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This project will develop a model that can accurately interpret ASL gestures. We will create an application where users can interact in real-time and receive feedback on the gestures they make. The model will predict what letter is being signed in real-time. We plan on recognizing entire words; for now, the project will focus on the ASL alphabet.

active 2023-09-192024-04-18 (UTC)

Complete coverage26,582 / 26,582 hourly files (100%) · 2 absent upstream2023-08-152026-08-26 (UTC)
Events
169
Pushes
106
Pull requests
5
Issues
0
Stars
2
Forks
3

Activity over time

Daily event counts in the loaded window

Line chart, 213 days from 2023-09-19 to 2024-04-18. Pushes: 106 total, peak 15 in a day. Pull requests: 5 total, peak 3 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 2 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
iaggarwal1515100
joshkabloomy212100
pcsom121200
anthonyvnguyen10640
abalakrishnan16600
vngonugondla4400
reedashimaz3300
NikxTricks3210
SvabhuG1100

Recent activity

Latest issues, pull requests and releases

  • Pull request#3NikxTricks2023-09-27 00:31
  • Pull request#2anthonyvnguyen2023-09-27 00:11
  • Pull request#2anthonyvnguyen2023-09-27 00:10
  • Pull request#1anthonyvnguyen2023-09-26 23:18
  • Pull request#1anthonyvnguyen2023-09-26 23:17

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 2 stars here means stars gained during the window, not the repo's star count.