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Alexandre-Delplanque/HerdNet

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Demo for HerdNet repository. "From Crowd to Herd Counting: How to Precisely Detect and Count African Mammals using Aerial Imagery and Deep Learning?"

active 2023-08-202026-04-08 (UTC)

Complete coverage26,616 / 26,616 hourly files (100%) · 2 absent upstream2023-08-152026-08-27 (UTC)
Events
146
Pushes
19
Pull requests
8
Issues
17
Stars
33
Forks
8

Activity over time

Daily event counts in the loaded window

Line chart, 963 days from 2023-08-20 to 2026-04-08. Pushes: 19 total, peak 4 in a day. Pull requests: 8 total, peak 2 in a day. Issues: 17 total, peak 2 in a day. Comments: 48 total, peak 5 in a day. Stars: 33 total, peak 2 in a day.

  • Pushes
  • Pull requests
  • Issues
  • Comments
  • Stars

Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.

Top contributors

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

ContributorContributionsPushesPRsComments
Alexandre-Delplanque5618525
idchacon287004
NIUYIHAHA6005
sunxiaoyang016005
cwinkelmann4003
FadelMamar4012
xiaotongtongxue3002
eebowen2000
tarunsharma12002
simbamangu2010
sfoucher1010

Recent activity

Latest issues, pull requests and releases

  • Issue#18Alexandre-Delplanque2026-04-08 11:32
    Clarification on correct setup for training HerdNet from DLA backbone (down_ratio, FIDT, Stitcher)
  • Issue#18Alexandre-Delplanque2025-11-03 11:13
    Clarification on correct setup for training HerdNet from DLA backbone (down_ratio, FIDT, Stitcher)
  • Issue#17simbamangu2025-10-03 07:17
    Model download links not working
  • Issue comment#14FadelMamar2025-04-02 18:51
    Single class detection is yielding strange results
  • Issue comment#14Alexandre-Delplanque2025-04-02 08:36
    Single class detection is yielding strange results
  • Issue comment#13tarunsharma12025-04-01 23:01
    Discrepancy in model training results
  • Issue comment#13idchacon282025-04-01 22:18
    Discrepancy in model training results
  • Issue comment#13tarunsharma12025-04-01 21:47
    Discrepancy in model training results
  • Issue comment#14FadelMamar2025-03-31 09:42
    Single class detection is yielding strange results
  • Issue comment#13Alexandre-Delplanque2025-03-25 14:48
    Discrepancy in model training results
  • Issue#13Alexandre-Delplanque2025-03-25 14:48
    Discrepancy in model training results
  • Issue comment#13idchacon282025-03-25 14:04
    Discrepancy in model training results
  • Issue comment#14Alexandre-Delplanque2025-03-25 08:03
    Single class detection is yielding strange results
  • Issue comment#13Alexandre-Delplanque2025-03-24 16:38
    Discrepancy in model training results
  • Issue comment#13idchacon282025-03-24 16:11
    Discrepancy in model training results
  • Pull request#15FadelMamar2025-03-19 13:54
  • Issue#14FadelMamar2025-03-19 13:31
    Single class detection is yielding strange results
  • Issue comment#13Alexandre-Delplanque2025-03-18 15:16
    Discrepancy in model training results
  • Issue comment#13Alexandre-Delplanque2025-03-12 10:10
    Discrepancy in model training results
  • Issue#13idchacon282025-03-06 22:17
    Discrepancy in model training results
  • Issue comment#12idchacon282025-03-04 15:49
    Request for Loss Cross Entropy Weights for HerdNet General Dataset
  • Issue#12idchacon282025-03-04 15:49
    Request for Loss Cross Entropy Weights for HerdNet General Dataset
  • Issue#12idchacon282025-03-04 15:18
    Request for Loss Cross Entropy Weights for HerdNet General Dataset
  • Issue comment#11NIUYIHAHA2025-02-10 10:38
    About Image Cropping
  • Issue comment#11NIUYIHAHA2025-02-10 10:38
    About Image Cropping

Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 33 stars here means stars gained during the window, not the repo's star count.