WpfdZddlZddlZddlZddlZddlZddlZddlZddlZddl Z ddl m Z m Z ddl Z ddlZddlZddlmZddlmZddlmZddlmZ ddlZejjjZejjjZn #e $rZ!e"Zej#jZYdZ![!ndZ![!wwxYwdZ$dd Z%d Z&d Z'e'd Z(Gdde)Z*Gdde*Z+Gdde)Z,de-de.fdZ/ d de e e.e.fde.fdZ0dZ1dZ2dZ3dZ4dZ5dS)!zTensorFlow Lite metadata tools.N)DictOptional)_pywrap_metadata_version)metadata_schema_py_generated)schema_py_generated)_pywrap_flatbuffersc\t|dr|Sd|vr|n|dz}t||S)z4Maybe open the binary file, and returns a file-like.readb)hasattr _open_file)filenamemodeopenmodes h/var/www/html/nettyfy-visnx/env/lib/python3.11/site-packages/mediapipe/tasks/python/metadata/metadata.py_maybe_open_as_binaryr2s> Xv OD[[TTdSj( Hh ' ''rcLt||}tj||S)zOpen file as a zipfile. Args: filename: str or file-like or path-like, to the zipfile. mode: str, common file mode for zip. (See: https://docs.python.org/3/library/zipfile.html) Returns: A ZipFile object. )rzipfileZipFile)rr file_likes r_open_as_zipfiler:s%$Hd33) D ) ))rc~t|d5}tj|cdddS#1swxYwYdS)zChecks whether it is a zipfile.rN)rr is_zipfile)rfs r _is_zipfilerIsXs++!q  a !!!!!!!!!!!!!!!!!!s 266ctjtjt jd}tj||S)aGets the path to the specified file in the data dependencies. The path is relative to the file calling the function. It's a simple replacement of "tensorflow.python.platform.resource_loader.get_path_to_datafile". Args: path: a string resource path relative to the calling file. Returns: The path to the specified file present in the data attribute of py_test or py_binary. )ospathdirnameinspectgetfilesys _getframejoin)r!data_files_paths rget_path_to_datafiler)OsAGOOGOCM!4D4D$E$EFF/ ot , ,,rz"../../metadata/metadata_schema.fbsceZdZdZdZdZdZdZedZ edZ dZ d Z d Z d Zd Zd ZdZdZdZdZdZdZdZdZdZdZdZdZdS)MetadataPopulatora3 Packs metadata and associated files into TensorFlow Lite model file. MetadataPopulator can be used to populate metadata and model associated files into a model file or a model buffer (in bytearray). It can also help to inspect list of files that have been packed into the model or are supposed to be packed into the model. The metadata file (or buffer) should be generated based on the metadata schema: mediapipe/tasks/metadata/metadata_schema.fbs Example usage: Populate metadata and label file into an image classifier model. First, based on metadata_schema.fbs, generate the metadata for this image classifier model using Flatbuffers API. Attach the label file onto the output tensor (the tensor of probabilities) in the metadata. Then, pack the metadata and label file into the model as follows. ```python # Populating a metadata file (or a metadata buffer) and associated files to a model file: populator = MetadataPopulator.with_model_file(model_file) # For metadata buffer (bytearray read from the metadata file), use: # populator.load_metadata_buffer(metadata_buf) populator.load_metadata_file(metadata_file) populator.load_associated_files([label.txt]) # For associated file buffer (bytearray read from the file), use: # populator.load_associated_file_buffers({"label.txt": b"file content"}) populator.populate() # Populating a metadata file (or a metadata buffer) and associated files to a model buffer: populator = MetadataPopulator.with_model_buffer(model_buf) populator.load_metadata_file(metadata_file) populator.load_associated_files([label.txt]) populator.populate() # Writing