caer 1.9.1

Modern Computer Vision on the Fly. Caer simplifies the training and visualization of Computer Vision models using modern best practices

Caer - Modern Computer Vision on the Fly

A Computer Vision library in Python with powerful image and video processing operations. Caer is a set of utility functions designed to help speed up your Computer Vision workflow. Functions inside caer will help reduce the number of calculation calls your code makes, ultimately making it neat, concise and readable.

Install

See the Caer Installation guide for detailed installation instructions including building from source.

Currently, caer supports releases of Python 3.6 onwards; Python 2 is not supported (nor recommended). To install the current release:

$ pip install caer

Getting Started

Example

>> import caer

# Load a standard 640x427 test image that ships out-of-the-box with caer
>> sunrise = caer.data.sunrise(rgb=True)

# Resize the image to 500x500 while MAINTAINING aspect ratio
>> resized = caer.resize(sunrise, target_size=(500,500), keep_aspect_ratio=True)

For more examples, see the Caer demos.

Resources

• PyPi
• Documentation
• Issue tracking

Contributing

We appreciate all contributions. If you plan to contribute new features, utility functions, or extensions to the core, please go through our [Contribution Guidelines][contributing]. By participating, you are expected to uphold the [Code of Conduct][coc].

To contribute, start working through the caer codebase, read the [Documentation][docs], navigate to the [Issues][issues] tab and start looking through interesting issues.

Current contributors can be viewed either from the [Contributors][contributors] file or by using the caer.__contributors__ command.

All Caer wheels on PyPi are MIT-licensed