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pip VS OpenCV

Compare pip VS OpenCV and see what are their differences

LibHunt
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

pip logo pip

The PyPA recommended tool for installing Python packages.

OpenCV logo OpenCV

OpenCV is the world's biggest computer vision library
  • pip Landing page
    Landing page //
    2023-08-23
  • OpenCV Landing page
    Landing page //
    2023-07-29

pip features and specs

  • Ease of Use
    pip is straightforward to use with simple command-line instructions for installing and managing Python packages.
  • Wide Adoption
    pip is the standard package manager for Python, widely adopted and supported across platforms, ensuring reliability and community support.
  • Dependency Management
    pip automatically handles package dependencies, downloading and installing them alongside the desired package.
  • Integration with PyPI
    pip seamlessly integrates with the Python Package Index (PyPI), giving access to thousands of packages.
  • Virtual Environment Support
    pip works well with virtual environments, allowing users to manage packages in isolated Python environments.

Possible disadvantages of pip

  • Limited Advanced Features
    pip focuses on simplicity and may lack some advanced package management features found in more sophisticated tools.
  • Version Conflicts
    While pip handles dependencies, it can sometimes lead to version conflicts when two packages require different versions of the same dependency.
  • Lack of System Package Awareness
    pip does not interact with system package managers, which can lead to situations where packages are duplicated or out of sync.
  • Performance with Large Projects
    Managing dependencies in large-scale projects can become cumbersome with pip, as it wasn't initially designed for such complex environments.

OpenCV features and specs

  • Comprehensive Library
    OpenCV offers a wide range of tools for various aspects of computer vision, including image processing, machine learning, and video analysis.
  • Cross-Platform Compatibility
    OpenCV is designed to run on multiple platforms, including Windows, Linux, macOS, Android, and iOS, which makes it versatile for development across different environments.
  • Open Source
    Being open-source, OpenCV is freely available for use and allows developers to inspect, modify, and enhance the code according to their needs.
  • Large Community Support
    A large community of developers and researchers actively contributes to OpenCV, providing extensive support, tutorials, forums, and continuously updated documentation.
  • Real-Time Performance
    OpenCV is highly optimized for real-time applications, making it suitable for performance-critical tasks in various industries such as robotics and interactive installations.
  • Extensive Integration
    OpenCV can easily be integrated with other libraries and frameworks such as TensorFlow, PyTorch, and OpenCL, enhancing its capabilities in deep learning and GPU acceleration.
  • Rich Collection of examples
    OpenCV provides a large number of example codes and sample applications, which can significantly reduce the learning curve for beginners.

Possible disadvantages of OpenCV

  • Steep Learning Curve
    Due to the vast array of functionalities and the complexity of some of its advanced features, beginners may find it challenging to learn and use effectively.
  • Documentation Gaps
    While the documentation is extensive, it can sometimes be incomplete or outdated, requiring users to rely on community forums or external sources for solutions.
  • Resource Intensive
    Some functions and algorithms in OpenCV can be quite resource-intensive, requiring significant processing power and memory, which can be a limitation for low-end devices.
  • Limited High-Level Abstractions
    OpenCV provides a wealth of low-level functions, but it may lack higher-level abstractions and frameworks, necessitating more hands-on coding and algorithm development.
  • Dependency Management
    Setting up and managing dependencies can be cumbersome, especially when integrating OpenCV with other libraries or on certain operating systems.
  • Backward Compatibility Issues
    With frequent updates and new versions, backward compatibility can sometimes be problematic, potentially breaking existing code when updating.

pip videos

+ Add

PIP Lancets Review #pip #piplancetreview #diabetes

More videos:

  • Review - Filling out the PIP Review Form
  • Review - My Tips for Your Personal Independence Payment Review | Disability | PIP

OpenCV videos

+ Add

AI Courses by OpenCV.org

More videos:

