StreamLit OpenCV Computer Vision Web App
How to build a Computer Vision Web Application using StreamLit MediaPipe in Python & OpenCV

What you will learn
Build a StreamLit Analytics Dashboard
Integrate Computer Vision into StreamLit
Learn how to use MediaPipes Face Landmark Detection on Images and Video
Implement Widgets, Sliders and checkboxes
OpenCV Python and StreamLit WebApp Development
Why take this course?
π Course Title: StreamLit OpenCV Computer Vision Web App
π Headline: Master the Art of Building a Real-Time Computer Vision Web Application with Python, StreamLit, and OpenCV
Embark on an exciting journey to harness the power of computer vision through web applications! πβ¨ In this comprehensive course titled "StreamLit OpenCV Computer Vision Web App," you'll learn the ins and outs of creating a fully functional, interactive computer vision application using Python, StreamLit, and OpenCV. Dive into the world of real-time image and video analysis with ease!
Course Overview:
π What You'll Learn:
- StreamLit UI Coding: Master the creation of intuitive user interfaces with Python alone.
- Face Landmark Detection: Utilize Google's MediaPipe to perform real-time face landmark detection.
- Interactive Web App Development: Build a web application that allows users to analyze images and videos in real-time.
- High-Quality Output: Create dashboards that are both professional and user-friendly, all without the need for front-end development skills.
Course Structure:
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Introduction to the Web App: A brief overview of the application's capabilities and its author.
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Page 1: Single Image Analysis: Learn how to infer face landmarks from a static image.
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Page 2: Real-Time Video Processing: Implement real-time face landmark detection on video streams at an impressive 30 frames per second (FPS).
Course Benefits:
- Ease of Use: StreamLit allows for the rapid development of web apps using Python scripts. No need to juggle with HTML, JAVA, or front-end technologies.
- Full Practical Course: This course is packed with practical coding sessions and real-world examples, with zero unnecessary theory.
Course Requirements:
π Before you dive in, make sure you have the following:
- A basic understanding of Computer Vision concepts.
- Proficiency in Python programming.
- A mid to high-range PC or laptop.
- Windows 10 or Ubuntu operating system.
Guaranteed Satisfaction:
π 30 Day Udemy Refund Guarantee: If this course doesn't live up to your expectations for any reason, Udemy's 30-day no questions asked refund guarantee has got you covered!
Price Note: The current price of this course is just a steal at $39, but remember, the price is set to increase on the 1st of April 2022 due to the addition of newer content every month. Don't miss out on this opportunity to upgrade your skills and stay ahead in the field of computer vision web applications! π
Enroll now and start your journey towards becoming a Computer Vision Web App expert with StreamLit, OpenCV, and Python! π€π©βπ»β¨
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