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Project description
CIFAR 10 Dataset Library
This library was created to allow an easy usage of CIFAR 10 DATA. This is a wrapper around the instructions givn on the CIFAR 10 site
Installation
pip3 install cifar10
Sample Usage
import cifar10
for image, label in cifar10.data_batch_generator():
image # numpy array of an image, which is of shape 32 x 32 x 3
label # integer value of the image label
API
data_batch_generator
Returns a generator of each image and label pair for data batch
data_batch_generator(cache_location: str=".") -> Iterator[Tuple[np.array, int]]
parameters
cache_location
(default: library folder location): where to cache the cifar10 data
test_batch_generator
Returns a generator of each image and label pair for test batch
test_batch_generator(cache_location: str=".") -> Iterator[Tuple[np.array, int]]
parameters
cache_location
(default: library folder location): where to cache the cifar10 data
meta
Returns the raw meta file
meta(cache_location: str=".") -> Dict[bytes, Any]
parameters
cache_location
(default: library folder location): where to cache the cifar10 data
image_label_map
Returns the raw meta file
image_label_map(cache_location: str=".") -> Dict[int, str]
parameters
cache_location
(default: library folder location): where to cache the cifar10 data
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