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felipeverones/yololit-RDD

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Este aplicativo utiliza modelos de deep learning YOLOv8x e YOLOv9e para detectar danos em pavimentos asfálticos. Ele foi desenvolvido como parte do meu Trabalho de Conclusão de Curso e oferece várias funcionalidades, incluindo detecção em tempo real, detecção em imagens, vídeos e captura de tela.

active 2024-09-02 → 2024-09-02 (UTC)

Complete coverage27,993 / 27,993 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-10-24 (UTC)
Events
5
Pushes
1
Pull requests
0
Issues
0
Stars
0
Forks
0

Activity over time

Daily event counts in the loaded window

Line chart, 1 days from 2024-09-02 to 2024-09-02. Pushes: 1 total, peak 1 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.

  • Pushes
  • Pull requests
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Top contributors

Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity

ContributorContributionsPushesPRsComments
felipeverones1100

Recent activity

Latest issues, pull requests and releases

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.