Pose Estimation - Deep Learning using OpenPose
The Complete Guide to Creating your own Pose Estimation Apps: Learn the Full Workflow - Build 5 AI Apps

What you will learn
What is Pose Estimation
How to take Pose Estimation further using OpenPose
Step-by-step instructions on how to execute OpenPose
How to implement your own Fall Detection App.
Using OpenPose to Count People
Dive deeper by using Pose Estimation for Yoga Pose Identification
Ensure perfect planking and push up posture with OpenPose
Calculate real-time body ratios
Why take this course?
🚀 Course Headline: The Complete Guide to Creating your own Pose Estimation Apps: Learn the Full Workflow - Build 5 AI Apps 🚀
Are you ready to dive into the world of Augmented Reality (AR) and Computer Vision with OpenPose? This course is your golden ticket to mastering Pose Estimation using Deep Learning, all without the need for specialized hardware! Whether your passion lies in character animation for video games, assisted driving systems, medical applications, or beyond, this comprehensive guide will equip you with the skills to build your own Pose Estimation apps using just an ordinary webcam.
🧠 What You'll Learn:
- ✅ Fundamentals of Pose Estimation: We start from the basics, ensuring you have a solid foundation in this cutting-edge technology.
- ✅ OpenPose Framework: Step-by-step guidance on implementing OpenPose in real-time applications.
- ✅ Practical Application Development: By the end of the course, you'll have built no less than 5 practical Pose Estimation apps, including:
- 🚫 Fall Detection
- 👥 People Counting
- 🧘♀️ Yoga Pose Identification
- 💪 Plank Pose Correction
- ✅ Automatic Body Ratio Calculation, and more!
🎉 Bonus Content:
- Learn the fundamentals of Artificial Neural Networks and Convolutional Neural Networks.
- Access to office hours where your questions are answered directly by the course instructor.
- Join a community of learners and engage in discussions.
🏆 Elevate Your Career:
- Earn a Certificate of Completion to showcase your new skills and dedication to learning.
- Stand out in the job market with proof of your expertise in AI and Pose Estimation.
💸 Risk-Free Learning:
- The course comes with a 30-day, money-back guarantee. Your satisfaction is our priority!
📚 Course Structure:
- A mix of theoretical explanations and practical, hands-on projects.
- Real-world examples and case studies to solidify your understanding.
- Step-by-step instructions for implementing OpenPose in various scenarios.
🛠️ Tools & Technologies Covered:
- Python programming language
- Deep Learning concepts
- OpenPose framework
- Webcam integration for real-time applications
🚀 Why Choose This Course?
- Expert guidance from an experienced instructor.
- Practical, project-based learning with immediate applications.
- A supportive community and direct access to help.
- A certificate of completion that can open doors in the AI job market.
📅 Enroll Now & Transform Your Future: Don't miss out on this opportunity to become an expert in Pose Estimation using OpenPose. Click the enroll button today and join us on this exciting learning journey! 🎯
🌟 Important Notes 🌟
- This course is heavily focused on practical application and less on theoretical details.
- We provide a comprehensive overview of OpenPose, with the emphasis on getting you up and running quickly.
- By the end of this course, not only will you have a solid understanding of Pose Estimation but also a portfolio of apps to show for it! 🎉
Ready to unlock your potential in Pose Estimation and Deep Learning? Let's get started! 🌟
Screenshots




Our review
🔍 Course Overview:
The course, titled "Human Pose Estimation and its application," focuses on teaching students how to implement Human Pose Estimation using OpenCV and Python. It is designed for those who have a foundational understanding of these tools, as the reviews suggest that having prior knowledge in this area will be beneficial.
Pros:
- Instructor Engagement: The instructor is reported to be excellent and responsive to questions, which is a positive aspect of the course.
- Relevant Content: The subject matter of Human Pose Estimation is highly relevant and interesting, as indicated by several reviews.
- Beginner Friendly: For beginners, the course is said to start simply and be easy to understand, exceeding some learners' expectations.
- Active Community: There seems to be an active community or peer support, which can enhance the learning experience.
Cons:
- Outdated Material: Some reviewers have noted that the code provided in the course is outdated and may not work with newer library versions. The instructor should consider updating the code and providing solutions to potential problems.
- Installation and Resource Issues: There are reports of installation links being outdated or incorrect, which could make the course more challenging to follow. Some reviewers also pointed out a lack of comprehensive resources for running scripts like
run.py
orwebcam.py
. - Incomplete Content: The course is criticized for not covering many features of TF-Pose estimation or OpenPose, and for lacking detailed explanations, especially on why certain code implementations are used.
- Error in Lecture Reference: At least one reviewer reported an error in the first lecture that referenced a non-existent previous lecture, which could confuse students.
- Complexity and Structure: Some learners found the course structure and pace to be too fast, making it difficult to follow along without additional resources or more detailed explanations.
General Feedback:
The general sentiment regarding this course seems to be mixed. While some aspects are commendable—such as the instructor's engagement and the relevance of the subject matter—there are significant concerns about the outdated code, installation issues, and the need for more comprehensive content and explanations. The course appears to be a good starting point but may require additional resources or updates from the instructor to enhance the learning experience and ensure that students can successfully implement Human Pose Estimation techniques using OpenCV and Python.
Recommendation:
For learners interested in this topic, it is recommended to look for supplementary materials and resources that can complement the course content. Additionally, potential students should consider reaching out to the instructor for clarifications or updates on the code used in the course before enrolling. It would also be beneficial to have a preliminary understanding of OpenCV and Python to fully grasp the lessons provided.