synthetic datasets for benchmarking AI and machine learning
# Synthetic Datasets
pip install synthetic-datasets
A generator of square images, by default 64x64, with static noise and a circle
with noisy pixels in the image at a random location and with a random size.
Each result from the generator is a square numpy matrix of type float32
from synthetic_datasets import NoiseCircle
nc = NoiseCircle(batch_size=32, dim=64)
for samples, labels in nc:
// samples is a (32, 64, 64) numpy array of noise circle images
// labels is a dict with three keys, "X", "Y", and "R".
// These represent the X, Y, and RADIUS (in pixels) of the circle in the image.
// Each key holds a numpy array of shape (32,)
## More info
- A Toronto AI initiative
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