facebookresearch / pytorch3d
PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
Summary
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| Main Code: 36,604 LOC (281 files) = PY (45%) + H (18%) + CU (14%) + CPP (10%) + CUH (6%) + JS (1%) + CSS (1%) + YAML (<1%) + BASH (<1%) + CFG (<1%) Secondary code: Test: 25,994 LOC (135); Generated: 0 LOC (0); Build & Deploy: 662 LOC (18); Other: 2,016 LOC (19); |
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| Duplication: 18% | |||
| File Size: 4% long (>1000 LOC), 37% short (<= 200 LOC) | |||
| Unit Size: 23% long (>100 LOC), 41% short (<= 10 LOC) | |||
| Conditional Complexity: 11% complex (McCabe index > 50), 52% simple (McCabe index <= 5) | |||
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Logical Component Decomposition: primary (25 components) | ||
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2 years 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
42 files |
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Latest commit date: 2022-01-24
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18
commits
(30 days)
2
contributors
(30 days) |
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