imutils vs Pillow

Side-by-side — pricing, strengths, tradeoffs, and fit.

imutils

Simplify image processing tasks with OpenCV and Python.

Pillow

Friendly PIL fork for image processing in Python

At a glance

Open SourceFree Tier
◌ Declining·From $0
Open SourceFree Tier
● Established·From $0

Overview

One-liner

Simplify image processing tasks with OpenCV and Python.

One-liner

Friendly PIL fork for image processing in Python

Maturity

Declining

Maturity

Established

Open source

✓ Yes

Open source

✓ Yes

Pricing

Free tier

✓ Available

Open source — free to use

Free tier

✓ Available

Open source — free to use

Starts at

$0

Starts at

$0

Model

Flat rate

Model

Flat rate

Enterprise

✕ None

Enterprise

✕ None

Best for

✓ Best for

Python developers working on small-scale image processing tasks who need a lightweight library.
Students and educators teaching basic computer vision techniques using OpenCV and Python.

✓ Best for

Developers working on Python-based image processing tasks who need a comprehensive library with good performance and extensive file format support.
Data scientists preprocessing images for machine learning models.

Not ideal for

✕ Not for

Projects requiring advanced or specialized image processing features beyond the scope of imutils.
Large-scale applications where performance optimization is critical.

✕ Not for

Projects requiring real-time video processing, as Pillow is primarily designed for static images
Applications that require heavy GPU acceleration for image processing

Strengths

↑ Strengths

Simplified image processing operations with OpenCV.
Convenience functions for common tasks like translation, rotation, and resizing.
Integration with Matplotlib for displaying images.

↑ Strengths

Supports various image file formats
Efficient and easy-to-use API for image processing tasks
Extensive documentation and community support

Weaknesses

↓ Weaknesses

Limited to Python and OpenCV, lacking support for other languages or image processing libraries
Small community and limited third-party support
No official maintenance or updates since 2019
Documentation is sparse and lacks comprehensive examples

↓ Weaknesses

Limited support for advanced image processing features
Performance bottlenecks with large images or datasets
Documentation lacks depth for complex use cases
Full imutils profile →Full Pillow profile →