U
    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eeej	f eee
e ef ee ee ee ed fd	d
ZedddZeeeef dddZedddZd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.
        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.gzZ 5c4f3ee8e5d25df40f4fd59a7f44e54c)zBhttps://www.robots.ox.ac.uk/~vgg/data/pets/data/annotations.tar.gzZ 95a8c909bbe2e81eed6a22bccdf3f68f)categorybinary-categoryZ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	  _|r     std
g }g  _g  _t j j d V}	|	D ]J}
|
  \}}}}||  jt|d   jt|d  qW 5 Q R X 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 V/var/www/html/venv/lib/python3.8/site-packages/torchvision/datasets/oxford_iiit_pet.py
<listcomp>5   s    z*OxfordIIITPet.__init__.<locals>.<listcomp>)r   r   r   zoxford-iiit-petZimagesannotationsZtrimapsz;Dataset not found. You can use download=True to download itz.txtr	   ZCatZ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>Q   s     z4OxfordIIITPet.__init__.<locals>.<listcomp>.<genexpr>_)joinr   )r   Zraw_clsr'   r   r   r   r    P   s   c                 S   s$   h | ]\}}| d dd |fqS )r'   r	   r   )rsplit)r   image_idlabelr   r   r   	<setcomp>S   s     z)OxfordIIITPet.__init__.<locals>.<setcomp>c                 S   s   | d S )Nr	   r   )Zimage_id_and_labelr   r   r   <lambda>T       z(OxfordIIITPet.__init__.<locals>.<lambda>)keyc                    s   g | ]} j | d  qS )z.jpg)_images_folderr   r*   r   r   r   r    Z   s     c                    s   g | ]} j | d  qS )z.png)_segs_folderr1   r   r   r   r    [   s     )#r   _split
isinstancestr_target_typessuper__init__pathlibPathr   _base_folderr0   _anns_folderr2   	_download_check_existsRuntimeError_labels_bin_labelsopenstripr   appendintZbin_classessortedzipclassesdictrangelenZbin_class_to_idxZclass_to_idx_images_segs)r   r   r   r   r   r   r   r   Z	image_idsfileliner*   r+   Z	bin_labelr'   	__class__r   r   r8   (   sF    



 
zOxfordIIITPet.__init__)returnc                 C   s
   t | jS r#   )rK   rL   r   r   r   r   __len__]   s    zOxfordIIITPet.__len__)idxrR   c                 C   s   t | j| d}g }| jD ]N}|dkr>|| j|  q |dkrX|| j|  q |t | j|  q |szd }nt	|dkr|d }nt
|}| jr| ||\}}||fS )NRGBr   r   r	   r   )r   rB   rL   convertr6   rD   r@   rA   rM   rK   tupler   )r   rT   imagetargetr   r   r   r   __getitem__`   s     

zOxfordIIITPet.__getitem__c                 C   s4   | j | jfD ]"}tj|r(tj|s dS qdS )NFT)r0   r<   ospathexistsisdir)r   folderr   r   r   r>   x   s    zOxfordIIITPet._check_existsc                 C   s4   |   rd S | jD ]\}}t|t| j|d qd S )N)Zdownload_rootmd5)r>   
_RESOURCESr
   r5   r;   )r   urlr`   r   r   r   r=      s    zOxfordIIITPet._download)r   r   NNNF)__name__
__module____qualname____doc__ra   r   r   r5   r9   r:   r   r   r   boolr8   rE   rS   r   r   rZ   r>   r=   __classcell__r   r   rP   r   r      s,         5r   )r[   os.pathr9   typingr   r   r   r   r   r   ZPILr   utilsr
   r   Zvisionr   r   r   r   r   r   <module>   s    