Flowers¶

class paddle.vision.datasets. Flowers ( data_file=None, label_file=None, setid_file=None, mode='train', transform=None, download=True, backend=None ) [source]

Implementation of Flowers dataset

Parameters

• data_file (str) – path to data file, can be set None if download is True. Default None, default data path: ~/.cache/paddle/dataset/flowers/

• label_file (str) – path to label file, can be set None if download is True. Default None, default data path: ~/.cache/paddle/dataset/flowers/

• setid_file (str) – path to subset index file, can be set None if download is True. Default None

• mode (str) – ‘train’, ‘valid’ or ‘test’ mode. Default ‘train’.

• transform (callable) – transform to perform on image, None for no transform.

• download (bool) – download dataset automatically if data_file is None. Default True

• backend (str, 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 paddle.vsion.get_image_backend , default backend is ‘pil’. Default: None.

Examples

from paddle.vision.datasets import Flowers

flowers = Flowers(mode='test')

for i in range(len(flowers)):
    sample = flowers[i]
    print(sample[0].size, sample[1])