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image unknown | label int8 0 7 | rotation_degrees float32 -25 25 | translate_x int8 -21 20 | translate_y int8 -17 16 | reflected bool 2
classes |
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End of preview. Expand in Data Studio
Transformed MNIST 48x48
MNIST images on a 48x48 canvas with extra margin. Classes 6 and 9 were removed. Each image received one reproducible random transform set: rotation, optional horizontal reflection, and a safe random translation that keeps the foreground away from the edge.
Splits
train: 48,133 examplestest: 8,033 examples- Labels: 0, 1, 2, 3, 4, 5, 7, 8
The label column uses contiguous IDs 0–7 with this mapping: 0->0, 1->1, 2->2, 3->3, 4->4, 5->5, 6->7, 7->8.
Features
image: grayscale 48x48 PNG byteslabel: contiguous class IDrotation_degrees,translate_x,translate_y,reflected: transform metadata
Load
from datasets import load_dataset, Image
ds = load_dataset("parquet", data_files={
"train": "data/train-00000-of-00001.parquet",
"test": "data/test-00000-of-00001.parquet",
})
ds = ds.cast_column("image", Image())
The original MNIST data was downloaded from the official MNIST mirror and filtered before transformation.
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