tj(dZddlmZddlZddlmZddlmZddl m Z m Z m Z m Z ddlmZmZdd lmZmZmZerd d lmZmZGd d e dZGdde dZeGdde ZdgZdS)z& Image/Text processor class for OWLv2 ) TYPE_CHECKINGN) BatchFeature) ImageInput) ImagesKwargsProcessingKwargsProcessorMixinUnpack)PreTokenizedInput TextInput) TensorTypeauto_docstringis_torch_available)%Owlv2ImageGuidedObjectDetectionOutputOwlv2ObjectDetectionOutputc$eZdZUdZedzed<dS)Owlv2ImagesKwargsaa query_images (`ImageInput`, *optional*): Query images to use for image-guided object detection. When provided, these images serve as visual queries to find similar objects in the main `images`. The query images override any text prompts, and the model performs image-to-image matching instead of text-to-image matching. N query_images)__name__ __module__ __qualname____doc__r__annotations__h/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/transformers/models/owlv2/processing_owlv2.pyrr&s/t######rrF)totalc,eZdZUeed<ddiddidZdS)Owlv2ProcessorKwargs images_kwargspadding max_lengthreturn_tensorsnp) text_kwargs common_kwargsN)rrrrr _defaultsrrrr r 1s@$$$$ |  d IIIrr c eZdZfdZe ddedzdeezeezeezde e de fdZ dd d d e d eeezdzd eeedzfdZ dd dd e de d eeezdzfdZxZS)Owlv2Processorc Lt||dSN)super__init__)selfimage_processor tokenizerkwargs __class__s rr.zOwlv2Processor.__init__?s# )44444rNimagestextr2returnc |jtfd|jji|}|ddd}|dd}|||t di}|t |ts0t |tr1t |dts|j|fi|dg}nt |trt |dtrvg}td |D} |D]W} t| | kr| d g| t| z zz} |j| fi|d} | | Xntd |d krAtjd |Dd} tjd|Dd} nj|dkrUtrGddl}|d|Dd} |d|Dd} nt d| |d<| |d<||j|fi|dj}d|i}||j|fi|d}|j|d<t)||S)a Returns: [`BatchFeature`]: A [`BatchFeature`] 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`. - **query_pixel_values** -- Pixel values of the query images to be fed to a model. Returned when `query_images` is not `None`. tokenizer_init_kwargsr!rNr&r$zXYou have to specify at least one text or query image or image. All three cannot be none.rc34K|]}t|VdSr,)len).0 text_singles r z*Owlv2Processor.__call__..js*%O%O;c+&6&6%O%O%O%O%O%Or zLInput text should be a string, a list of strings or a nested list of stringsr%cg|] }|d S input_idsrr;encodings r z+Owlv2Processor.__call__..ws+\+\+\hH[,A+\+\+\r)axiscg|] }|d Sattention_maskrrBs rrDz+Owlv2Processor.__call__..xs0f0f0fPX:J1K0f0f0frptcg|] }|d Sr@rrBs rrDz+Owlv2Processor.__call__..|s&W&W&Wx '<&W&W&Wr)dimcg|] }|d SrGrrBs rrDz+Owlv2Processor.__call__..}s+a+a+a8H5E,F+a+a+arz/Target return tensor type could not be returnedrArHquery_pixel_values pixel_values)data tensor_type) _merge_kwargsr r1 init_kwargspop ValueError isinstancestrlistmaxr:append TypeErrorr% concatenatertorchcatr0rNr)r/r4r5r2 output_kwargsrr$rO encodingsmax_num_queriesr<rCrArHr\rMimage_featuress r__call__zOwlv2Processor.__call__Bs1$+*   "&."<   %_599.$OO &}56FG ,@,@' !II&W&WY&W&W&W]^I__ !