timedcapture
a cython-based module to achieve on-time capture through V4L2
Science Score: 23.0%
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
Found 2 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
○Committers with academic emails
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (13.7%) to scientific vocabulary
Repository
a cython-based module to achieve on-time capture through V4L2
Basic Info
- Host: GitHub
- Owner: gwappa
- License: mit
- Language: Jupyter Notebook
- Default Branch: master
- Size: 929 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
timedcapture
a cython-based module to achieve on-time video capture through V4L2.
For a general usage, refer to USAGE.
Prerequisites
IMPORTANT NOTE: the current implementation only allows 16-bit grayscale acquisition. IMPORTANT NOTE: there is no functionality that controls the frame rate. Frame-capture timings must be controlled elsewhere, either using software or hardware timers.
- The library is tested on Ubuntu 18.04 LTS, but it is supposed to work on any Linux environment that runs V4L2.
- Please note that the library is optimized for cameras from ImagingSource.
By using devices from other manufacturers, you will not have control over functionalities such as:
- 1 microsecond-order exposure control (V4L2 only allows the order of 10 microseconds)
- auto-gain/manual-gain switch (the gain control will be totally manual- or auto-controlled)
- trigger modes (by default, only the free-running mode will be allowed)
- "strobe" output These settings must be configured elsewhere.
Installation
Requires Python >=3.6 to work.
For the time being, we only provide the source distribution on PyPI. You will need a working Cython and Numpy combination pre-installed.
bash
$ pip install numpy>=1.19 cython>=0.29 # or: "conda install numpy cython", in case you use Anaconda
$ pip install timedcapture
Alternatively, you can visit our releases page
and download the x86_64 binary wheel.
You can install it via:
bash
$ pip install timedcapture-<version...>.whl
License
2020 Keisuke Sehara, the MIT License.
You can cite timedcapture by using the DOI: https://doi.org/10.5281/zenodo.4459207
Owner
- Name: Keisuke Sehara
- Login: gwappa
- Kind: user
- Location: Tokyo, Japan
- Repositories: 7
- Profile: https://github.com/gwappa
a hard-core N.E.E.T. with some coding capabilities (C/C++, Java, Python, Rust) interested in automating chores without paying royalty.
GitHub Events
Total
Last Year
Committers
Last synced: over 3 years ago
All Time
- Total Commits: 22
- Total Committers: 1
- Avg Commits per committer: 22.0
- Development Distribution Score (DDS): 0.0
Top Committers
| Name | Commits | |
|---|---|---|
| Keisuke Sehara | k****a@g****m | 22 |
Issues and Pull Requests
Last synced: about 1 year ago
All Time
- Total issues: 0
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 0
- Total pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
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Packages
- Total packages: 1
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Total downloads:
- pypi 12 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 1
- Total maintainers: 1
pypi.org: timedcapture
a cython-based module to achieve on-time capture through V4L2.
- Homepage: https://github.com/gwappa/python-timedcapture
- Documentation: https://timedcapture.readthedocs.io/
- License: MIT
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Latest release: 0.3.2
published over 5 years ago
Rankings
Maintainers (1)
Dependencies
- numpy >=1.19