U
h @ st d dl mZ d dlZd dlmZ d dlmZmZmZm Z m
Z
d dl Z ddl
mZmZ ddlmZ G dd d eZdS )
) annotationsN)Path)AnyCallableOptionalTupleUnion ) download_and_extract_archiveverify_str_arg)
VisionDatasetc sr e Zd ZdZdZddddd d d
d d fd
d
ZddddZdddddZd dddZd
dddZ Z
S ) FGVCAircrafta `FGVC Aircraft `_ Dataset.
The dataset contains 10,000 images of aircraft, with 100 images for each of 100
different aircraft model variants, most of which are airplanes.
Aircraft models are organized in a three-levels hierarchy. The three levels, from
finer to coarser, are:
- ``variant``, e.g. Boeing 737-700. A variant collapses all the models that are visually
indistinguishable into one class. The dataset comprises 100 different variants.
- ``family``, e.g. Boeing 737. The dataset comprises 70 different families.
- ``manufacturer``, e.g. Boeing. The dataset comprises 30 different manufacturers.
Args:
root (str or ``pathlib.Path``): Root directory of the FGVC Aircraft dataset.
split (string, optional): The dataset split, supports ``train``, ``val``,
``trainval`` and ``test``.
annotation_level (str, optional): The annotation level, supports ``variant``,
``family`` and ``manufacturer``.
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 in root directory. If dataset is already downloaded, it is not
downloaded again.
zWhttps://www.robots.ox.ac.uk/~vgg/data/fgvc-aircraft/archives/fgvc-aircraft-2013b.tar.gztrainvalvariantNFzUnion[str, Path]strzOptional[Callable]boolNone)rootsplitannotation_level transformtarget_transformdownloadreturnc sh t j|||d t|dd| _t|dd| _tj| jd| _ |rL|
| s\t dtj| j dd d
d d| j }t
|d }d
d |D | _W 5 Q R X tt| jtt| j| _tj| j dd} tj| j dd| j d| j d}
g | _g | _t
|
d T}|D ]H} | dd\} }
| jtj| | d | j| j|
qW 5 Q R X d S )N)r r r )trainvalr testr )r familyZ manufacturerzfgvc-aircraft-2013bz;Dataset not found. You can use download=True to download itdataz variants.txtz families.txtzmanufacturers.txtrc S s g | ] }| qS )strip).0liner r T/var/www/html/venv/lib/python3.8/site-packages/torchvision/datasets/fgvc_aircraft.py
K s z)FGVCAircraft.__init__..ZimagesZimages__z.txt r z.jpg)super__init__r _splitZ_annotation_levelospathjoinr
_data_path _download
_check_exists RuntimeErroropenclassesdictziprangelenZ class_to_idx _image_files_labelsr! r append)selfr r r r r r Zannotation_filefZimage_data_folderZ labels_filer# Z
image_nameZ
label_name __class__r r$ r) + sD $ zFGVCAircraft.__init__int)r c C s
t | jS N)r7 r8 r; r r r$ __len__[ s zFGVCAircraft.__len__zTuple[Any, Any])idxr c C sP | j | | j| }}tj|d}| jr8| |}| jrH| |}||fS )NRGB)r8 r9 PILZImager2 convertr r )r; rC Z
image_filelabelimager r r$ __getitem__^ s
zFGVCAircraft.__getitem__c C s | r dS t| j| j dS )zW
Download the FGVC Aircraft dataset archive and extract it under root.
N)r0 r
_URLr rA r r r$ r/ j s zFGVCAircraft._downloadc C s t j| jot j| jS r@ )r+ r, existsr. isdirrA r r r$ r0 r s zFGVCAircraft._check_exists)r r NNF) __name__
__module__ __qualname____doc__rJ r) rB rI r/ r0
__classcell__r r r= r$ r
s 0 r
)
__future__r r+ pathlibr typingr r r r r Z PIL.ImagerE utilsr
r Zvisionr r
r r r r$ s