j dd|Ddd } n|dkrtrddl}|jdd|Ddd} |jdd|Ddd} nT|dkrtrddl}|jdd|Ddd } |jdd|Ddd } ntdt} | | d<| | d<|dk r`t} |j|fd|i|j}|| d<|dk r|j|fd|i|}|dk r|dk r|j| d<| S|dk r|dk r|j| d<| S|dk s|dk r| Sttf||dSdS)a/ Main method to prepare for the model one or several text(s) and image(s). This method forwards the `text` and `kwargs` arguments to CLIPTokenizerFast's [`~CLIPTokenizerFast.__call__`] if `text` is not `None` to encode: the text. To prepare the image(s), this method forwards the `images` and `kwrags` arguments to CLIPImageProcessor's [`~CLIPImageProcessor.__call__`] if `images` is not `None`. Please refer to the doctsring of the above two methods for more information. Args: text (`str`, `List[str]`, `List[List[str]]`): The sequence or batch of sequences to be encoded. Each sequence can be a string or a list of strings (pretokenized string). If the sequences are provided as list of strings (pretokenized), you must set `is_split_into_words=True` (to lift the ambiguity with a batch of sequences). images (`PIL.Image.Image`, `np.ndarray`, `torch.Tensor`, `List[PIL.Image.Image]`, `List[np.ndarray]`, `List[torch.Tensor]`): The image or batch of images to be prepared. Each image can be a PIL image, NumPy array or PyTorch tensor. In case of a NumPy array/PyTorch tensor, each image should be of shape (C, H, W), where C is a number of channels, H and W are image height and width. query_images (`PIL.Image.Image`, `np.ndarray`, `torch.Tensor`, `List[PIL.Image.Image]`, `List[np.ndarray]`, `List[torch.Tensor]`): The query image to be prepared, one query image is expected per target image to be queried. Each image can be a PIL image, NumPy array or PyTorch tensor. In case of a NumPy array/PyTorch tensor, each image should be of shape (C, H, W), where C is a number of channels, H and W are image height and width. return_tensors (`str` or [`~utils.TensorType`], *optional*): If set, will return tensors of a particular framework. Acceptable values are: - `'tf'`: Return TensorFlow `tf.constant` objects. - `'pt'`: Return PyTorch `torch.Tensor` objects. - `'np'`: Return NumPy `np.ndarray` objects. - `'jax'`: Return JAX `jnp.ndarray` objects. Returns: [`BatchEncoding`]: A [`BatchEncoding`] with the following fields: - **input_ids** -- List of token ids to be fed to a model. Returned when `text` is not `None`. - **attention_mask** -- List of indices specifying which tokens should be attended to by the model (when `return_attention_mask=True` or if *"attention_mask"* is in `self.model_input_names` and if `text` is not `None`). - **pixel_values** -- Pixel values to be fed to a model. Returned when `images` is not `None`. NzXYou have to specify at least one text or query image or image. All three cannot be none.r)paddingreturn_tensorscSsg|] }t|qSr)len).0trrr qsz,OwlViTProcessor.__call__.. zLInput text should be a string, a list of strings or a nested list of stringsrcSsg|] }|dqS input_idsrrencodingrrrr!~s)ZaxiscSsg|] }|dqSattention_maskrr%rrrr!sZjaxcSsg|] }|dqSr#rr%rrrr!scSsg|] }|dqSr'rr%rrrr!sptcSsg|] }|dqSr#rr%rrrr!s)dimcSsg|] }|dqSr'rr%rrrr!stfcSsg|] }|dqSr#rr%rrrr!scSsg|] }|dqSr'rr%rrrr!sz/Target return tensor type could not be returnedr$r(rquery_pixel_values pixel_values)dataZ tensor_type)r isinstancestrrr maxrappend TypeErrorrZ concatenaterZ jax.numpynumpyrtorchcatrZ tensorflowstackrr r-dict)rtextZimagesZ query_imagesrrr encodingsZmax_num_queriesr r&r$r(Zjnpr5r+r,Zimage_featuresrrr__call__?sp% "       zOwlViTProcessor.__call__cOs|jj||S)z This method forwards all its arguments to [`OwlViTImageProcessor.post_process`]. Please refer to the docstring of this method for more information. )r post_processrargsrrrrr<szOwlViTProcessor.post_processcOs|jj||S)z This method forwards all its arguments to [`OwlViTImageProcessor.post_process_object_detection`]. Please refer to the docstring of this method for more information. )r post_process_object_detectionr=rrrr?sz-OwlViTProcessor.post_process_object_detectioncOs|jj||S)z This method forwards all its arguments to [`OwlViTImageProcessor.post_process_one_shot_object_detection`]. Please refer to the docstring of this method for more information. )r #post_process_image_guided_detectionr=rrrr@sz3OwlViTProcessor.post_process_image_guided_detectioncOs|jj||S)z This method forwards all its arguments to CLIPTokenizerFast's [`~PreTrainedTokenizer.batch_decode`]. Please refer to the docstring of this method for more information. )r batch_decoder=rrrrAszOwlViTProcessor.batch_decodecOs|jj||S)z This method forwards all its arguments to CLIPTokenizerFast's [`~PreTrainedTokenizer.decode`]. Please refer to the docstring of this method for more information. )r decoder=rrrrBszOwlViTProcessor.decodecCstdt|jS)Nzg`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.)r rrimage_processor_classrrrrfeature_extractor_classs z'OwlViTProcessor.feature_extractor_classcCstdt|jS)Nz[`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.)r rrr rDrrrr s z!OwlViTProcessor.feature_extractor)NN)NNNrr)__name__ __module__ __qualname____doc__ attributesrCZtokenizer_classrr;r<r?r@rArBpropertyrEr __classcell__rrrrr s  p r )rIr typingrr4rZprocessing_utilsrZtokenization_utils_baserutilsrrrr rrrrs