benchmark image dataset collection and preprocessing
Benchmark Image Dataset Collection And Preprocessing
Image datasets incorporated so far
MNIST dataset and its variants - 12000 train, 50000 test
- MB: MNIST basic dataset
- MBI: MNIST background image - A patch from a black and white image was used as the background for the digit image
- MDRBI: MNIST digits with rotation and background image - The perturbations used in MRD and MBI were combined.
- MRB: MNIST random background - A random background was inserted in the digit image
- MRD: MNIST rotated digits - The digits were rotated by an angle generated uniformly between 0 and 360 radians.
CONVEX dataset - 8000 train, 50000 test
Usage of the package
download the datasets
Download the datasets and put the files under the root directory of your project as shown in the following picture.
Load the datasets
# import the loader tool from bidcap.utils.loader import ImagesetLoader # import mb. Pass the dataset name described above as the first parameter data = ImagesetLoader.load('mb') # training images data.train['images'] # training labels data.train['labels'] # test images data.test['images'] # test labels data.test['labels']
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