cleanvision
Automatically find issues in image datasets and practice data-centric computer vision. (by cleanlab)
| task-amenability | cleanvision | |
|---|---|---|
| 2 | 4 | |
| 13 | 925 | |
| - | 1.6% | |
| 1.3 | 7.3 | |
| almost 1 year ago | 16 days ago | |
| Python | Python | |
| - | GNU Affero General Public License v3.0 |
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.
task-amenability
Posts with mentions or reviews of task-amenability.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-22.
-
[D] Is accurately estimating image quality even possible?
The repo: https://github.com/s-sd/task-amenability
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Data Valuation using Reinforcement Learning
As a sidenote, we have been working on an approach for data valuation which does not require a clean validation set. You can access the paper and code and try that out if you'd like.
cleanvision
Posts with mentions or reviews of cleanvision.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-04-22.
-
[D] Is accurately estimating image quality even possible?
Github: https://github.com/cleanlab/cleanvision Blogpost: https://cleanlab.ai/blog/cleanvision/
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How to label augmented images for training YOLO algorithm?
Before you start augmentations you could also use something like CleanVision to examine your image data and see if there are any recurring problems like (near) duplicates, blurry images, etc. It doesn't do anything for you, but it might be good to get an idea for the images you are working with.
- CleanVision: Audit your Image Data for better Computer Vision
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[P] CleanVision: Audit your Image Data for better Computer Vision
Github: https://github.com/cleanlab/cleanvision
What are some alternatives?
When comparing task-amenability and cleanvision you can also consider the following projects:
imgaug - Image augmentation for machine learning experiments.
amplify - Bacalhau Amplify: automatic enrichment, enhancement, and explanation of your data
cleanvision-examples - Notebooks demonstrating example applications of the cleanvision library
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
improved-aesthetic-predictor - CLIP+MLP Aesthetic Score Predictor