StreamLit OpenCV Computer Vision Web App

StreamLit OpenCV Computer Vision Web App, available at $54.99, has an average rating of 4.65, with 9 lectures, based on 15 reviews, and has 90 subscribers.

You will learn about 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 This course is ideal for individuals who are Students who want to create presentable computer vision web apps or Students who want to learn StreamLit and how to integrate it with Computer Vision It is particularly useful for Students who want to create presentable computer vision web apps or Students who want to learn StreamLit and how to integrate it with Computer Vision.

Enroll now: StreamLit OpenCV Computer Vision Web App

Summary

Title: StreamLit OpenCV Computer Vision Web App

Price: $54.99

Average Rating: 4.65

Number of Lectures: 9

Number of Published Lectures: 9

Number of Curriculum Items: 9

Number of Published Curriculum Objects: 9

Original Price: $99.99

Quality Status: approved

Status: Live

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

Who Should Attend

Students who want to create presentable computer vision web apps
Students who want to learn StreamLit and how to integrate it with Computer Vision

Target Audiences

Students who want to create presentable computer vision web apps
Students who want to learn StreamLit and how to integrate it with Computer Vision

*Price goes up to $39 on the 1st of April 2022. Price increase is due to newer content added to the course every month.

In this course, we are going to learn how to build from scratch a Computer Vision Web Application using StreamLit in Python and OpenCV. We’ll start off by coding the StreamLit User Interface with Python onlyand then combine it with Googles’ Media Pipe Library to perform face landmark detection in real-time. From there we’ll create three pages:

The first webapp page will tell us a little about the Web App and the Author,
The second page of the UI one helps us to infer Face-Mesh on a single image, and
The third will allow us to implement Real-Time face landmark detection on a video at 30FPS.

What’s really great about this is that unlike native OpenCV apps is that you can actually interact with the app and make adjustments and create neat and professional dashboards with this.

If you don’t already know, StreamLit can turn data scripts into shareable web apps in minutes. All in Python. All for free. NO front-end, HTML, JAVA experience required.

This course is a full practical course, no fluff, just straight on practical coding.

Requirements

Please ensure that you have the following:

Basic understanding of Computer Vision
Python Programming Skills
Mid to high range PC/ Laptop
Windows 10/Ubuntu

30 Day Udemy Refund Guarantee

If you are not happy with this course for any reason, you are covered by Udemy’s 30 day no questions asked refund guarantee.

Course Curriculum

Chapter 1: Building your StreamLit Computer Vision Dashboard

Lecture 1: Introduction

Lecture 2: Getting the Project Files

Lecture 3: StreamLit Framework

Lecture 4: Streamlit Image Resize Function and Sidebar

Lecture 5: About Me Page Design

Lecture 6: Image Detection Page

Lecture 7: Video Detection Part-1

Lecture 8: Video Detection Part-2

Lecture 9: Video Detection Part-3

Instructors

Augmented Startups
M(Eng) AI Instructor 100k+ Subs on YouTube & 60k+ students

Rating Distribution

1 stars: 0 votes
2 stars: 1 votes
3 stars: 0 votes
4 stars: 6 votes
5 stars: 8 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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