Science Score: 26.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
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○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (8.6%) to scientific vocabulary
Last synced: 10 months ago
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Repository
nothing to do
Basic Info
- Host: GitHub
- Owner: j29271ustinisAaC
- License: mit
- Language: Jupyter Notebook
- Default Branch: main
- Size: 212 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Created over 1 year ago
· Last pushed 10 months ago
Metadata Files
Readme
Changelog
Contributing
Funding
License
Code of conduct
Citation
Codeowners
Security
Authors
Notice
Dco
README
To actually get this beast to run on your computer, you'll probably have to
edit some of the matlab files in the config/ subdirectory.
(1) config/datapath.m should return the path where you have your videos stored.
The path should point to a directory which includes a subdirectory for each video.
E.g. $(datapath)/tiger2/.
Each subdirectory should contain files with ground truth labelings and images similar
to what MIL-Track uses.
As an example, see my track-data.zip file.
(2) cluster_ctl is called like so cluster_ctl('on',...) or cluster_ctl('off',...)
to enable or disable the matlab pool. I have three pools, with different characteristics,
available to me so this function, heuristically, selects the best one. Depending on what
type of MATLAB pools you have, you'll need to rewrite this function. The simplest option
would be to call "matlabpool open" when called with "on" and "matlabpool close" when
called with "off".
(3) You should be able to compile by simplying calling "compile.m". I've tested this on Linux
and it should work on other OSs... I welcome patches.
(4) config/cfg.m : lets you stitch many of the parameters of the tracker. Of particular
interest will be the option 'tmp_dir'. You'll want to point this to an empty directory
which is writable. It is used for caching results.
Then, you "should" be able to run it with a command similar to the following:
addpath(genpath('.')); matlab_init('coke11'); track = track_online('coke11');
Alternatively, you might just use track_tbd('coke11'); which doesn't do any learning (after
the first frame) or use a motion model. It is much faster and still performs quite well.
Owner
- Login: j29271ustinisAaC
- Kind: user
- Repositories: 1
- Profile: https://github.com/j29271ustinisAaC
GitHub Events
Total
- Push event: 966
- Create event: 2
Last Year
- Push event: 966
- Create event: 2
Dependencies
.github/workflows/ci-plus.yml
actions
- actions/checkout v3 composite
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Cargo.lock
cargo
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Cargo.toml
cargo
api-gateway-microservice/pom.xml
maven
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API Basejumps/File-Metadata-Microservice/package.json
npm
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Dockerfile
docker
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NSMusicS-Electron/Dockerfile
docker
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docker
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Gopkg.lock
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android/build.gradle
maven
FSH.StarterKit.nuspec
nuget
Gemfile
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Gemfile.lock
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DESCRIPTION
cran
- base64enc * imports
- glue * imports
- googleAuthR * imports
- jsonlite * imports
- tibble * imports
.github/workflows/build-openwrt.yml
actions
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ROS/Dockerfile
docker
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bower.json
bower
docker-compose-builder.yml
docker
docker-compose.yml
docker
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go.sum
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build.gradle
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maven
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pom.xml
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npm
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package-lock.json
npm
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package.json
npm
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composer.json
packagist
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pubspec.lock
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pubspec.yaml
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backend/Pipfile
pypi
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project/Sprint4/requirements-dev.txt
pypi
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pyproject.toml
pypi
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requirement.txt
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requirements.txt
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setup.py
pypi
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