https://github.com/babots-project/behavioural_flagging
Python re-implementation of Salvador et al. 2014 behavioural flagging algo.
Science Score: 26.0%
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Low similarity (3.2%) to scientific vocabulary
Repository
Python re-implementation of Salvador et al. 2014 behavioural flagging algo.
Basic Info
- Host: GitHub
- Owner: BABots-Project
- Language: Python
- Default Branch: main
- Size: 4.88 KB
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- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Behavioural Flagging
The data used is from Broekmans et al 2016 (https://datadryad.org/stash/dataset/doi:10.5061/dryad.t0m6p)
The behaviour of a worm is characterised by crawls alternated by reorientations as per Salvador et al 2014. The current implementation allows to recognize the reorientations: - omegas, where the solidity of the worm is used - reversals, an adaptation of Hardaker's method to detect reversal events - pauses, characterised by a significant decrease in velocity (<=1/3 of the average) - pirouettes, characterised by an omega followed by a reversal within 0.5s
Next step is the implementation of the crawl recognition. The algorithm will produce a final list of all states as they occur starting from the images and centroid coordinates of a tracked worm.
Owner
- Name: BABots-Project
- Login: BABots-Project
- Kind: organization
- Repositories: 1
- Profile: https://github.com/BABots-Project
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