the updated model buffer into a file. updated_model_buf = populator.get_model_buffer() with open("updated_model.tflite", "wb") as f: f.write(updated_model_buf) # Transferring metadata and associated files from another TFLite model: populator = MetadataPopulator.with_model_buffer(model_buf) populator_dst.load_metadata_and_associated_files(src_model_buf) populator_dst.populate() updated_model_buf = populator.get_model_buffer() with open("updated_model.tflite", "wb") as f: f.write(updated_model_buf) ``` Note that existing metadata buffer (if applied) will be overridden by the new metadata buffer. TFLITE_METADATAsTFL3sM001cNt|||_d|_i|_dS)zConstructor for MetadataPopulator. Args: model_file: valid path to a TensorFlow Lite model file. Raises: IOError: File not found. ValueError: the model does not have the expected flatbuffer identifier. N)_assert_model_file_identifier _model_file _metadata_buf_associated_files)self model_files r__init__zMetadataPopulator.__init__s0"*---!DDDrc||S)a=Creates a MetadataPopulator object that populates data to a model file. Args: model_file: valid path to a TensorFlow Lite model file. Returns: MetadataPopulator object. Raises: IOError: File not found. ValueError: the model does not have the expected flatbuffer identifier. )clsr3s rwith_model_filez!MetadataPopulator.with_model_files 3z??rc t|S)a>Creates a MetadataPopulator object that populates data to a model buffer. Args: model_buf: TensorFlow Lite model buffer in bytearray. Returns: A MetadataPopulator(_MetadataPopulatorWithBuffer) object. Raises: ValueError: the model does not have the expected flatbuffer identifier. )_MetadataPopulatorWithBuffer)r7 model_bufs rwith_model_bufferz#MetadataPopulator.with_model_buffers ( 2 22rct|jd5}|cdddS#1swxYwYdS)z}Gets the buffer of the model with packed metadata and associated files. Returns: Model buffer (in bytearray). rbN)r r/r )r2rs rget_model_bufferz"MetadataPopulator.get_model_buffers D$d + +q VVXXs 7;;ct|jsgSt|jd5}|cdddS#1swxYwYdS)zsGets a list of associated files packed to the model file. Returns: List of packed associated files. rN)rr/rnamelist)r2zfs rget_packed_associated_file_listz1MetadataPopulator.get_packed_associated_file_lists t' ( ( i $*C 0 0B [[]]sA  AAc|jsgStjtj|jd}d||DS)zGets a list of associated files recorded in metadata of the model file. Associated files may be attached to a model, a subgraph, or an input/output tensor. Returns: List of recorded associated files. rcBg|]}|jdS)utf-8)namedecode).0files r zGMetadataPopulator.get_recorded_associated_file_list..s8     !!   r)r0 _metadata_fbModelMetadataT InitFromObj ModelMetadataGetRootAsModelMetadata)_get_recorded_associated_file_object_list)r2metadatas r!get_recorded_associated_file_listz3MetadataPopulator.get_recorded_associated_file_listsy   i*66"99   # #$$H  BB8LL   rcr|jd|DdS)a6Loads the associated file buffers (in bytearray) to be populated. Args: associated_files: a dictionary of associated file names and corresponding file buffers, such as {"file.txt": b"file content"}. If pass in file paths for the file name, only the basename will be populated. cTi|]%\}}tj||&Sr6)r r!basename)rIrGbufferss r zBMetadataPopulator.load_associated_file_buffers.. s>### D' ###rN)r1updateitems)r2associated_filess rload_associated_file_buffersz.MetadataPopulator.load_associated_file_bufferssQ !!