+ j2^RIt^RIt^RIHt^RIHtHtHtHtH t ^RI H t ^RI H t RRltRR ltR R ltRR R llt!RR] 4tRtRRltRRltRRlt!RR]4tR#)N)Path)AnyCallablecastOptionalUnion)Image) VisionDatasetcxV^8dQhR\R\\\\R3,3,R\/#)filename extensions.return)strrtuplebool)formats"\/home/luca/screen-checking/.venv/lib/python3.14/site-packages/torchvision/datasets/folder.py __annotate__r s: g g g%U3PS8_@T:U gZ^ gcVP4P\V\4'dV4#\ V44#)zChecks if a file is an allowed extension. Args: filename (string): path to a file extensions (tuple of strings): extensions to consider (lowercase) Returns: bool: True if the filename ends with one of given extensions )lowerendswith isinstancerr)r rs&&rhas_file_allowed_extensionr s7 >>  $ $:j#3N3NZ ffTYZdTe ffrc0V^8dQhR\R\/#)r r rrr)rs"rrrs @ @C @D @rc"\V\4#)zChecks if a file is an allowed image extension. Args: filename (string): path to a file Returns: bool: True if the filename ends with a known image extension )rIMG_EXTENSIONS)r s&r is_image_filer s &h ??rcV^8dQhR\\\3,R\\\,\ \\ 3,3,/#r directoryrrrrrlistdictint)rs"rrr$s9 ! !E#t), !tCy$sCx.7P1Q !rc\R\P!V444pV'g\RV R24h\ V4UUu/uFwr#W2bK pppW3#uuppi)zOFinds the class folders in a dataset. See :class:`DatasetFolder` for details. c3h"TF(qP4'gKVPxK* R#5iN)is_dirname).0entrys& r find_classes..)sU-BEllnZUZZ-Bs22z"Couldn't find any class folder in .)sortedosscandirFileNotFoundError enumerate)r#classesicls_name class_to_idxs& r find_classesr;$sc URZZ -BUUG "DYKq QRR3*9sE#s(O3459HcUD[12 9  9  %S/ 9rca\PPV4pVf\V4wrQMV'g \ R4hSRJ;'dVRJpSRJ;'dVRJpV'g V'd \ R4hSe RV3Rllp\ \ \.\3,V4p.p\4p \VP44Fp W,p \PPW 4p \PPV 4'gKQ\\P!V RR74Fuwrp\V4F`p\PPW4pV!V4'gK2VV 3pVPV4W9gKOV P!V 4Kb Kw K \VP44V , pV'diV'gaRR P\V44 R 2pSe4TR \#S\4'dSMR PS4 2, p\%V4hV#) zGenerates a list of samples of a form (path_to_sample, class). See :class:`DatasetFolder` for details. Note: The class_to_idx parameter is here optional and will use the logic of the ``find_classes`` function by default. NzE'class_to_index' must have at least one entry to collect any samples.zMBoth extensions and is_valid_file cannot be None or not None at the same timec0V^8dQhR\R\/#)r xrr)rs"rr"make_dataset..__annotate__Ms = =S =T =rc<\VS4#r*)r)rBrs&rr>#make_dataset..is_valid_fileMs-a< r?_ both_noneboth_something instancesavailable_classes target_class class_index target_dirrootfnamesfnamerGitem empty_classesmsgs&&f&& r make_datasetr_1s""9-I&y1< `aad"<<}'MI|0023 "0 WW\\): ww}}Z(( %bggjd&KLODVww||D0 &&,D$$T*#<)--l;( M 4 ))+,/@@M[4TYYvm?T5U4VVXY  ! /jUX>Y>Y _c_h_his_t/uv vC$$ rcaa]tRt^mtoRtR V3RlV3Rlllt]RV3RlRll4tV3RlRltV3RlR lt V3R lR lt R t Vt V;t #) DatasetFoldera0A generic data loader. This default directory structure can be customized by overriding the :meth:`find_classes` method. Args: root (str or ``pathlib.Path``): Root directory path. loader (callable): A function to load a sample given its path. extensions (tuple[string]): A list of allowed extensions. both extensions and is_valid_file should not be passed. transform (callable, optional): A function/transform that takes in a sample and returns