Di2ddlZddlZddlmZddlmZmZmZmZm Z ddl m Z ddl m Z dede eeed ffd efd Zded efd Zd e eefd eeeeeefffdZ dd e eefdeeeefdee eeed ffdeeegefded eeeeff dZGdde ZdZde eefd e jfdZde eefd efdZde eefd efdZGddeZy)N)Path)AnyCallablecastOptionalUnion)Image) VisionDatasetfilename extensions.returnc~|jjt|tr|St |S)aChecks 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 ]/var/www/pod-logistic/pod-ai/venv/lib/python3.12/site-packages/torchvision/datasets/folder.pyhas_file_allowed_extensionr s4 >>  $ $:j#3NZ ffTYZdTe ffc"t|tS)zChecks if a file is an allowed image extension. Args: filename (string): path to a file Returns: bool: True if the filename ends with a known image extension )rIMG_EXTENSIONS)r s r is_image_filers &h ??r directoryctdtj|D}|std|dt |Dcic]\}}|| }}}||fScc}}w)zWFinds the class folders in a dataset. See :class:`DatasetFolder` for details. c3VK|]!}|js|j#ywN)is_dirname).0entrys r zfind_classes..)sUEellnUZZUs))z"Couldn't find any class folder in .)sortedosscandirFileNotFoundError enumerate)rclassesicls_name class_to_idxs r find_classesr.$sf URZZ -BUUG "DYKq QRR3.is_valid_fileMs-a< MI|0023 < "<0 WW\\)\: ww}}Z( %bggjd&KL Y _c_h_his_t/uv vC$$ rcfeZdZdZ ddeeefdeegefde e edfde ede ed e eege fd e d dffd Z e dd eeefdeeefde e edfd e eege fd e d ee eeff dZd eeefd e eeeeefffdZded e eeffdZd efdZxZS) DatasetFolderaA 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 NrHloaderr . transformtarget_transformr/r0rc&t |||||j|j\}} |j |j| |||} ||_||_||_| |_| |_ | D cgc]} | d c} |_ ycc} w)N)rRrS)r-r r/r0r ) super__init__r.rHrNrQr r*r-samplestargets) selfrHrQr rRrSr/r0r*r-rWs __class__s rrVzDatasetFolder.__init__s EUV $ 1 1$)) <## II%!'# $  $ ( &-.!. .s9 Brr-c<| tdt|||||S)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 r/r0)r7rN)rr-r r/r0s rrNzDatasetFolder.make_datasets2@  IJ J | -ep  rct|S)utFind 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.)rYrs rr.zDatasetFolder.find_classess6I&&rindexc|j|\}}|j|}|j|j|}|j|j|}||fS)z Args: index (int): Index Returns: tuple: (sample, target) where target is class_index of the target class. )rWrQrRrS)rYr^r5targetsamples r __getitem__zDatasetFolder.__getitem__sb||E* fT" >> %^^F+F  ,**62Fv~rc,t|jSr)lenrW)rYs r__len__zDatasetFolder.__len__s4<<  r)NNNNF)NNF)__name__ __module__ __qualname____doc__rrrrrrrr8rV staticmethoddictintlistrNr.rbre __classcell__r[s@rrPrPms@15(,/39=!/CI/#$/U38_- / H% / #8, / # 56// /8159=! & d#& 38n& U38_-&  # 56 &  & eCHo  & & P'eCI&6'5cDQTVYQYNAZ;[':sCx"!!rrP) z.jpgz.jpegz.pngz.ppmz.bmpz.pgmz.tifz.tiffz.webpr5ct|d5}tj|}|jdcdddS#1swYyxYw)NrbRGB)openr convert)r5fimgs r pil_loaderrws< dD "Qjjm{{5!"""s &=Acbddl} |j|S#t$rt|cYSwxYw)Nr)accimager OSErrorrw)r5rys raccimage_loaderr{ s3 ~~d##  $ s ..cNddlm}|dk(r t|St|S)Nr)get_image_backendry) torchvisionr}r{rw)r5r}s rdefault_loaderrs&-j(t$$$rc|eZdZdZddeddfdeeefdee dee de ege fdee ege fd e f fd Z xZ S) ImageFolderaA 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 NFrHrRrSrQr/r0c dt||||tnd|||||j|_y)N)rRrSr/r0)rUrVrrWimgs)rYrHrRrSrQr/r0r[s rrVzImageFolder.__init__?s@   +3N-'#  LL r)rfrgrhrirrrrrrrr8rVrnros@rrrsD)-/3'59=!!CI!H%!#8, ! #$ !  # 56 !!!rr)NNNF)r&os.pathpathlibrtypingrrrrrPILr visionr rrr8rrrmrkrlr.rNrPrrwr{rrrrrs 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