##-3355###rc|D]b}t|t|d5}|||idddn #1swxYwYcdS)zLoads associated files that to be concatenated after the model file. Args: associated_files: list of file paths. Raises: IOError: File not found. r>N)_assert_file_existr r\r )r2r[af_nameafs rload_associated_filesz'MetadataPopulator.load_associated_filess$@@!!! gt $ $@ ))7BGGII*>???@@@@@@@@@@@@@@@@@s*AA !A c|std||tjt |}t jt j |d}||_ | |tj d}||||j|}||_dS)aLoads the metadata buffer (in bytearray) to be populated. Args: metadata_buf: metadata buffer (in bytearray) to be populated. Raises: ValueError: The metadata to be populated is empty. ValueError: The metadata does not have the expected flatbuffer identifier. ValueError: Cannot get minimum metadata parser version. ValueError: The number of SubgraphMetadata is not 1. ValueError: The number of input/output tensors does not match the number of input/output tensor metadata. z&The metadata to be populated is empty.rN) ValueError_validate_metadatarGetMinimumMetadataParserVersionbytesrLrMrNrOrPminParserVersion._use_basename_for_associated_files_in_metadata flatbuffersBuilderFinishPackMETADATA_FILE_IDENTIFIEROutputr0)r2 metadata_buf min_versionrRr metadata_buf_with_versions rload_metadata_bufferz&MetadataPopulator.load_metadata_buffer!s A ? @ @@L)))+J lK*66"99,JJLLH +H 77AAAAAHHX]]1  t<=== ! 2Drct|t|d5}|}dddn #1swxYwY|t |dS)aLoads the metadata file to be populated. Args: metadata_file: path to the metadata file to be populated. Raises: IOError: File not found. ValueError: The metadata to be populated is empty. ValueError: The metadata does not have the expected flatbuffer identifier. ValueError: Cannot get minimum metadata parser version. ValueError: The number of SubgraphMetadata is not 1. ValueError: The number of input/output tensors does not match the number of input/output tensor metadata. r>N)r^r r rr bytearray)r2 metadata_filerros rload_metadata_filez$MetadataPopulator.load_metadata_fileGs}%%% M4 ( (AVVXXli 5566666sAAActt|}|r||ttj|rot tj|5|fdDddddS#1swxYwYdSdS)zLoads the metadata and associated files from another model buffer. Args: src_model_buf: source model buffer (in bytearray) with metadata and associated files. c<i|]}||Sr6)r )rIrrBs rrXzHMetadataPopulator.load_metadata_and_associated_files..ks% 2 2 2qQ 2 2 2rN)get_metadata_bufferrrrioBytesIOrr\rA)r2 src_model_bufmetadata_bufferrBs @r"load_metadata_and_associated_filesz4MetadataPopulator.load_metadata_and_associated_files[s*-88O1 0002:m,,--4 BJ}55 6 64" )) 2 2 2 2BKKMM 2 2 2 4 4 444444444444444444444s*4B++B/2B/c~|||dS)zCPopulates loaded metadata and associated files into the model file.N)_assert_validate_populate_metadata_buffer_populate_associated_filesr2s rpopulatezMetadataPopulator.populatems>""$$$##%%%%%rc|}|}|j}|D],}||vr&||vr"t d|-|D]S}||vr"t d|||vr't jd|TdS)zValidates the metadata and associated files to be populated. Raises: ValueError: File is recorded in the metadata, but is not going to be populated. File has already been packed. zUFile, '{0}', is recorded in the metadata, but has not been loaded into the populator.z%File, '{0}', has already been packed.z]File, '{0}', does not exist in the metadata. But packing it to tflite model is still allowed.N)rSrCr1keysrcformatwarningswarn)r2recorded_files packed_filesto_be_populated_filesrfrs rrz"MetadataPopulator._assert_validatess;;==N7799L!27799KK ( ( (R|-C-C??EvbzzKK K#88 l  @GGJJKKK .   --3VAYY 8 8 8 88rc t|s"td|t|d5}t|d5}|}|D]T}||vr#td||||}|||U dddn #1swxYwYddddS#1swxYwYdS)z:Copy archieved files in file_list from src_zip ro dst_zip.zFile, '{0}', is not a zipfile.raz0File, '{0}', does not exist in the zipfile, {1}.N)rrcrrrAr writestr) r2src_zip file_listdst_zipsrc_zfdst_zfsrc_listr file_buffers r_copy_archived_filesz&MetadataPopulator._copy_archived_filess w  I 7>>wGG H HH '3 ' ' (6 '3 ' ' (+1""h((! H  @GGW kk!nn ;'''' ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( ( (s7C$A,C  C$ C C$C C$$C(+C(cf|gSg}t||}|pgD]}|j}t|tjtjfr|||dz }It|tjr2|||dz }|||dz }|S)a9Gets the files that are attached the process units field of a table. Args: table: a Flatbuffers table object that contains fields of an array of ProcessUnit, such as TensorMetadata and SubGraphMetadata. field_name: the name of the field in the table that represents an array of ProcessUnit. If the table is TensorMetadata, field_name can be "ProcessUnits". If the table is SubGraphMetadata, field_name can be either "InputProcessUnits" or "OutputProcessUnits". Returns: A list of AssociatedFileT objects. N vocabFilesentencePieceModel)getattroptions isinstancerLBertTokenizerOptionsTRegexTokenizerOptionsT _get_associated_files_from_tableSentencePieceTokenizerOptionsT)r2table field_namer process_units process_unitrs r(_get_associated_files_from_process_unitsz:MetadataPopulator._get_associated_files_from_process_unitss } iIE:..M&+QQ $g Gl@*AC D DQT::7KPPP g|J K KQT:: )++ + T::7KPPP rc.|gSt||pgS)aGets the associated files that are attached a table directly. Args: table: a Flatbuffers table object that contains fields of an array of AssociatedFile, such as TensorMetadata and BertTokenizerOptions. field_name: the name of the field in the table that represents an array of ProcessUnit. If the table is TensorMetadata, field_name can be "AssociatedFiles". If the table is BertTokenizerOptions, field_name can be "VocabFile". Returns: A list of AssociatedFileT objects. )r)r2rrs rrz2MetadataPopulator._get_associated_files_from_tables% } i 5* % % ++rcg}|||dz }|jpgD]}|||dz }|jpgD]4}|||dz }|||dz }5|jpgD]4}|||dz }|||dz }5|||dz }|||dz }|S)aGets a list of AssociatedFileT objects recorded in the metadata. Associated files may be attached to a model, a subgraph, or an input/output tensor. Args: metadata: the ModelMetadataT object. Returns: List of recorded AssociatedFileT objects. associatedFiles processUnitsinputProcessUnitsoutputProcessUnits)rsubgraphMetadatainputTensorMetadataroutputTensorMetadata)r2rRrsubgraphtensor_metadatas rrQz;MetadataPopulator._get_recorded_associated_file_object_listsvNd;;#%%%N-3**== %'''n&9?R--/$?? .00 0$GG ^-- -&:@b--/$?? .00 0$GG ^-- -EE ')))nEE (***nn rcLtj5}t|jd5}t j||dddn #1swxYwYt |d5}|jD]\}}| || dddn #1swxYwY| dt|jd5}t j||dddn #1swxYwYddddS#1swxYwYdS)zConcatenates associated files after TensorFlow Lite model file. If the MetadataPopulator object is created using the method, with_model_file(model_file), the model file will be updated. r>Nrrwb) tempfileSpooledTemporaryFiler r/shutil copyfileobjrr1rZrseek)r2temprrB file_namers rrz,MetadataPopulator._populate_associated_files s  & ( ( $D d& - -$1d###$$$$$$$$$$$$$$$ D# & &."