fTh&*SSKJrJr SSKJr SSKJrJrJrJ r J r J r SSK J r Jr \ "5(a SSKJr SSKJr \"5(aSS KJr \"5(a SS KrSS KJr \ R0"\5r\"\"S S S 95"SS\ 55rg ))ListUnion)GenerationConfig)add_end_docstringsis_tf_availableis_torch_availableis_vision_availableloggingrequires_backends)Pipelinebuild_pipeline_init_args)Image) load_image)'TF_MODEL_FOR_VISION_2_SEQ_MAPPING_NAMESN)$MODEL_FOR_VISION_2_SEQ_MAPPING_NAMEST) has_tokenizerhas_image_processorc^\rSrSrSrSr\"SS9rU4SjrSSjr SS\ \ \ \ S \ S 44U4S jjjr SS jrS rS rSrU=r$)ImageToTextPipeline.a Image To Text pipeline using a `AutoModelForVision2Seq`. This pipeline predicts a caption for a given image. Unless the model you're using explicitly sets these generation parameters in its configuration files (`generation_config.json`), the following default values will be used: - max_new_tokens: 256 Example: ```python >>> from transformers import pipeline >>> captioner = pipeline(model="ydshieh/vit-gpt2-coco-en") >>> captioner("https://huggingface.co/datasets/Narsil/image_dummy/raw/main/parrots.png") [{'generated_text': 'two birds are standing next to each other '}] ``` Learn more about the basics of using a pipeline in the [pipeline tutorial](../pipeline_tutorial) This image to text pipeline can currently be loaded from pipeline() using the following task identifier: "image-to-text". See the list of available models on [huggingface.co/models](https://huggingface.co/models?pipeline_tag=image-to-text). T)max_new_tokensc>[TU]"U0UD6 [US5 URURS:Xa [ 5 g[ 5 g)Nvisiontf)super__init__r check_model_type frameworkrr)selfargskwargs __class__s \/var/www/auris/envauris/lib/python3.13/site-packages/transformers/pipelines/image_to_text.pyrImageToTextPipeline.__init__PsD $)&)$) 7;~~7M 3 Sw c0n0nUbX6S'UbXFS'UbXS'Ub%UbSU;a [S5eURU5 URbURUS'URbURUS'URUS'Xe04$)Nprompttimeoutrzp`max_new_tokens` is defined both as an argument and inside `generate_kwargs` argument, please use only 1 versionassistant_model tokenizerassistant_tokenizer) ValueErrorupdater,r.r-)r"rgenerate_kwargsr*r+forward_paramspreprocess_paramss r&_sanitize_parameters(ImageToTextPipeline._sanitize_parametersWs  *0h '  +2i (  %/=+ ,  &).>/.Q &  ! !/ 2    +040D0DN, -  # # /*...N; '484L4LN0 1 "44r(inputsz Image.Imagec p>SU;aURS5nUc [S5e[TU] "U40UD6$)a' Assign labels to the image(s) passed as inputs. Args: inputs (`str`, `List[str]`, `PIL.Image` or `List[PIL.Image]`): The pipeline handles three types of images: - A string containing a HTTP(s) link pointing to an image - A string containing a local path to an image - An image loaded in PIL directly The pipeline accepts either a single image or a batch of images. max_new_tokens (`int`, *optional*): The amount of maximum tokens to generate. By default it will use `generate` default. generate_kwargs (`Dict`, *optional*): Pass it to send all of these arguments directly to `generate` allowing full control of this function. timeout (`float`, *optional*, defaults to None): The maximum time in seconds to wait for fetching images from the web. If None, no timeout is set and the call may block forever. Return: A list or a list of list of `dict`: Each result comes as a dictionary with the following key: - **generated_text** (`str`) -- The generated text. imageszBCannot call the image-to-text pipeline without an inputs argument!)popr/r__call__)r"r6r$r%s r&r:ImageToTextPipeline.__call__rsA< v ZZ)F >ab bw1&11r(c[XS9nUGb[RS5 [U[5(d[ S[ U5S35eURRRnUS:XaURXRS9nURS:XaURUR5nURUSS 9RnURR /U-n["R$"U5R'S 5nUR)S U05 GOUS :XaFURXURS 9nURS:XaURUR5nOUS:waoURXRS9nURS:XaURUR5nURX RS9nUR)U5 OS[ SUS35eURXRS9nURS:XaURUR5nURRRS:XaUcSUS 'U$)N)r+uPassing `prompt` to the `image-to-text` pipeline is deprecated and will be removed in version 4.48 of 🤗 Transformers. Use the `image-text-to-text` pipeline insteadz&Received an invalid text input, got - zy - but expected a single string. Note also that one single text can be provided for conditional image to text generation.git)r8return_tensorsptF)textadd_special_tokensr input_ids pix2struct)r8 header_textr>zvision-encoder-decoder)r>z Model type z- does not support conditional text generation)rlogger warning_once isinstancestrr/typemodelconfig model_typeimage_processorr!to torch_dtyper-rB cls_token_idtorchtensor unsqueezer0)r"imager*r+rL model_inputsrB text_inputss r& preprocessImageToTextPipeline.preprocesss252     W fc** >T)#/??43C3C#DL NN5NQ[[ !^^889IE !LL3==a@ ##[)$<=|+#335eieses3t >>T)#/??43C3C#DL77#335Q_Q_3` >>T)#/??43C3C#DL"nnVNNnS ##K0!;zl:g!hii //u^^/\L~~%+t/?/?@ ::   ' '5 0V^(,L %r(c 2SU;a7[US[5(a[SUS55(aSUS'SU;aURUS'UR UR R 5nUR R"U40UDUD6nU$)NrBc3(# UHoSLv M g7fN).0xs r& /ImageToTextPipeline._forward..sA'@!I'@sgeneration_config)rGlistallrar9rJmain_input_namegenerate)r"rUr1r6 model_outputss r&_forwardImageToTextPipeline._forwards < '< 4d;;A|K'@AAA(,L % o 5373I3IO/ 0 !!$**"<"<= ++FVlVoV r(cv/nUH0nSURRUSS90nURU5 M2 U$)Ngenerated_textT)skip_special_tokens)r-decodeappend)r"rfrecords output_idsrecords r& postprocessImageToTextPipeline.postprocesssL'J $.."7"7(,#8#F NN6 "(r(r\)NNNNr[)NN)__name__ __module__ __qualname____firstlineno____doc___pipeline_calls_generater_default_generation_configrr4rrHrr:rWrgrq__static_attributes__ __classcell__)r%s@r&rr.sf4 $!1" 56"2uS$s)]DDW%WX"2"2H1f,  r(r)typingrr generationrutilsrrr r r r baserrPILr image_utilsrmodels.auto.modeling_tf_autorrQmodels.auto.modeling_autor get_loggerrsrErr\r(r&rs )5(VP   H %,4UYZ[z(z\zr(