Skip to main content

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.

Project description

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

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

License

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

albucore-0.0.15.tar.gz (11.5 kB view details)

Uploaded Source

Built Distribution

albucore-0.0.15-py3-none-any.whl (9.0 kB view details)

Uploaded Python 3

File details

Details for the file albucore-0.0.15.tar.gz.

File metadata

  • Download URL: albucore-0.0.15.tar.gz
  • Upload date:
  • Size: 11.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.8.18

File hashes

Hashes for albucore-0.0.15.tar.gz
Algorithm Hash digest
SHA256 a6d3042512cb0f06b2f0c3b77c8febae6098191c0f10e6160b64bf7f11e8328b
MD5 e99e49dbf7ebd05d3cfe22c7b4e0cd93
BLAKE2b-256 f5c8a5934c76b8b6a9faf220a4cd55dcbf9b44f298648ad9d1484c4e55bc2dc8

See more details on using hashes here.

File details

Details for the file albucore-0.0.15-py3-none-any.whl.

File metadata

  • Download URL: albucore-0.0.15-py3-none-any.whl
  • Upload date:
  • Size: 9.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.8.18

File hashes

Hashes for albucore-0.0.15-py3-none-any.whl
Algorithm Hash digest
SHA256 9e3e2112c510ef954c19a645fb859944b394f6b273b50c6b3db7d6812c2c06d0
MD5 3d7a6cdcf328aadb792032d32b94e490
BLAKE2b-256 23d91c44d7b76504779b66fafa58884a957c2f6039ed0589f0f262faab1088da

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page