Package: cleanvision
CleanVision automatically detects potential issues in image datasets like images that are: blurry, under/over-exposed, (near) duplicates, etc.
This data-centric AI package is a quick first step for any computer vision project to find problems in the dataset, which you want to address before applying machine learning.
CleanVision is super simple -- run the same couple lines of Python code to audit any image dataset!InstallationpipinstallcleanvisionQuickstartDownload an example dataset (optional). Or just use any collection of image files you have.wget-nc'https://cleanlab-public.s3.amazonaws.com/CleanVision/image_files.zip'Run CleanVision to audit the images.fromcleanvisionimportImagelab# Specify path to folder containing the image files in your datasetimagelab=Imagelab(data_path="FOLDER_WITH_IMAGES/")# Automatically check for a predefined list of issues within your datasetimagelab.find_issues()# Produce a neat report of the issues found in your datasetimagelab.report()CleanVision diagnoses many types of issues, but you can also check for only specific issues.issue_types={"dark":{},"blurry":{}}imagelab.find_issues(issue_types=issue_types)# Produce a report with only the specified issue_typesimagelab.report(issue_types=issue_types)More resources on how to use CleanVisionTutorialRun CleanVision on a HuggingFace datasetRun CleanVision on a Torchvision datasetExample scriptthat can be run with:python examples/run.py --path <FOLDER_WITH_IMAGES>Additional example notebooksDocumentationBlog PostFAQCleanyour data for better ComputerVisionThe quality of machine learning models hinges on the quality of the data used to train them, but it is hard to manually identify all of the low-quality data in a big dataset. CleanVision helps you automatically identify common types of data issues lurking in image datasets.This package currently detects issues in the raw images themselves, making it a useful tool for any computer vision
task such as: classification, segmentation, object detection, pose estimation, keypoint detection,generative modeling, etc.
To detect issues in the labels of your image data, you can instead
use thecleanlabpackage.In any collection of image files (mostformatssupported), CleanVision can detect the following types of issues:Issue TypeDescriptionIssue KeyExample1Exact DuplicatesImages that are identical to each otherexact_duplicates2Near DuplicatesImages that are visually almost identicalnear_duplicates3BlurryImages where details are fuzzy (out of focus)blurry4Low InformationImages lacking content (little entropy in pixel values)low_information5DarkIrregularly dark images (underexposed)dark6LightIrregularly bright images (overexposed)light7GrayscaleImages lacking colorgrayscale8Odd Aspect RatioImages with an unusual aspect ratio (overly skinny/wide)odd_aspect_ratio9Odd SizeImages that are abnormally large or small compared to the rest of the datasetodd_sizeCleanVision supports Linux, macOS, and Windows and runs on Python 3.7+.Join our communityThe best place to learn isour Slack community. Join the discussion there to see how
folks are using this library, discuss upcoming features, or ask for private support.Need professional help with CleanVision?  Join our#help Slack channeland message us there, or reach out via email:team@cleanlab.aiInterested in contributing? See thecontributing guide. An easy starting point is to
considerissuesmarkedgood first issueor
simply reach out inSlack. We welcome your help building a standard open-source library
for data-centric computer vision!Ready to start adding your own code? See thedevelopment guide.Have an issue?Search existing issuesorsubmit a new issue.Have ideas for the future of data-centric computer vision? Check
outour active/planned Projects and what we could use your help with.LicenseCopyright (c) 2022 Cleanlab Inc.cleanvision is free software: you can redistribute it and/or modify it under the terms of the GNU Affero General Public
License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later
version.cleanvision is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied
warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.SeeGNU Affero General Public LICENSEfor details.Commercial licensing is available for enterprise teams that want to use CleanVision in production workflows, but are unable to open-source their codeas is required by the current license. Please email us:team@cleanlab.ai