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cv2-helper

cv2-helper is a Python library designed to make using OpenCV friendlier, faster, and more intuitive. It is especially built for developers, researchers, and students who need to run behavioral tests, debug pipelines, and visualize results in computer vision projects without writing repetitive setup code.

In addition to simplifying native functions, it includes new functionalities and advanced image processing algorithms fully compatible with OpenCV data structures (numpy.ndarray).

Key Features

  • Simplified Visualization: Forget about combining cv2.imshow, cv2.waitKey, and cv2.destroyAllWindows constantly; visualize images in a single line.

  • Quick Behavioral Testing: Ideal tools for agile prototyping and visual debugging of image processing pipelines.

  • Extended Algorithms & Utilities: Additional functions compatible with OpenCV geared towards common visual analysis tasks.

  • Native Integration: 100% compatible with NumPy arrays and standard OpenCV (cv2) functions.

Installation

You can install cv2-helper directly from PyPI using pip:

pip install cv2-helper

Quick Start

Here is a basic example of how to use the imshow visualization function to easily display an image:

import cv2
from cv2_helper import imshow

# Load an image using OpenCV
image = cv2.imread("sample_image.jpg")

# Display the image easily with cv2-helper
imshow(image, title="Test Result")

Requirements

  • Python $\geq 3.8$
  • OpenCV Python (opencv-python $\geq 4.0.0$)
  • NumPy

Author

Created and maintained by Pedro Mayorga

📧 Contact email: ppmayorga80@gmail.com

License

This project is distributed under the MIT license.

Metadata

Release files for cv2-helper 1.3.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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Source distribution for cv2-helper 1.3.0
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Table of built distributions (wheels) for cv2-helper 1.3.0
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cv2_helper-1.3.0-py3-none-any.whl Python 3 none any Details

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