a transformed version. E.g, ``transforms.RandomCrop`` for images. target_transform (callable, optional): A function/transform that takes in the target and transforms it. is_valid_file (callable, optional): A function that takes path of a file and check if the file is a valid file (used to check of corrupt files) both extensions and is_valid_file should not be passed. allow_empty(bool, optional): If True, empty folders are considered to be valid classes. An error is raised on empty folders if False (default). Attributes: classes (list): List of the class names sorted alphabetically. class_to_idx (dict): Dict with items (class_name, class_index). samples (list): List of (sample path, class_index) tuples targets (list): The class_index value for each image in the dataset c<V^8dQhRS[S[S[3,RS[S[.S[3,RS[S[S[R3,,RS[S[,RS[S[,RS[S[S[.S[3,,RS[R R /#) r rYloaderr. transformtarget_transformr>r?rN)rrrrrrrr)r __classdict__s"rrDatasetFolder.__annotate__s//CI/#$/U38_- / H% / #8, / # 56// /rc$<\S V`WVR7VPVP4wrVP VPV VVVR7p W nW0nWnWnWn V U u.uF q^,NK up Vn R#uup i))rdre)r:rr>r?N) super__init__r;rYr_rcrr7r:samplestargets) selfrYrcrrdrer>r?r7r:rks __class__s &&&&&&&& rrjDatasetFolder.__init__s EUV $ 1 1$)) <## II%!'# $  $ ( &-.g!g. .s2B c<V^8dQhRS[S[S[3,RS[S[S[3,RS[S[S[R3,,RS[S[S[.S[3,,RS[RS[ S[S[S[3,,/#r=) rrrr&r'rrrrr%)rrfs"rrrgs& & d#& 38n& U38_-&  # 56 &  & eCHo  & rc <Vf \R4h\WW#VR7#)aGenerates a list of samples of a form (path_to_sample, class). This can be overridden to e.g. read files from a compressed zip file instead of from the disk. Args: directory (str): root dataset directory, corresponding to ``self.root``. class_to_idx (Dict[str, int]): Dictionary mapping class name to class index. extensions (optional): A list of allowed extensions. Either extensions or is_valid_file should be passed. Defaults to None. is_valid_file (optional): A function that takes path of a file and checks if the file is a valid file (used to check of corrupt files) both extensions and is_valid_file should not be passed. Defaults to None. allow_empty(bool, optional): If True, empty folders are considered to be valid classes. An error is raised on empty folders if False (default). Raises: ValueError: In case ``class_to_idx`` is empty. ValueError: In case ``extensions`` and ``is_valid_file`` are None or both are not None. FileNotFoundError: In case no valid file was found for any class. Returns: List[Tuple[str, int]]: samples of a form (path_to_sample, class) z*The class_to_idx parameter cannot be None.)rr>r?)rIr_)r#r:rr>r?s&&&&&rr_DatasetFolder.make_datasets.