Documentation#
CleanVision automatically detects various issues in image datasets, such as images that are: (near) duplicates, blurry, over/under-exposed, etc. This data-centric AI package is designed as a quick first step for any computer vision project to find problems in your dataset, which you may want to address before applying machine learning.
Installation#
To install the latest stable version (recommended):
$ pip install cleanvision
To install the bleeding-edge developer version:
$ pip install git+https://github.com/cleanlab/cleanvision.git
Quickstart#
Using CleanVision to audit your image data is as simple as running the code below:
from cleanvision.imagelab import Imagelab
# Specify path to folder containing the image files in your dataset
imagelab = Imagelab(data_path="FOLDER_WITH_IMAGES/")
# Automatically check for a predefined list of issues within your dataset
imagelab.find_issues()
# Produce a neat report of the issues found in your dataset
imagelab.report()
CleanVision diagnoses many types of issues, but you can also check for only specific issues:
issue_types = {"light": {}, "blurry": {}}
imagelab.find_issues(issue_types)
# Produce a report with only the specified issue_types
imagelab.report(issue_types.keys())
More on how to get started with CleanVision: