ݘh3`ddlZddlZddlZddlZddlmZmZmZmZddl Z ddl m Z ddl mZddlmZmZddlmZmZmZmZmZmZmZmZddlmZed d Zeje Z!Gd d eZGdd eZ"ee"j#e"_#e"j#j$.e"j#j$%ddde"j#_$dSdS)N)AnyOptionalTypeVarUnion)custom_object_save) BatchFeature)is_valid_image load_image)IMAGE_PROCESSOR_NAMEPROCESSOR_NAMEPushToHubMixin copy_func download_urlis_offline_mode is_remote_urllogging) cached_filesImageProcessorTypeImageProcessingMixin)boundceZdZdZdS)r a Holds the output of the image processor specific `__call__` methods. This class is derived from a python dictionary and can be used as a dictionary. Args: data (`dict`): Dictionary of lists/arrays/tensors returned by the __call__ method ('pixel_values', etc.). tensor_type (`Union[None, str, TensorType]`, *optional*): You can give a tensor_type here to convert the lists of integers in PyTorch/TensorFlow/Numpy Tensors at initialization. N)__name__ __module__ __qualname____doc__j/var/www/html/services/rag-service/venv/lib/python3.11/site-packages/transformers/image_processing_base.pyr r 0s    rr czeZdZdZdZdZdefdZe d"de e d e ee j fd ee ee j fd ed ed ee eefdede fdZd#de ee j fdefdZed e ee j fdeeeefeeefffdZedeeeffdZdeeeffdZede ee j ffdZdefdZde ee j ffdZdZed$dZd e eeeeeeffd!ZdS)%rz This is an image processor mixin used to provide saving/loading functionality for sequential and image feature extractors. Nc .|dd|dd|_|D]N\}} t|||#t$r*}t d|d|d||d}~wwxYwdS)z'Set elements of `kwargs` as attributes.feature_extractor_typeNprocessor_classz Can't set z with value z for )pop_processor_classitemssetattrAttributeErrorloggererror)selfkwargskeyvalueerrs r__init__zImageProcessingMixin.__init__Hs  +T222 & + To test a pull request you made on the Hub, you can pass `revision="refs/pr/"`. return_unused_kwargs (`bool`, *optional*, defaults to `False`): If `False`, then this function returns just the final image processor object. If `True`, then this functions returns a `Tuple(image_processor, unused_kwargs)` where *unused_kwargs* is a dictionary consisting of the key/value pairs whose keys are not image processor attributes: i.e., the part of `kwargs` which has not been used to update `image_processor` and is otherwise ignored. subfolder (`str`, *optional*, defaults to `""`): In case the relevant files are located inside a subfolder of the model repo on huggingface.co, you can specify the folder name here. kwargs (`dict[str, Any]`, *optional*): The values in kwargs of any keys which are image processor attributes will be used to override the loaded values. Behavior concerning key/value pairs whose keys are *not* image processor attributes is controlled by the `return_unused_kwargs` keyword parameter. Returns: A image processor of type [`~image_processing_utils.ImageProcessingMixin`]. Examples: ```python # We can't instantiate directly the base class *ImageProcessingMixin* so let's show the examples on a # derived class: *CLIPImageProcessor* image_processor = CLIPImageProcessor.from_pretrained( "openai/clip-vit-base-patch32" ) # Download image_processing_config from huggingface.co and cache. image_processor = CLIPImageProcessor.from_pretrained( "./test/saved_model/" ) # E.g. image