albucore 0.0.1

A high-performance image processing library designed to optimize and extend the Albumentations library with specialized functions for advanced image transformations. Perfect for developers working in computer vision who require efficient and scalable image augmentation.

Albucore

Albucore is a high-performance image processing library designed to optimize operations on images using Python and OpenCV, building upon the foundations laid by the popular Albumentations library. It offers specialized optimizations for different image data types and aims to provide faster processing times through efficient algorithm implementations.

Features

• Optimized image multiplication operations for both uint8 and float32 data types.
• Support for single-channel and multi-channel images.
• Custom decorators to manage channel dimensions and output constraints.

Installation

Install Albucore using pip:

pip install -U albucore

Example

Here's how you can use Albucore to multiply an image by a constant or a vector:

import cv2
import numpy as np
from albucore import multiply

# Load an image
img = cv2.imread('path_to_your_image.jpg')

# Multiply by a constant
multiplied_image = multiply(img, 1.5)

# Multiply by a vector
multiplier = [1.5, 1.2, 0.9]  # Different multiplier for each channel
multiplied_image = multiply(img, multiplier)

Benchmarks

Benchmark Results for 1000 Images of float32 Type (256, 256, 1)

	albucore	opencv	numpy
MultiplyConstant	12925 ± 1237	10963 ± 1053	14040 ± 2063
MultiplyVector	3832 ± 512	10824 ± 1005	8986 ± 511

Benchmark Results for 1000 Images of uint8 Type (256, 256, 1)

	albucore	opencv	numpy
MultiplyConstant	24131 ± 1129	11622 ± 175	6969 ± 643
MultiplyVector	24279 ± 908	11756 ± 152	6936 ± 408

Albucore provides significant performance improvements for image processing tasks. Here are some benchmark results comparing Albucore with OpenCV and Numpy:

For more detailed benchmark results, including other configurations and data types, refer to the Benchmark.md in the repository.

License

Distributed under the MIT License. See LICENSE for more information.