{-j% d dl mZ d dlmZmZmZ er d dlmZ d dlm Z ddl
m Z m Z ed Z
d dlZd dlZd dlZd dlmZ d dlZd d lmZ d d
lmZ d d lmZ g Zd Z d
Z dZ dZ dZ dZ!ddddZ" G d dee#d Z$dS ) ) annotations)
TYPE_CHECKINGAnyLiteralN)
_Transform )
_ImageBackend_ImageDataTypetrainvalidtest)Image)_check_exists_and_download)Dataset)
try_importz8http://paddlemodels.bj.bcebos.com/flowers/102flowers.tgzz9http://paddlemodels.bj.bcebos.com/flowers/imagelabels.matz3http://paddlemodels.bj.bcebos.com/flowers/setid.mat 52808999861908f626f3c1f4e79d11fa e0620be6f572b9609742df49c70aed4d a5357ecc9cb78c4bef273ce3793fc85ctstidtrnidr
)r r r
c v e Zd ZU dZded< ded< ded< ded< ded < d
ed < dddZd dZd Zd S ) Flowersa
Implementation of `Flowers102 `_
dataset.
Args:
data_file (str|None, optional): Path to data file, can be set None if
:attr:`download` is True. Default: None, default data path: ~/.cache/paddle/dataset/flowers/.
label_file (str|None, optional): Path to label file, can be set None if
:attr:`download` is True. Default: None, default data path: ~/.cache/paddle/dataset/flowers/.
setid_file (str|None, optional): Path to subset index file, can be set
None if :attr:`download` is True. Default: None, default data path: ~/.cache/paddle/dataset/flowers/.
mode (str, optional): Either train or test mode. Default 'train'.
transform (Callable|None, optional): transform to perform on image, None for no transform. Default: None.
download (bool|None, optional): download dataset automatically if :attr:`data_file` is None. Default: True.
backend (str|None, optional): Specifies which type of image to be returned:
PIL.Image or numpy.ndarray. Should be one of {'pil', 'cv2'}.
If this option is not set, will get backend from :ref:`paddle.vision.get_image_backend `,
default backend is 'pil'. Default: None.
Returns:
:ref:`api_paddle_io_Dataset`. An instance of Flowers dataset.
Examples:
.. code-block:: python
>>> # doctest: +TIMEOUT(60)
>>> import itertools
>>> import paddle.vision.transforms as T
>>> from paddle.vision.datasets import Flowers
>>> flowers = Flowers()
>>> print(len(flowers))
6149
>>> for i in range(5): # only show first 5 images
... img, label = flowers[i]
... # do something with img and label
... print(type(img), img.size, label)
... # (523, 500) [1]
>>> transform = T.Compose(
... [
... T.Resize(64),
... T.ToTensor(),
... T.Normalize(
... mean=[0.5, 0.5, 0.5],
... std=[0.5, 0.5, 0.5],
... to_rgb=True,
... ),
... ]
... )
>>> flowers_test = Flowers(
... mode="test",
... transform=transform, # apply transform to every image
... backend="cv2", # use OpenCV as image transform backend
... )
>>> print(len(flowers_test))
1020
>>> for img, label in itertools.islice(iter(flowers_test), 5): # only show first 5 images
... # do something with img and label
... print(type(img), img.shape, label) # type: ignore
... # [3, 64, 96] [1]
r backend
str | None data_file
label_file
setid_file _DatasetModemode_Transform[Any, Any] | None transformNr Tdownloadbool_ImageBackend | NonereturnNonec ^ | dv s
J d| | t j }|dvrt d| || _ t | }|s)|s
J d t |t t d| }|s)|s
J d t |t t d| }|s)|s
J d t |t t d| }|| _ t j | } | d d
| _ t& j | j st' j | j t& j | j d }
t& j |
s| | j t3 d } | | d
d | _ | | | d | _ d S )Nr z3mode should be 'train', 'valid' or 'test', but got )pilcv2z4Expected backend are one of ['pil', 'cv2'], but got z>data_file is not set and downloading automatically is disabledflowersz?label_file is not set and downloading automatically is disabledz?setid_file is not set and downloading automatically is disabledz.tgz/jpgzscipy.iolabelsr ) lowerpaddlevisionget_image_backend
ValueErrorr
MODE_FLAG_MAPr DATA_URLDATA_MD5 LABEL_URL LABEL_MD5 SETID_URL SETID_MD5r" tarfileopenreplace data_pathospathexistsmkdirjoin
extractallr loadmatr. indexes) selfr r r r r" r# r flagdata_tarjpg_pathscios ^/var/www/html/banglarbhumi/venv/lib/python3.11/site-packages/paddle/vision/datasets/flowers.py__init__zFlowers.__init__ sH zz||
H G G
? m5577G . ( ( PwPP
TZZ\\*
P
8 38Xy( I
Q
8 4Iy)X J
Q
8 4Iy)X J #< **"**6377w~~dn-- % HT^ $ $ $7<<66w~~h'' 0 / / /*%%ll:..x8; ||J//5a8 idxint,tuple[_ImageDataType, npt.NDArray[np.int64]]c N | j | }t j | j |dz
g }d|dd}t j | j | }| j dk rt j
| }n1| j dk r&t j t j
| }| j | | }| j dk r|| d fS | t j | d fS )N z
jpg/image_05z.jpgr) r* int64)rF nparrayr. r? r@ rC r> r r r< r" astyper0 get_default_dtype)rG rO indexlabelimg_nameimages rL __getitem__zFlowers.__getitem__ s S!$+eai0122..... T^X66 <5 Ju%%EE
\U
"
"HUZ . .//E > %NN5))E <5 %,,w/// /||F 4 6 677 g9N9NNNrN c * t | j S )N)lenrF )rG s rL __len__zFlowers.__len__ s 4< rN )NNNr NTN)r r r r r r r r r" r! r# r$ r r% r& r' )rO rP r& rQ )__name__
__module__ __qualname____doc____annotations__rM r^ ra rN rL r r 6 s @ @D **** !%!%!% $15 (,>9 >9 >9 >9 >9@O O O O(! ! ! ! !rN r )r
znpt.NDArray[np.int64])%
__future__r typingr r r numpy.typingnpt#paddle.vision.transforms.transformsr r] r r
r r? r; numpyrV PILr r0 paddle.dataset.commonr paddle.ior paddle.utilsr __all__r5 r7 r9 r6 r8 r: r4 tupler rg rN rL rt sr # " " " " " . . . . . . . . . . 5 >>>>>>5555555534L
< < < < < < # # # # # #
E G A - . .
"7WEE
_! _! _! _! _!ge EFG _! _! _! _! _!rN