h2SSKrSSKrSSKJr SSKJrJrJrJrJ r SSK J r SSK J r S\S\ \\\S 44S \4S jrS\S \4S jrS \ \\4S \\\\\\444SjrSS \ \\4S\\\\4S\\ \\\S 44S\\\/\4S\S \\\\44 Sjjr"SS\ 5rSrS\ \\4S \ R4SjrS\ \\4S \4SjrS\ \\4S \4Sjr"SS\5rg)N)Path)AnyCallablecastOptionalUnion)Image) VisionDatasetfilename extensions.returncUR5R[U[5(aU5$[ U55$)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 isinstancestrtuple)r r s S/var/www/auris/envauris/lib/python3.13/site-packages/torchvision/datasets/folder.pyhas_file_allowed_extensionr s7 >>  $ $:j#3N3NZ ffTYZdTe ffc"[U[5$)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_filers &h ??r directoryc[S[R"U555nU(d[SUS35e[ U5VVs0sHup#X2_M nnnX4$s snnf)zOFinds the class folders in a dataset. See :class:`DatasetFolder` for details. c3f# UH'oR5(dMURv M) g7fN)is_dirname).0entrys r find_classes..)sU-BEllnZUZZ-Bs11z"Couldn't find any class folder in .)sortedosscandirFileNotFoundError enumerate)rclassesicls_name class_to_idxs r find_classesr/$sc URZZ -BUUG "DYKq QRR3[UT5$r)r)r3r s rr0#make_dataset..is_valid_fileMs-a< MI|0023 "0 WW\\): ww}}Z(( %bggjd&KLODVww||D0 &&,D$$T*#<)--l;( M 4 ))+,/@@M[4TYYvm?T5U4VVXY  ! /jUX>Y>Y _c_h_his_t/uv vC$$ rc~^\rSrSrSrSS\\\4S\\/\ 4S\ \ \S4S\ \S \ \S \ \\/\ 4S \ S S4U4S jjjr \SS\\\4S\\\4S\ \ \S4S \ \\/\ 4S \ S \\ \\44 Sjj5rS\\\4S \ \\\\\444SjrS\S \ \ \ 44SjrS \4SjrSrU=r$) DatasetFolderma0A 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 NrJloaderr . transformtarget_transformr0r1rc>[T U]XUS9 URUR5upUR URU UUUS9n X lX0lXlXlXl U V s/sHoSPM sn Ul gs sn f)N)rUrV)r.r r0r1r ) super__init__r/rJrPrTr r+r.samplestargets) selfrJrTr rUrVr0r1r+r.rZs __class__s rrYDatasetFolder.__init__s EUV $ 1 1$)) <## II%!'# $  $ ( &-.g!g. .s,Brr.c4Uc [S5e[XX#US9$)aGenerates a list of samples of a form (path_to_sample, class). This can be overridden to e.g. read files from a compressed zip file instead of from the disk. Args: directory (str): root dataset directory, corresponding to ``self.root``. class_to_idx (Dict[str, int]): Dictionary mapping class name to class index. extensions (optional): A list of allowed extensions. Either extensions or is_valid_file should be passed. Defaults to None. is_valid_file (optional): A function that takes path of a file and checks if the file is a valid file (used to check of corrupt files) both extensions and is_valid_file should not be passed. Defaults to None. allow_empty(bool, optional): If True, empty folders are considered to be valid classes. An error is raised on empty folders if False (default). Raises: ValueError: In case ``class_to_idx`` is empty. ValueError: In case ``extensions`` and ``is_valid_file`` are None or both are not None. FileNotFoundError: In case no valid file was found for any class. Returns: List[Tuple[str, int]]: samples of a form (path_to_sample, class) z*The class_to_idx parameter cannot be None.)r r0r1)r9rP)rr.r r0r1s rrPDatasetFolder.make_datasets.@  IJ J  ep  rc[U5$)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/)r\rs rr/DatasetFolder.find_classess6I&&rindexcURUup#URU5nURbURU5nURbURU5nXC4$)zu Args: index (int): Index Returns: tuple: (sample, target) where target is class_index of the target class. )rZrTrUrV)r\rdr7targetsamples r __getitem__DatasetFolder.__getitem__s^||E* T" >> %^^F+F  ,**62F~rc,[UR5$r)lenrZ)r\s r__len__DatasetFolder.__len__s4<<  r)r.r+r rTrZr[)NNNNF)NNF)__name__ __module__ __qualname____firstlineno____doc__rrrrrrrr:rY staticmethoddictintlistrPr/rhrl__static_attributes__ __classcell__r^s@rrRrRms@15(,/39=!/CI/#$/U38_- / H% / #8, / # 56// //8159=! & d#& 38n& U38_-&  # 56 &  & eCHo  & & P'eCI&6'5cDQTVYQYNAZ;[':sCx"!!!rrR) z.jpgz.jpegz.pngz.ppmz.bmpz.pgmz.tifz.tiffz.webpr7c[US5n[R"U5nURS5sSSS5 $!,(df  g=f)NrbRGB)openr convert)r7fimgs r pil_loaderrs3 dD Qjjm{{5!   s '> A cdSSKnURU5$![a [U5s$f=f)Nr)accimager OSErrorr)r7rs raccimage_loaderr s3 ~~d##  $ s //cPSSKJn U"5S:Xa [U5$[U5$)Nr)get_image_backendr) torchvisionrrr)r7rs rdefault_loaderrs&-j(t$$$rc^\rSrSrSrSS\SS4S\\\4S\ \ S\ \ S\ \/\ 4S \ \ \/\ 4S \ 4 U4S jjjr S rU=r$) ImageFolderiaBA generic data loader where the images are arranged in this way by default: :: root/dog/xxx.png root/dog/xxy.png root/dog/[...]/xxz.png root/cat/123.png root/cat/nsdf3.png root/cat/[...]/asd932_.png This class inherits from :class:`~torchvision.datasets.DatasetFolder` so the same methods can be overridden to customize the dataset. Args: root (str or ``pathlib.Path``): Root directory path. transform (callable, optional): A function/transform that takes in a PIL image or torch.Tensor, depends on the given loader, and returns a transformed version. E.g, ``transforms.RandomCrop`` target_transform (callable, optional): A function/transform that takes in the target and transforms it. loader (callable, optional): A function to load an image given its path. is_valid_file (callable, optional): A function that takes path of an Image file and check if the file is a valid file (used to check of corrupt files) allow_empty(bool, optional): If True, empty folders are considered to be valid classes. An error is raised on empty folders if False (default). Attributes: classes (list): List of the class names sorted alphabetically. class_to_idx (dict): Dict with items (class_name, class_index). imgs (list): List of (image path, class_index) tuples NFrJrUrVrTr0r1c `>[TU]UUUc[OSUUUUS9 URUlg)N)rUrVr0r1)rXrYrrZimgs)r\rJrUrVrTr0r1r^s rrYImageFolder.__init__?s@   +3N-'#  LL r)r)rnrorprqrrrrrrrrrr:rYrwrxrys@rrrsD)-/3'59=!!CI!H%!#8, ! #$ !  # 56 !!!rr)NNNF)r'os.pathpathlibrtypingrrrrrPILr visionr rrr:rrrvrtrur/rPrRrrrrrrrrs 77! g g%U3PS8_@T:U gZ^ g @C @D @ !E#t), !tCy$sCx.7P1Q !.28<59 9S$Y94S>*9sE#s(O3459HcUD[12 9  9  %S/ 9xQ!MQ!h]"U39%"%++" %T * s  sDy) c 2!-2!r