Ultralytics YOLO11 | Training, Inference, Benchmarking, and Deployment Explained! 🚀 - What is Depth Estimation & How to Implement It with MiDaS by Intel Labs | Monocular Depth Explained🚀

Depth estimation enables AI to perceive how far objects are from the camera, a critical step toward 3D understanding, robotics, and AR/VR applications. In this tutorial, we explore MiDaS, a depth estimation model by Intel Labs for high-quality monocular depth estimation. We’ll start with a quick overview of the MiDaS GitHub repository and run a depth estimation demo video to visualize the model's performance. You’ll then learn how to implement and run the MiDaS Python code step-by-step, visualize the results, and even perform real-time depth estimation using a webcam. Chapters: 00:00 - Introduction to depth estimation and MiDaS by Intel Labs 01:00 - MiDaS GitHub repository README walkthrough 04:04 - Depth estimation demo video 05:11 - Step-by-step depth estimation code walkthrough in Python 08:23 - Running the depth estimation code and visualizing results 10:04 - Real-time depth estimation using a webcam 11:03 - Conclusion and key takeaways 🔗 MiDaS GitHub Repo ➡️ https://github.com/isl-org/MiDaS 🔗 Code ➡️ https://drive.google.com/file/d/1UauJsHB_A54t-d6AMon-x7UQ_SCS-vbj/view?usp=sharing Ultralytics Resources: 🏢 About Us: https://ultralytics.com/about 💼 Join Our Team: https://ultralytics.com/work 📞 Contact Us: https://ultralytics.com/contact 💬 Discord Community: https://discord.com/invite/ultralytics 📄 Ultralytics License: https://ultralytics.com/license #depthestimation #midas #intellabs #computervision #python #ultralytics