&*&<&B&B&D&D . . "I{ ++i - - - - ................  iilll d& - -$4###$$$$$$$$$$$$$$$ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $ $s|DA  D A DA D'6B* D*B. .D1B. 2-DD5 DD DD DD Dct|jd5}|}dddn #1swxYwYtjtj|d}tj}|j |_ d}|j sg|_ n>|j D]6}|j d|jkrd}||j|j<7|s}|jsg|_|j|tj}|j|_ t'|jdz |_|j |t)jd}||||j|}|} | rt7j5} | |||j| | | dt|jd5}tAj!| |dddn #1swxYwYddddS#1swxYwYdSt|jd5}||ddddS#1swxYwYdS) aiPopulates the metadata buffer (in bytearray) into the model file. Inserts metadata_buf into the metadata field of schema.Model. If the MetadataPopulator object is created using the method, with_model_file(model_file), the model file will be updated. Existing metadata buffer (if applied) will be overridden by the new metadata buffer. r>NrFrFTrr)"r r/r _schema_fbModelTrNModelGetRootAsModelBufferTr0datarRrGrHMETADATA_FIELD_NAMErWbufferappend MetadataTlenrirjrkrlTFLITE_FILE_IDENTIFIERrnrCrrwriterrrr) r2rr;model buffer_field is_populatedmetametadata_fieldr rrs rrz+MetadataPopulator._populate_metadata_buffer%s D$d + +q&&((i   ) )'' 155 7 7E%''L*LL >4enn.44$ 9  G $ $(@ @ @,'3%- $ , ]  m<(((!+--n 4n!%-0014n nN+++ AAHHUZZ]]D7888 I7799L   ( * *&d 9 !!$"2L$GGG ! ($ / / &1  T1 % % % & & & & & & & & & & & & & & & &&&&&&&&&&&&&&&&&& d& - -  sU7;;+AJI) J)I- -J0I- 1JJJ#KK  K c||D]+}tj|j|_,dS)z8Removes any associated file local directory (if exists).N)rQr r!rVrG)r2rRrJs rrhz@MetadataPopulator._use_basename_for_associated_files_in_metadataasD>>xHH..'""49--dii..rct|tj|d}|dkr4t d|t|jd5}| }dddn #1swxYwYtj |d}| d}|d}||kr#t d||| d}|d} || kr#t d|| dS)z'Validates the metadata to be populated.rrzBThe number of SubgraphMetadata should be exactly one, but got {0}.r>NzXThe number of input tensors ({0}) should match the number of input tensor metadata ({1})zZThe number of output tensors ({0}) should match the number of output tensor metadata ({1}))"_assert_metadata_buffer_identifierrLrOrPSubgraphMetadataLengthrcrr r/r rrr Subgraphs InputsLengthSubgraphMetadataInputTensorMetadataLength OutputsLengthOutputTensorMetadataLength) r2ro model_metarr;rnum_input_tensorsnum_input_metanum_output_tensorsnum_output_metas rrdz$MetadataPopulator._validate_metadatafs&|444+BBaJ((**a// &&,f%<<>>'@'@ A AA D$d + +q&&((i   + +Iq 9 9E**77990033MMOONN**  ((./@/=)?)? @ @@++99;; 11   % % ' '_,,  ))/0B0?*A*A B BB-,sB22B69B6N)__name__ __module__ __qualname____doc__rrrmr4 classmethodr8r<r?rCrSr\rarrrvr~rrrrrrQrrrhrdr6rrr+r+gs66z*"$     ; " 3 3; 3   *    @ @ @$3$3$3L777(444$&&& 888@((("B,,,,---^$$$6:::x... B B B B Brr+c(eZdZdZfdZdZxZS)r:aSubclass of MetadataPopulator that populates metadata to a model buffer. This class is used to populate metadata into a in-memory model buffer. As we use Zip API to concatenate associated files after tflite model file, the populating operation is developed based on a model file. For in-memory model buffer, we create a tempfile to serve the populating operation. This class is then used to generate this tempfile, and delete the file when the MetadataPopulator object is deleted. cJ|stdtj5}|j}dddn #1swxYwYt |d5}||dddn #1swxYwYt |dS)zConstructor for _MetadataPopulatorWithBuffer. Args: model_buf: TensorFlow Lite model buffer in bytearray. Raises: ValueError: model_buf is empty. ValueError: model_buf does not have the expected flatbuffer identifier. zmodel_buf cannot be empty.Nr)rcrNamedTemporaryFilerGr rsuperr4)r2r;rr3r __class__s rr4z%_MetadataPopulatorWithBuffer.