aws-samples / annotate-medical-images-in-dicom-server-and-build-ml-models-on-amazon-sagemaker
Summary
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| Main Code: 2,499 LOC (14 files) = YAML (33%) + CSS (33%) + HTML (14%) + JS (13%) + PY (5%) Secondary code: Test: 5 LOC (1); Generated: 0 LOC (0); Build & Deploy: 126 LOC (5); Other: 934 LOC (11); |
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| Duplication: 4% | |||
| File Size: 0% long (>1000 LOC), 13% short (<= 200 LOC) | |||
| Unit Size: 37% long (>100 LOC), 26% short (<= 10 LOC) | |||
| Conditional Complexity: 0% complex (McCabe index > 50), 79% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (8 components) | ||
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1 year, 2 months old
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0% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits. |
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| Goals: Keep the system simple and easy to change (4) | |||
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Features of interest:
TODOs
1 file |
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Latest commit date: 2021-08-26
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