@  IJ J  ep  rcx<V^8dQhRS[S[S[3,RS[S[S[,S[S[S[3,3,/#r"r$)rrfs"rrrgs=''eCI&6'5cDQTVYQYNAZ;['rc \V4#)uFind the class folders in a dataset structured as follows:: directory/ ├── class_x │ ├── xxx.ext │ ├── xxy.ext │ └── ... │ └── xxz.ext └── class_y ├── 123.ext ├── nsdf3.ext └── ... └── asd932_.ext This method can be overridden to only consider a subset of classes, or to adapt to a different dataset directory structure. Args: directory(str): Root directory path, corresponding to ``self.root`` Raises: FileNotFoundError: If ``dir`` has no class folders. Returns: (Tuple[List[str], Dict[str, int]]): List of all classes and dictionary mapping each class to an index. )r;)rmr#s&&rr;DatasetFolder.find_classess6I&&rc<<V^8dQhRS[RS[S[S[3,/#)r indexr)r'rr)rrfs"rrrgs#sCxrc VPV,wr#VPV4pVPeVPV4pVPeVPV4pWC3#)zu Args: index (int): Index Returns: tuple: (sample, target) where target is class_index of the target class. )rkrcrdre)rmrxrGtargetsamples&& r __getitem__DatasetFolder.__getitem__s^||E* T" >> %^^F+F  ,**62F~rc <V^8dQhRS[/#)r r)r')rrfs"rrrgs!!!rc,\VP4#r*)lenrk)rms&r__len__DatasetFolder.__len__s4<<  r)r:r7rrcrkrl)NNNNF)NNF)__name__ __module__ __qualname____firstlineno____doc__rj staticmethodr_r;r|r__static_attributes____classdictcell__ __classcell__rorfs@@rraramsQ8//8& & & P'':"!!!rracfV^8dQhR\\\3,R\P/#r rGr)rrrr )rs"rrrs'""U39%"%++"rc\VR4;_uu_4p\P!V4pVPR4uuRRR4# +'giR#;i)rbRGBN)openr convert)rGfimgs& r pil_loaderrs9 dD  Qjjm{{5!    s 'A A cRV^8dQhR\\\3,R\/#rrrrr)rs"rrr s#  %T * s rcf^RIpVPV4# \d\T4u#i;i)rN)accimager OSErrorr)rGrs& raccimage_loaderr s3 ~~d##  $ s 00cRV^8dQhR\\\3,R\/#rr)rs"rrrs#  sDy) c rcR^RIHpV!4R8Xd \V4#\V4#)r)get_image_backendr) torchvisionrrr)rGrs& rdefault_loaderrs&-j(t$$$rcPaa]tRtRtoRtRR]RR3V3RlV3RllltRtVtV;t #) ImageFolderiaBA generic data loader where the images are arranged in this way by default: :: root/dog/xxx.png root/dog/xxy.png root/dog/[...]/xxz.png root/cat/123.png root/cat/nsdf3.png root/cat/[...]/asd932_.png This class inherits from :class:`~torchvision.datasets.DatasetFolder` so the same methods can be overridden to customize the dataset. Args: root (str or ``pathlib.Path``): Root directory path. transform (callable, optional): A function/transform that takes in a PIL image or torch.Tensor, depends on the given loader, and returns a transformed version. E.g, ``transforms.RandomCrop`` target_transform (callable, optional): A function/transform that takes in the target and transforms it. loader (callable, optional): A function to load an image given its path. is_valid_file (callable, optional): A function that takes path of an Image file and check if the file is a valid file (used to check of corrupt files) allow_empty(bool, optional): If True, empty folders are considered to be valid classes. An error is raised on empty folders if False (default). Attributes: classes (list): List of the class names sorted alphabetically. class_to_idx (dict): Dict with items (class_name, class_index). imgs (list): List of (image path, class_index) tuples NFc <V^8dQhRS[S[S[3,RS[S[,RS[S[,RS[S[.S[3,RS[S[S[.S[3,,RS[/#)r rYrdrercr>r?)rrrrrrr)rrfs"rrImageFolder.__annotate__?su!!CI!H%!#8, ! #$ !  # 56 !!rc j<\ST`TTVf\MRVVVVR7VPVnR#)N)rdrer>r?)rirjrrkimgs)rmrYrdrercr>r?ros&&&&&&&rrjImageFolder.__init__?s@   +3N-'#  LL r)r) rrrrrrrjrrrrs@@rrrs+D)-/3'59=!!!!rr)NNNF) z.jpgz.jpegz.pngz.ppmz.bmpz.pgmz.tifz.tiffz.webp)r3os.pathpathlibrtypingrrrrrPILr visionr rr r;r_rarrrrrrrrsc 77! g @ !9xQ!MQ!h]"  2!-2!r