processor (or model) was saved using *save_pretrained('./test/saved_model/')* image_processor = CLIPImageProcessor.from_pretrained("./test/saved_model/preprocessor_config.json") image_processor = CLIPImageProcessor.from_pretrained( "openai/clip-vit-base-patch32", do_normalize=False, foo=False ) assert image_processor.do_normalize is False image_processor, unused_kwargs = CLIPImageProcessor.from_pretrained( "openai/clip-vit-base-patch32", do_normalize=False, foo=False, return_unused_kwargs=True ) assert image_processor.do_normalize is False assert unused_kwargs == {"foo": False} ```r6r7r8r:use_auth_tokenNrThe `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.V`token` and `use_auth_token` are both specified. Please set only the argument `token`.r9)r$warningswarn FutureWarning ValueErrorget_image_processor_dict from_dict) r4r5r6r7r8r9r:r,r=image_processor_dicts rfrom_pretrainedz$ImageProcessingMixin.from_pretrained[st({#1 %5!"%z$4d;;  % ME     l#E  #F7O'Cs'CDa'l'lek'l'l$fs}1<r9r?zProvided path (z#) should be a directory, not a fileT)exist_okcommit_messagerepo_id)configzImage processor saved in )rLr9)r$r@rArBgetrCospathisfileAssertionErrormakedirssplitsep _create_repo_get_files_timestamps _auto_classrjoinr to_json_filer)info_upload_modified_files) r+rHrIr,r=rLrMfiles_timestampsoutput_image_processor_files rsave_pretrainedz$ImageProcessingMixin.save_pretraineds $4d;;  % ME   zz'"". l-F7O 7>>. ) ) h !f>!f!f!fgg g NT2222  J#ZZ(8$??NjjN,@,@,M,Mb,QRRG'd'::6::G#99.II    ' t^D A A A A')gll>CW&X&X# 5666 M0KMMNNN    ' ' -jj)) (   ,,,rc |dd}|dd}|dd}|dd}|dd}|dd}|d d} |d d} |d d } |d t} |dd} |dd}|-tjdt|t d|}d|d}| | |d<t r| stdd} t|}tj |}tj |r tj || }tj |r|}d}nt|r|}t!|}n_| } t#||t$g||||| ||| | d }|d}n1#t&$rt($rt'd|d|d| dwxYw t+|d5}|}dddn #1swxYwYt/j|}|d|}n&#t.j$rt'd |d!wxYw|rtd"|n td"|d#|||fS)$a From a `pretrained_model_name_or_path`, resolve to a dictionary of parameters, to be used for instantiating a image processor of type [`~image_processor_utils.ImageProcessingMixin`] using `from_dict`. Parameters: pretrained_model_name_or_path (`str` or `os.PathLike`): The identifier of the pre-trained checkpoint from which we want the dictionary of parameters. subfolder (`str`, *optional*, defaults to `""`): In case the relevant files are located inside a subfolder of the model repo on huggingface.co, you can specify the folder name here. image_processor_filename (`str`, *optional*, defaults to `"config.json"`): The name of the file in the model directory to use for the image processor config. Returns: `tuple[Dict, Dict]`: The dictionary(ies) that will be used to instantiate the image processor object. r6Nr7Fresume_downloadproxiesr9r=r8r: subfolderimage_processor_filename_from_pipeline _from_autor>r?image processor) file_typefrom_auto_classusing_pipelinez+Offline mode: forcing local_files_only=TrueT) filenamesr6r7rdrcr8r9 user_agentr:re%_raise_exceptions_for_missing_entriesrz Can't load image processor for 'z'. If you were trying to load it from 'https://huggingface.co/models', make sure you don't have a local directory