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tusen-ai
simpledet
Python2019–2019
tusen-ai / simpledet

simpledet

A Simple and Versatile Framework for Object Detection and Instance Recognition

2Distinct people
2Mentions
0Explicit recommenders
3.1KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

A Simple and Versatile Framework for Object Detection and Instance Recognition

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month2 dated mentions

Observed mentions: 2019-02-04 12:28:46 UTC to 2019-10-01 05:35:03 UTC.

012019-02-01 00:00:00 UTC to 2019-03-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsFeb 20192019-03-01 00:00:00 UTC to 2019-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-04-01 00:00:00 UTC to 2019-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-05-01 00:00:00 UTC to 2019-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-06-01 00:00:00 UTC to 2019-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJun 20192019-07-01 00:00:00 UTC to 2019-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-08-01 00:00:00 UTC to 2019-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-09-01 00:00:00 UTC to 2019-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-10-01 00:00:00 UTC to 2019-11-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsOct 2019

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Feb 20192019-02-01 00:00:00 UTC2019-03-01 00:00:00 UTC110
Mar 20192019-03-01 00:00:00 UTC2019-04-01 00:00:00 UTC000
Apr 20192019-04-01 00:00:00 UTC2019-05-01 00:00:00 UTC000
May 20192019-05-01 00:00:00 UTC2019-06-01 00:00:00 UTC000
Jun 20192019-06-01 00:00:00 UTC2019-07-01 00:00:00 UTC000
Jul 20192019-07-01 00:00:00 UTC2019-08-01 00:00:00 UTC000
Aug 20192019-08-01 00:00:00 UTC2019-09-01 00:00:00 UTC000
Sep 20192019-09-01 00:00:00 UTC2019-10-01 00:00:00 UTC000
Oct 20192019-10-01 00:00:00 UTC2019-11-01 00:00:00 UTC101

What Hacker News says

2 sources
Are you looking for advanced models that you can train on your data pretty much out-of-the-box or simple, easy-to-read models that help you learn the underlying concepts? If it's the first case, what you want to do is find the best GitHub repos for the task(s) you are trying to do. Make sure the GitHub repo has a model zoo and good support and start from there. In CV, if you are trying to do high-end work, the repos to check out are: - https://github.com/facebookresearch/maskrcnn-benchmark (don't be misled by the name, it has support for lots of the high-end modern CV models) - https://github.com/open-mmlab/mmdetection - https://github.com/TuSimple/simpledet (haven't explored this one as much, but it looks very solid) If you want easy-to-read code for non-trivial tasks, I would suggest taking a look at Gluon (GluonCV - https://gluon-cv.mx
Read the rest
net.io/ and GluonNLP - https://gluon-nlp.mxnet.io/). I haven't worked much with the fast.ai library, but that's probably also a good suggestion.
In Tensorflow 2.0

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