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Refactor pipeline to use grain crop dictionaries #1022
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…ti class & subgrains
…mask required bool. Tested in debugger.
…2] >= 2, shape[1]==shape[2]
…rainCrops. Locally debugged working
Proposed solution to the data frame issue
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Its that or split into separate files. I'm ambivalent as to the preferred solution as I don't use the output but consideration for end users should be given. Whilst data management, manipulation, summarisation and plotting are, in my view, core skills for researchers these days experience levels vary widely and I don't know what would be easiest. |
Are we aiming to include this refactoring in |
cropped_images, cropped_masks, bboxs = prep_arrays(image, grains_mask, pad_width) | ||
n_grains = len(cropped_images) | ||
img_base = np.zeros_like(image) | ||
# cropped_images, cropped_masks, bboxs = prep_arrays(image, grains_mask, pad_width) |
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(continued from default config) or need to be padded here otherwise the 3x3 convolutions will not work
Co-authored-by: Neil Shephard <[email protected]>
… into SylviaWhittle/grain_restructure
… into SylviaWhittle/grain_restructure
… doesnt add to crops dictionary
…of disordered tracing, add vetted crops plot in plottingdictionary.yaml
… into SylviaWhittle/grain_restructure
… into SylviaWhittle/grain_restructure
This is a draft PR and documentation / tests will be added before full PR is made
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