o
    Vh,                     @   st   d dl Z d dlZ d dlZd dlmZmZmZmZmZm	Z	 d dl
mZ ddlmZmZ ddlmZ G dd deZdS )	    N)AnyCallableOptionalSequenceTupleUnion)Image   )download_and_extract_archiveverify_str_arg)VisionDatasetc                       s   e Zd ZdZdZdZ						ddeeej	f d	ed
ee
e ef dee dee dee def fddZdefddZdedeeef fddZdefddZdddZ  ZS )OxfordIIITPeta  `Oxford-IIIT Pet Dataset   <https://www.robots.ox.ac.uk/~vgg/data/pets/>`_.

    Args:
        root (str or ``pathlib.Path``): Root directory of the dataset.
        split (string, optional): The dataset split, supports ``"trainval"`` (default) or ``"test"``.
        target_types (string, sequence of strings, optional): Types of target to use. Can be ``category`` (default) or
            ``segmentation``. Can also be a list to output a tuple with all specified target types. The types represent:

                - ``category`` (int): Label for one of the 37 pet categories.
                - ``binary-category`` (int): Binary label for cat or dog.
                - ``segmentation`` (PIL image): Segmentation trimap of the image.

            If empty, ``None`` will be returned as target.

        transform (callable, optional): A function/transform that takes in a PIL image and returns a transformed
            version. E.g, ``transforms.RandomCrop``.
        target_transform (callable, optional): A function/transform that takes in the target and transforms it.
        transforms (callable, optional): A function/transform that takes input sample
            and its target as entry and returns a transformed version.
        download (bool, optional): If True, downloads the dataset from the internet and puts it into
            ``root/oxford-iiit-pet``. If dataset is already downloaded, it is not downloaded again.
    ))z=https://www.robots.ox.ac.uk/~vgg/data/pets/data/images.tar.gz 5c4f3ee8e5d25df40f4fd59a7f44e54c)zBhttps://www.robots.ox.ac.uk/~vgg/data/pets/data/annotations.tar.gz 95a8c909bbe2e81eed6a22bccdf3f68f)categorybinary-categorysegmentationtrainvalr   NFrootsplittarget_types
transforms	transformtarget_transformdownloadc                    s  t |dd _t|tr|g} fdd|D  _t j||||d t j	d  _
 j
d  _ j
d  _ jd	  _|rD     sLtd
g }g  _g  _t j j d 0}	|	D ]%}
|
  \}}}}||  jt|d   jt|d  qbW d    n1 sw   Y  ddg _dd tdd t| jD dd dD  _tt jtt j _tt jtt j _  fdd|D  _! fdd|D  _"d S )Nr   )r   testc                    s   g | ]	}t |d  jqS )r   )r   _VALID_TARGET_TYPES).0target_typeself X/var/www/vscode/kcb/lib/python3.10/site-packages/torchvision/datasets/oxford_iiit_pet.py
<listcomp>7   s    z*OxfordIIITPet.__init__.<locals>.<listcomp>)r   r   r   zoxford-iiit-petimagesannotationstrimapsz;Dataset not found. You can use download=True to download itz.txtr	   CatDogc                 S   s*   g | ]\}}d  dd |dD qS ) c                 s   s    | ]}|  V  qd S N)title)r   partr!   r!   r"   	<genexpr>S   s    z4OxfordIIITPet.__init__.<locals>.<listcomp>.<genexpr>_)joinr   )r   raw_clsr.   r!   r!   r"   r#   R   s    c                 S   s$   h | ]\}}| d dd |fqS )r.   r	   r   )rsplit)r   image_idlabelr!   r!   r"   	<setcomp>U   s   $ z)OxfordIIITPet.__init__.<locals>.<setcomp>c                 S   s   | d S )Nr	   r!   )image_id_and_labelr!   r!   r"   <lambda>V   s    z(OxfordIIITPet.__init__.<locals>.<lambda>)keyc                       g | ]
} j | d  qS )z.jpg)_images_folderr   r2   r   r!   r"   r#   \       c                    r8   )z.png)_segs_folderr:   r   r!   r"   r#   ]   r;   )#r   _split
isinstancestr_target_typessuper__init__pathlibPathr   _base_folderr9   _anns_folderr<   	_download_check_existsRuntimeError_labels_bin_labelsopenstripr   appendintbin_classessortedzipclassesdictrangelenbin_class_to_idxclass_to_idx_images_segs)r    r   r   r   r   r   r   r   	image_idsfileliner2   r3   	bin_labelr.   	__class__r   r"   rB   *   sJ   




zOxfordIIITPet.__init__returnc                 C   s
   t | jS r*   )rV   rY   r   r!   r!   r"   __len___   s   
zOxfordIIITPet.__len__idxc                 C   s   t | j| d}g }| jD ]'}|dkr|| j|  q|dkr,|| j|  q|t | j|  q|s=d }nt	|dkrH|d }nt
|}| jrW| ||\}}||fS )NRGBr   r   r	   r   )r   rL   rY   convertr@   rN   rJ   rK   rZ   rV   tupler   )r    rc   imagetargetr   r!   r!   r"   __getitem__b   s    

zOxfordIIITPet.__getitem__c                 C   s4   | j | jfD ]}tj|rtj|s dS qdS )NFT)r9   rF   ospathexistsisdir)r    folderr!   r!   r"   rH   z   s
   zOxfordIIITPet._check_existsc                 C   s4   |   rd S | jD ]\}}t|t| j|d q	d S )N)download_rootmd5)rH   
_RESOURCESr
   r?   rE   )r    urlrp   r!   r!   r"   rG      s
   zOxfordIIITPet._download)r   r   NNNF)ra   N)__name__
__module____qualname____doc__rq   r   r   r?   rC   rD   r   r   r   boolrB   rO   rb   r   r   ri   rH   rG   __classcell__r!   r!   r_   r"   r      s:    5r   )rj   os.pathrC   typingr   r   r   r   r   r   PILr   utilsr
   r   visionr   r   r!   r!   r!   r"   <module>   s     