  • Review - Practical Python and OpenCV

Category Popularity

0-100% (relative to pip and OpenCV)

pip

OpenCV

Front End Package Manager
100 100%
Front End Package Manager
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Kids
100 100%
Kids
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare pip and OpenCV

pip Reviews

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OpenCV Reviews

7 Best Computer Vision Development Libraries in 2024
From the widespread adoption of OpenCV with its extensive algorithmic support to TensorFlow's role in machine learning-driven applications, these libraries play a vital role in real-world applications such as object detection, facial recognition, and image segmentation.
Source: www.labellerr.com
10 Python Libraries for Computer Vision
OpenCV is the go-to library for computer vision tasks. It boasts a vast collection of algorithms and functions that facilitate tasks such as image and video processing, feature extraction, object detection, and more. Its simple interface, extensive documentation, and compatibility with various platforms make it a preferred choice for both beginners and experts in the field.
Source: clouddevs.com
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
OpenCV is an open-source computer vision and machine learning software library that was first released in 2000. It was initially developed by Intel, and now it is maintained by the OpenCV Foundation. OpenCV provides a set of tools and software development kits (SDKs) that help developers create computer vision applications. It is written in C++, but it supports several...
Source: www.uubyte.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
These are some of the most basic operations that can be performed with the OpenCV on an image. Apart from this, OpenCV can perform operations such as Image Segmentation, Face Detection, Object Detection, 3-D reconstruction, feature extraction as well.
Source: neptune.ai
5 Ultimate Python Libraries for Image Processing
Pillow is an image processing library for Python derived from the PIL or the Python Imaging Library. Although it is not as powerful and fast as openCV it can be used for simple image manipulation works like cropping, resizing, rotating and greyscaling the image. Another benefit is that it can be used without NumPy and Matplotlib.
Source: towardsdatascience.com

Social recommendations and mentions

Based on our record, OpenCV should be more popular than pip. It has been mentiond 59 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

pip mentions (19)

  • PYMODINS
    Use the package manager pip to Install pymodins. - Source: dev.to / 10 months ago
  • How to build a new Harlequin adapter with Poetry
    To get the most out of this guide, you should have a basic understanding of virtual environments, Python packages and modules, and pip. Our objectives are to:. - Source: dev.to / 10 months ago
  • The ultimate guide to creating a secure Python package
    You need a build system to render the files you publish in the Python package. You can use a build frontend, such as pip, or a build backend, such as setuptools, Flit, Hatchling, or PDM. - Source: dev.to / 12 months ago
  • Let’s build AI-tools with the help of AI and Typescript!
    Package installer for Python (pip), we use this for installing the Python-based packages, such as Jupyter Lab, and we're going to use this for installing other Python-based tools like the Chroma DB vector database. - Source: dev.to / about 1 year ago
  • GrandTourer – a CLI tool for easily launching applications on macOS
    Use the package manager pip to install GrandTourer. GrandTourer requires Python >=3.8. Source: over 1 year ago
View more

OpenCV mentions (59)

  • Top Programming Languages for AI Development in 2025
    Ideal For: Computer vision, NLP, deep learning, and machine learning. - Source: dev.to / 5 days ago
  • Why 2024 Was the Best Year for Visual AI (So Far)
    Almost everyone has heard of libraries like OpenCV, Pytorch, and Torchvision. But there have been incredible leaps and bounds in other libraries to help support new tasks that have helped push research even further. It would be impossible to thank each and every project and the thousands of contributors who have helped make the entire community better. MedSAM2 has been helping bring the awesomeness of SAM2 to the... - Source: dev.to / 4 months ago
  • 20 Open Source Tools I Recommend to Build, Share, and Run AI Projects
    OpenCV is an open-source computer vision and machine learning software library that allows users to perform various ML tasks, from processing images and videos to identifying objects, faces, or handwriting. Besides object detection, this platform can also be used for complex computer vision tasks like Geometry-based monocular or stereo computer vision. - Source: dev.to / 6 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library is used for image and video processing, offering functions for tasks like object detection, filtering, and transformations in computer vision. - Source: dev.to / 7 months ago
  • Built in Days, Acquired for $20K: The NuloApp Story
    First of all, OpenCV, an open-source computer vision library, was used as the main editing tool. This is how NuloApp is able to get the correct aspect ratio for smartphone content, and do other cool things like centering the video on the speaker so that they aren't out of frame when the aspect ratio is changed. - Source: dev.to / 7 months ago
View more

What are some alternatives?

When comparing pip and OpenCV, you can also consider the following products

Conda - Binary package manager with support for environments.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Python Poetry - Python packaging and dependency manager.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Python Package Index - A repository of software for the Python programming language

NumPy - NumPy is the fundamental package for scientific computing with Python

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