__init__s 5 3 4 44  $ & &$9j J % %ggi GGZ     s:>>A77A;>A;ctj|jrtj|jdSdS)zKDestructor of _MetadataPopulatorWithBuffer. Deletes the tempfile. N)r r!existsr/removers r__del__z$_MetadataPopulatorWithBuffer.__del__s@  w~~d&''"i !!!!!""r)rrrrr4r __classcell__)rs@rr:r:sQ!!!!!*"""""""rr:creZdZdZdZedZedZdZdZ dZ dZ ed Z d S) MetadataDisplayerzDDisplays metadata and associated file info in human-readable format.clt|t|||_||_||_dS)zConstructor for MetadataDisplayer. Args: model_buffer: valid buffer of the model file. metadata_buffer: valid buffer of the metadata file. associated_file_list: list of associate files in the model file. N)_assert_model_buffer_identifierr _model_buffer_metadata_buffer_associated_file_list)r2 model_bufferr}associated_file_lists rr4zMetadataDisplayer.__init__s>$L111&777%D+D!5Drct|t|d5}||cdddS#1swxYwYdS)aCreates a MetadataDisplayer object for the model file. Args: model_file: valid path to a TensorFlow Lite model file. Returns: MetadataDisplayer object. Raises: IOError: File not found. ValueError: The model does not have metadata. r>N)r^r r<r )r7r3rs rr8z!MetadataDisplayer.with_model_filesz""" J % %-  " "16688 , ,------------------s'AAAc|stdt|}|std||}||||S)zCreates a MetadataDisplayer object for a file buffer. Args: model_buffer: TensorFlow Lite model buffer in bytearray. Returns: MetadataDisplayer object. zmodel_buffer cannot be empty.z!The model does not have metadata.)rcry"_parse_packed_associated_file_list)r7rr}rs rr<z#MetadataDisplayer.with_model_buffersh 8 6 7 77),77O < : ; ;;AA,OO 3|_.B C CCrc||jvr"td|tt j|j5}||cdddS#1swxYwYdS)zGet the specified associated file content in bytearray. Args: filename: name of the file to be extracted. Returns: The file content in bytearray. Raises: ValueError: if the file does not exist in the model. z*The file, {}, does not exist in the model.N)rrcrrrzr{rr )r2rrBs rget_associated_file_bufferz,MetadataDisplayer.get_associated_file_bufferst111  6 = =h G G I II "*T%788 9 9R WWX  sA44A8;A8c4tj|jS)z8Get the metadata buffer in bytearray out from the model.)copydeepcopyrrs rryz%MetadataDisplayer.get_metadata_buffers =. / //rc*t|jS)z)Converts the metadata into a json string.)convert_to_jsonrrs rget_metadata_jsonz#MetadataDisplayer.get_metadata_jsons 40 1 11rc4tj|jS)zzReturns a list of associated files that are packed in the model. Returns: A name list of associated files. )rrrrs rrCz1MetadataDisplayer.get_packed_associated_file_lists =3 4 44rc ttj|5}|cdddS#1swxYwYdS#tj$rgcYSwxYw)zGets a list of associated files packed to the model file. Args: model_buf: valid file buffer. Returns: List of packed associated files. N)rrzr{rAr BadZipFile)r7r;rBs rrz4MetadataDisplayer._parse_packed_associated_file_list s BJy11 2 2b{{}}   iiis3!AA AAA A AA%$A%N) rrrrr4rr8r<rryrrCrr6rrrrsLL 6 6 6--;-"DD;D"&000222555;rrr}rGctj|}|d}||rdSt |D]l}||}| d|kr*|| fcSmdS)a#Gets the custom metadata in metadata_buffer based on the name. Args: metadata_buffer: valid metadata buffer in bytes. name: custom metadata name. Returns: Index of custom metadata, custom metadata flatbuffer. Returns (None, None) if the custom metadata is not found. rN)NNrF) rLrO GetRootAsrCustomMetadataIsNonerangeCustomMetadataLengthCustomMetadataNamerH DataAsNumpytobytes)r}rGmodel_metadataricustom_metadatas r_get_custom_metadatars -77HH.  , ,Q / /( 6688 : ..00 1 188a--a00O$$W--55 ++--5577 77776 rcustom_metadata_schemareturnctj}d|_tj|}t t 5}|}dddn #1swxYwY||std|j ztj ||}|s|Stj |}| D]\}} t||\} } | stjd|0t#| t | d5}|} dddn #1swxYwY|| std|j ztj || } |ddd | }||d <tj | |d <tj|d S)aConverts the metadata into a json string. Args: metadata_buffer: valid metadata buffer in bytes. custom_metadata_schema: A dict of custom metadata schema, in which key is custom metadata name [1], value is the filepath that defines custom metadata schema. For instance, custom_metadata_schema = {"SEGMENTER_METADATA": "metadata/vision_tasks_metadata_schema.fbs"}. [1]: https://github.com/google/mediapipe/blob/46b5c4012d2ef76c9d92bb0d88a6b107aee83814/mediapipe/tasks/metadata/metadata_schema.fbs#L612 Returns: Metadata in JSON format. Raises: ValueError: error occurred when parsing the metadata schema file. TNz&Cannot parse metadata schema. Reason: z7No custom metadata with name %s in metadata flatbuffer.r>z-Cannot parse custom metadata schema. Reason: subgraph_metadatarrrGr)indent)r IDLOptions strict_jsonParserr "_FLATC_TFLITE_METADATA_SCHEMA_FILEr parsercerror generate_textjsonloadsrZrlogginginfor^dumps)r}roptparserrmetadata_schema_contentraw_json_content json_datarG schema_fileidxrcustom_metadata_schema_contentcustom_metadata_json json_metas rrr5sn& &((##/  %c * *&455'ffhh''''''''''''''' - . .N = L M MM(6vOO  j)**)2779999dK/FFC  l CT{### K & &0!'(vvxx$000000000000000 <<6 7 7  9FL H  /<-.q12CDSIIIf #788If Ia ( ( ((s$A$$A(+A(+E  E E cht|s"td|dS)zChecks if a file exists.zFile, '{0}', does not exist.N) _exists_fileIOErrorr)rs rr^r^ns< h  C 077AA B BBCCrct|t|d5}t|ddddS#1swxYwYdS)zAChecks if a model file has the expected TFLite schema identifier.r>N)r^r rr )r3rs rr.r.tsZ   *d##.q#AFFHH---..................s"AAAcdtj|dstddS)Nrz^The model provided does not have the expected identifier, and may not be a valid TFLite model.)rrModelBufferHasIdentifierrc)r;s rrr{s>   2 29a @ @,  + , ,,,,rcdtj|dstddS)zHChecks if a metadata buffer has the expected Metadata schema identifier.rzbThe metadata buffer does not have the expected identifier, and may not be a valid TFLite Metadata.N)rLrO ModelMetadataBufferHasIdentifierrc)ros rrrsC  # D DA  (  ' ( ((((rctj|d}t|D]}||}|dtj krj| }| |}| dkr| cSdS)zReturns the metadata in the model file as a buffer. Args: model_buf: valid buffer of the model file. Returns: Metadata buffer. Returns `None` if the model does not have metadata. rrFN)rrrrMetadataLengthMetadatar rHr+rBufferBuffers DataLengthr r )r; tflite_modelrr buffer_indexrRs rryrys!00A>>, ,,.. / /..a   # #D yy{{'""&7&KKK[[]]l%%l33h     ! # #  ! ! # # + + - ---- L r)r)N)6rrr#rzrr r rr%rtypingrrrrri"mediapipe.tasks.cc.metadata.pythonrmediapipe.tasks.metadatarrLrr/mediapipe.tasks.python.metadata.flatbuffers_libr tensorflowtfgfileGFiler rr. ImportErroreopenr!rrrr)robjectr+r:rrfstrrrr^r.rrryr6rrrJs&%   !!!!!!!!GGGGGGQQQQQQFFFFFFOOOOOO  u{ *#,,   *,,,,,, ((( * * * *!!! ---&&:%9(&*&*" _B_B_B_B_B_B_B_BD&"&"&"&"&"#4&"&"&"RggggggggT%s4IM6)6)-5d38n-E6)6)6)6)6)rCCC ...,,,(((s&A;;BBB