Creating and Publishing Computer Vision Packages
Lakshay Kumar (~lakshay6) |
Description:
Creating and Publishing Computer Vision Packages
Description:
Computer Vision (CV) has revolutionized the way we interact with and understand visual data. In this talk, we will dive into the exciting world of CV, exploring its applications and potential in various fields. We will showcase a live demonstration of CV techniques implemented in Python, providing a hands-on experience of the power and versatility of this technology.
Beyond the basics, we will focus on the process of creating a CV package for real-life implementation. We will discuss the key steps involved in packaging CV algorithms, ensuring modularity, extensibility, and reusability. From defining the package structure to incorporating the necessary dependencies, we will cover best practices that streamline the development process.
But creating a CV package is only half the journey. To truly make an impact, it is essential to share your work with the wider developer community. We will explore effective strategies for publishing your CV packages, making them readily available for other developers to utilize and contribute to. We will discuss popular platforms and repositories for package distribution, such as PyPI and GitHub, and delve into the essential documentation and licensing considerations.
Throughout the talk, we will draw from real-world examples and experiences, highlighting success stories and lessons learned from creating and publishing CV packages. Whether you are a seasoned CV practitioner or just starting your journey into this fascinating field, this talk aims to equip you with the knowledge and tools needed to create impactful CV packages and share them with the thriving developer community.
Join us as we explore the intricacies of creating and publishing computer vision packages, and unlock the potential of CV in various domains!
What You'll Learn:
- Gain an understanding of Computer Vision (CV) and its applications in various fields.
- Experience a live demonstration of CV techniques implemented in Python.
- Learn the key steps involved in packaging CV algorithms for real-life implementation.
- Discover best practices for ensuring modularity, extensibility, and reusability in CV packages.
- Explore effective strategies for publishing CV packages and making them available to other developers.
- Understand popular platforms and repositories like PyPI and GitHub for package distribution.
- Learn about essential documentation and licensing considerations when publishing CV packages.
- Benefit from real-world examples, success stories, and lessons learned in creating and publishing CV packages.
- Acquire the knowledge and tools needed to create impactful CV packages and share them with the thriving developer community.
- Unlock the potential of Computer Vision (CV) in various domains through practical insights and guidance.
Join us to gain valuable insights and expertise in creating and publishing computer vision packages!
Prerequisites:
Preferable Prerequisites:
To make the most out of this talk on creating and publishing computer vision packages, it is recommended to have a basic understanding of Python programming. Familiarity with the following concepts and libraries will be helpful:
- Python Syntax: Understand the basics of Python programming language, including variables, data types, conditionals, loops, and functions.
- Object-Oriented Programming (OOP): Knowledge of OOP concepts like classes, objects, and inheritance will be beneficial, as packaging computer vision algorithms often involves creating modular and reusable code structures.
- Version Control: Familiarity with basic version control concepts using Git will be useful, especially when discussing publishing CV packages on platforms like GitHub.
While the talk will provide an overview of creating and publishing computer vision packages, having a basic understanding of Python programming will ensure you can follow along and grasp the concepts more effectively.
No worries if you're not familiar with these prerequisites! We'll be discussing them in the simplest terms possible, making it accessible for everyone.
Speaker Info:
I am an author of From Data to World : 5 Real world secrets with Data Science and currently serving as a Data Analyst and SD Manager at UK Start-up, where i am building an automation for a complex registration process. I've mentored students, guiding them through their Python learning along with implementation and helping them take their first steps into the world of technology. Before embarking on my college journey, I actively collaborated with small startups and businesses, assisting them in leveraging technology to streamline their operations. This experience allowed me to acquire proficiency in programming languages such as Java, C++, and Python. Presently, I am exploring the fascinating realms of AI/ML, driven by a strong curiosity to delve deeper into this field. I had the privilege of sharing my insights and expertise with audiences at Microsoft, EFY group, OpsTree, Thoughtworks and Mathworks. My talks have provided valuable insights into the latest trends and advancements in the tech industry.