CAREamics/careamics
A deep-learning library for denoising images using Noise2Void and friends (CARE, PN2V, HDN etc.), with a focus on user-experience and documentation.)
This helps researchers, scientists, and imaging specialists clean up noisy microscopy images without needing perfectly clean reference images. You input your raw, noisy image data, and it outputs a clearer, denoised version, making features easier to analyze. It's designed for anyone working with biological or materials science imaging who needs to improve image quality for better quantification or visualization.
126 stars. Available on PyPI.
Use this if you are a scientist or researcher working with microscopy images and need to remove noise from your data using advanced deep learning methods like Noise2Void, particularly if you prefer a PyTorch-based solution.
Not ideal if you need to denoise images from a different domain like satellite imagery or consumer photos, or if you prefer a TensorFlow-based solution.
Stars
126
Forks
20
Language
Python
License
BSD-3-Clause
Category
Last pushed
Mar 13, 2026
Commits (30d)
0
Dependencies
17
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