with the same name. Otherwise, make sure 'z2' is the correct path to a directory containing a z fileutf-8encodingimage_processorz"It looks like the config file at 'z' is not a valid JSON file.zloading configuration file z from cache at )r$r r@rArBrCrr)r]strrQrRisdirr[rSrrrr OSError ExceptionopenreadjsonloadsrPJSONDecodeError)r4r5r,r6r7rcrdr9r=r8r:rerg from_pipelinerlrois_localimage_processor_fileresolved_image_processor_fileresolved_image_processor_filesreadertextrFs rrDz-ImageProcessingMixin.get_image_processor_dict sB(JJ{D11 $4e<< **%6==**Y-- 7D))$4d;;!::&8%@@::j$//JJ{B// #)::.HJ^#_#_  #3T::  **\599  % ME     l#E#4YY  $+8J' (    $%5 $ KKE F F F# (+,I(J(J%7==!>?? 7==6 7 7 i#%7<<0MOg#h#h 7>>7 8 8$ ,I )HH 8 9 9! #@ ,89V,W,W ) )#;  1=13^D'#1#$3%5)%':? 2 2 2.1Oq0Q--      O7TOO9VOO0HOOO  3gFFF %&{{}} % % % % % % % % % % % % % % %#':d#3#3 #7#;#; > >+1::f+=+=  ( & [4H%H%H06 ;0G0G  -#55 455  ,,.. & &JC,, &e444  %%% " "C JJsD ! ! ! ! 888999  #"F* *" "rcVtj|j}|jj|d<|S)z Serializes this instance to a Python dictionary. Returns: `dict[str, Any]`: Dictionary of all the attributes that make up this image processor instance. image_processor_type)rdeepcopy__dict__ __class__r)r+outputs rto_dictzImageProcessingMixin.to_dicts*t}--)-)@%& r json_filect|d5}|}dddn #1swxYwYtj|}|di|S)a Instantiates a image processor of type [`~image_processing_utils.ImageProcessingMixin`] from the path to a JSON file of parameters. Args: json_file (`str` or `os.PathLike`): Path to the JSON file containing the parameters. Returns: A image processor of type [`~image_processing_utils.ImageProcessingMixin`]: The image_processor object instantiated from that JSON file. rqrrNr)ryrzr{r|)r4rrrrFs rfrom_json_filez#ImageProcessingMixin.from_json_files)g . . . !&;;==D ! ! ! ! ! ! ! ! ! ! ! ! ! ! !#z$//s**)***s 377c.|}|D]6\}}t|tjr|||<7|dd}|||d<tj|dddzS)z Serializes this instance to a JSON string. Returns: `str`: String containing all the attributes that make up this feature_extractor instance in JSON format. r%Nr#T)indent sort_keys ) rr& isinstancenpndarraytolistr$r{dumps)r+ dictionaryr-r.r%s rto_json_stringz#ImageProcessingMixin.to_json_strings\\^^ $**,, 1 1JC%,, 1"',,.. 3&>>*z5ImageProcessingMixin.fetch_images.. s'DDDQD%%a((DDDrz=only a single or a list of entries is supported but got type=)rlistrur r TypeErrortype)r+rs` rrz!ImageProcessingMixin.fetch_imagess ' . . wDDDD2CDDD D )3 / / w/00 0 - . . w$ $u\`ar\s\suuvv vr)NFFNr3)F)r)rrrrrZr0rur2 classmethodrrrrQPathLikerboolrGratupledictrrDrErrrr\rrrrrrrrr@s K   0C00008<$!&,0o=o= $ %o=',S"+-='>o=E#r{"234o= o=  o= c4i() o=o= o=o=o=[o=b;-;-eC4D.E;-TX;-;-;-;-zq,,1#r{2B,Cq, tCH~tCH~- .q,q,q,[q,f*#T#s(^*#*#*#[*#X c3h    +uS"+-='>+++[+$GGGGG* 05bk1A+B 0 0 0 0DDD%%%[%*weCcDcO4S.Twwwwwwrrjrzimage processor file)object object_class object_files)&rr{rQr@typingrrrrnumpyrdynamic_module_utilsrfeature_extraction_utilsr BaseBatchFeature image_utilsr r utilsr r rrrrrr utils.hubrr get_loggerrr)rrIrformatrrrrs  000000000000444444FFFFFF33333333                    $#####W19OPPP  H % %     #    QwQwQwQwQw>QwQwQwh$-9-A-M#N#N #+7/C/O/W/^/^ /CRh0_00$,,,87r