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Yashparkar06/Fruit-Ripeness

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This project utilizes image processing and machine learning techniques to determine the ripeness level of various fruits. By analyzing specific features like color, texture, and shape, the system provides an accurate assessment of how ripe a fruit is.

active 2025-01-14 → 2025-01-14 (UTC)

Complete coverage28,070 / 28,070 hourly files (100%) · 2 absent upstream2023-08-15 → 2026-10-27 (UTC)
Events
5
Pushes
2
Pull requests
0
Issues
0
Stars
1
Forks
0

Activity over time

Daily event counts in the loaded window

Line chart, 1 days from 2025-01-14 to 2025-01-14. Pushes: 2 total, peak 2 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: 1 total, peak 1 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Top contributors

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

ContributorContributionsPushesPRsComments
Yashparkar062200

Recent activity

Latest issues, pull requests and releases

No issue or PR events — this repo's activity is pushes only.

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 1 stars here means stars gained during the window, not the repo's star count.