aws-samples / amazon-rekognition-video-analyzer
A working prototype for capturing frames off of a live MJPEG video stream, identifying objects in near real-time using deep learning, and triggering actions based on an objects watch list.
Summary
     |
|||
| Main Code: 11,384 LOC (14 files) = JS (88%) + PY (5%) + YAML (3%) + CSS (1%) + HTML (<1%) + TXT (<1%) + CFG (<1%) Secondary code: Test: 0 LOC (0); Generated: 0 LOC (0); Build & Deploy: 0 LOC (0); Other: 307 LOC (5); |
|||
| Duplication: 3% | |||
| File Size: 88% long (>1000 LOC), 5% short (<= 200 LOC) | |||
| Unit Size: 11% long (>100 LOC), 42% short (<= 10 LOC) | |||
| Conditional Complexity: 12% complex (McCabe index > 50), 42% simple (McCabe index <= 5) | |||
|
|
Logical Component Decomposition: primary (8 components) | ||
|
|
4 years, 7 months old
|
||
|
|
0% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits. |
||
| Goals: Keep the system simple and easy to change (4) | |||
|
Features of interest:
TODOs
1 file |
|||
Latest commit date: 2020-05-04
|
0
commits
(30 days)
0
contributors
(30 days) |
|