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Create ~10 test images per shape per shape parameter. Start with the generation script of the Simple shapes image dataset to create these test images.
Shapes are:triangle and circle (2 in total)
Shape parameters are:
for circles: size (radius) and gray-scale contrast (2 in total)
for triangles: size ("radius"), rotation angle and gray-scale contrast (3 in total)
Gray-scale contrast is defined as the difference between BG and FG colours
For each one of 10 radii sizes: (10 images with different rotation angles and for each rotation angle:) 10 images with varying gray-scale contrast.
I'm still quite curious about XAI's response to the transition of shapes from a triangle to a circle, which was a topic mentioned quite long time ago. But I understand that it is a bit difficult to define this kind of transition quantitatively. If we have extra time, this topic maybe a good candidate as well.
Create ~10 test images per shape per shape parameter. Start with the generation script of the Simple shapes image dataset to create these test images.
Shapes are: triangle and circle (2 in total)
Shape parameters are:
Gray-scale contrast is defined as the difference between BG and FG colours
For each one of 10 radii sizes: (10 images with different rotation angles and for each rotation angle:) 10 images with varying gray-scale contrast.
Total: 100 circles and 1000 triangles.
The output of this issue should be:
A generation script for the images with functions per shape with all parameters. Stored at the dataset_preparation folder for Geometric shapes: generate_geometric_shapes4research.ipynb
Store the images in .npz file(s) - the same format as the trained model's data on Surfdrive.
Stems from #445 and dianna-ai/dianna-exploration#187 (see for Practicalities).
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