&+a+aW`+a+a+agh!i!i !RSSS )D %3D! "  #!5!5l!e!emTcFd!e!e!r (*<=D  1T1&[[M/D >BBBBr皙?outputsr threshold target_sizes text_labelsc|j|||}|/t|t|krtd|0t ||D]\}fd|dD}||d<n |D]}d|d<|S)a Converts the raw output of [`Owlv2ForObjectDetection`] into final bounding boxes in (top_left_x, top_left_y, bottom_right_x, bottom_right_y) format. Args: outputs ([`Owlv2ObjectDetectionOutput`]): Raw outputs of the model. threshold (`float`, *optional*, defaults to 0.1): Score threshold to keep object detection predictions. target_sizes (`torch.Tensor` or `list[tuple[int, int]]`, *optional*): Tensor of shape `(batch_size, 2)` or list of tuples (`tuple[int, int]`) containing the target size `(height, width)` of each image in the batch. If unset, predictions will not be resized. text_labels (`list[list[str]]`, *optional*): List of lists of text labels for each image in the batch. If unset, "text_labels" in output will be set to `None`. Returns: `list[Dict]`: A list of dictionaries, each dictionary containing the following keys: - "scores": The confidence scores for each predicted box on the image. - "labels": Indexes of the classes predicted by the model on the image. - "boxes": Image bounding boxes in (top_left_x, top_left_y, bottom_right_x, bottom_right_y) format. - "text_labels": The text labels for each predicted bounding box on the image. )rdrerfNzAMake sure that you pass in as many lists of text labels as imagesc g|] }| Srr)r;iimage_text_labelss rrDzIOwlv2Processor.post_process_grounded_object_detection..s%[%[%[q&7&:%[%[%[rlabelsrg)r0post_process_object_detectionr:rTzip) r/rdrerfrgoutput image_outputobject_text_labelsrks @r&post_process_grounded_object_detectionz5Owlv2Processor.post_process_grounded_object_detections<%CCy|D    "s;'7'73v;;'F'F`aa a  "36v{3K3K A A/ /%[%[%[%[LQYDZ%[%[%[".@ ]++ A!' 3 3 .2 ]++ r333333?r nms_thresholdc>|j||||S)a Converts the output of [`Owlv2ForObjectDetection.image_guided_detection`] into the format expected by the COCO api. Args: outputs ([`Owlv2ImageGuidedObjectDetectionOutput`]): Raw outputs of the model. threshold (`float`, *optional*, defaults to 0.0): Minimum confidence threshold to use to filter out predicted boxes. nms_threshold (`float`, *optional*, defaults to 0.3): IoU threshold for non-maximum suppression of overlapping boxes. target_sizes (`torch.Tensor`, *optional*): Tensor of shape (batch_size, 2) where each entry is the (height, width) of the corresponding image in the batch. If set, predicted normalized bounding boxes are rescaled to the target sizes. If left to None, predictions will not be unnormalized. Returns: `list[Dict]`: A list of dictionaries, each dictionary containing the following keys: - "scores": The confidence scores for each predicted box on the image. - "boxes": Image bounding boxes in (top_left_x, top_left_y, bottom_right_x, bottom_right_y) format. - "labels": Set to `None`. )rdrerurf)r0#post_process_image_guided_detection)r/rdrerurfs rrwz2Owlv2Processor.post_process_image_guided_detections/:#GGy \hH   r)NN)rcNN)rsrtN)rrrr.rrr r rWr r rrbfloatr tuplerVrrrw __classcell__)r3s@rr*r*=s55555%)Z^ICICT!IC++d9o=EV@WWIC-. IC  ICICIC^IC^8<.2 ..-..!4;.5 . $s)_t+ ....h"8<   8    !4;.5         rr*)rtypingrnumpyr%image_processing_utilsr image_utilsrprocessing_utilsrrr r tokenization_utils_baser r utilsr rrmodeling_owlv2rrrr r*__all__rrrrs! 222222%%%%%% DCCCCCCCCCCCCCCCCCbaaaaaaaa$$$$$ E$$$$     +5    b b b b b ^b b b J  r