Rotation Equivariance Testing Dataset

A dataset generator for testing rotation equivariance in neural networks, specifically focusing on segmentation tasks using simple geometric shapes.

Dataset Details

Image Size: 128 x 128 pixels
Number of Samples: 100 images
Rotation Range: 0° to 360° (uniformly distributed)
Shape Type: Ellipses with major axis 40 pixels and minor axis 20 pixels, Arrows

python generate.py

Name		Name	Last commit message	Last commit date
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data		data
README.md		README.md
generate.py		generate.py
requirements.txt		requirements.txt