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active 2025-01-292025-01-31 (UTC)

Complete coverage26,735 / 26,735 hourly files (100%) · 2 absent upstream2023-08-152026-09-01 (UTC)
Events
9
Pushes
0
Pull requests
0
Issues
7
Stars
0
Forks
0

Activity over time

Daily event counts in the loaded window

Line chart, 3 days from 2025-01-29 to 2025-01-31. Pushes: 0 total, peak 0 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 7 total, peak 7 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 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
Cetykon7000

Recent activity

Latest issues, pull requests and releases

  • Issue#28Cetykon2025-01-31 03:56
    As a user I want the app to tell me if I am fallowing an unfamiliar path during a workout through my headphones, so that I don't need to keep doing the exercise incorrectly.
  • Issue#27Cetykon2025-01-31 03:49
    As a user I want the app to give me corrected feedback after it detects a wrong bar path or direction while doing a workout, that I know what to adjust.
  • Issue#26Cetykon2025-01-31 03:49
    As a user I want the app to detect if I am fallowing an unfamiliar bar path or direction while doing my workout, so that I can make adjustments on my next set.
  • Issue#25Cetykon2025-01-31 03:39
    As a user I want the app to be design around taking different body proportions into account, so that I know that it is giving me the correct feedback.
  • Issue#24Cetykon2025-01-31 03:39
    As a user I want the application to take my body proportions so that I know the application is taking this into account when giving me feedback.
  • Issue#1Cetykon2025-01-31 03:28
    As a user I want the app to be able to identify the workout that I am doing so that I don't need to use the touch interface
  • Issue#22Cetykon2025-01-31 03:24
    As a user I want the app to be equipped with a machine learning model trained to identify different workout, so that it can identify them.

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.