ImageStackAlignator
Implementation of Google's Handheld Multi-Frame Super-Resolution algorithm (from Pixel 3 and Pixel 4 camera) (by kunzmi)
mlf-core
CPU and GPU deterministic and therefore fully reproducible machine learning pipelines using MLflow. (by mlf-core)
ImageStackAlignator | mlf-core | |
---|---|---|
1 | 3 | |
378 | 45 | |
- | - | |
0.0 | 0.0 | |
about 4 years ago | about 1 year ago | |
C# | Python | |
GNU General Public License v3.0 only | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ImageStackAlignator
Posts with mentions or reviews of ImageStackAlignator.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-05-31.
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[D] “Please Commit More Blatant Academic Fraud” (Blog post on problems in ML research by Jacob Buckman)
I was so frustrated when I tried my hand on reproducing the outlined steps on their paper on multi-frame super resolution. Other people like Michael Kunz said it had some errors too.
mlf-core
Posts with mentions or reviews of mlf-core.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-05-31.
-
[D] “Please Commit More Blatant Academic Fraud” (Blog post on problems in ML research by Jacob Buckman)
Link: https://github.com/mlf-core/mlf-core
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your ML workflow?
I am using mlf-core (Github: https://github.com/mlf-core/mlf-core) to make all of my projects fully CPU and GPU deterministic and reproducible. MLflow and Tensorboard allow me to explore my generated results interactively. Conda and Docker ensure a quick and reproducible runtime environment.
- Building an End-to-End Machine Learning Application From Idea to Deployment
What are some alternatives?
When comparing ImageStackAlignator and mlf-core you can also consider the following projects:
fake-news - Building a fake news detector from initial ideation to model deployment