--- title: datagenerator keywords: fastai sidebar: home_sidebar summary: "API details." description: "API details." nb_path: "nbs/02_datagenerator.ipynb" ---
img_sz_list = ImageSizeList(None)
img_sz_list.get_size()
class LabelEncoder:
def __init__(self, labels):
self.labels = labels
self.label_to_idx = {label: i for i, label in enumerate(self.labels)}
def encode(self, label):
return self.label_to_idx[label]
ds = Dataset(cat_dog_path, image_size=[(28, 28), (32, 32), (64, 64)])
# ds = Dataset('/data/aniket/tiny-imagenet/data/tiny-imagenet-200/train')
# ds = Dataset('/data/aniket/tiny-imagenet/data/tiny-imagenet-200/train', image_size=(224,224))
# return glob(f'{path}/*/images/*')
# def get_label(path):
# return path.split('/')[-3]
# ds.update_component('get_label', get_label)
for e in ds.generator(True):
print(e[0].dtype, e[1])
break
dl = ds.get_tf_dataset()
for e in dl.take(1):
print(e[0].shape)