[Udemy] Hands on Robotic Vision: OpenCV, PyTorch, YOLO, Simulation [9/2026, ENG] [TorrentX]

Hands on Robotic Vision: OpenCV, PyTorch, YOLO, SimulationГод выпуска: 9/2026 Производитель: Udemy Сайт производителя: https://www.udemy.com/course/hands-on-computer-vision-for-robotics-opencv-pytorch-yolo/ Автор: Saroj Debnath Продолжительность: 31h 39m Тип раздаваемого материала: Видеоурок Язык: Английский Описание: This course takes you from the fundamentals of computer vision to building fully vision-guided robots, covering everything needed to master one of modern robotics' most in-demand skills. It begins with image processing using OpenCV—color spaces, edge and contour detection, ArUco marker recognition, and camera calibration—then moves into deep learning for vision, where you build convolutional neural networks from scratch in PyTorch, apply transfer learning with ResNet, detect objects in real time with YOLO, and perform instance segmentation, with every concept tied to a practical robotics use case.The course then bridges theory and hardware by teaching how cameras are modeled mathematically, how to set up eye-to-hand and eye-in-hand configurations, and how to implement Image-Based Visual Servoing, the technique that lets a robot move based on what it sees. You finish by building complete projects in PyBullet simulation with a Franka Panda robot arm, including color-based grasping, vision-guided pick and place, and ArUco-based navigation, before closing with real hardware projects on a Universal Robot arm. By the end, you will have a portfolio of robot vision projects and the confidence to apply computer vision to real-world robotics challenges. Basic Python is required, but no prior robotics or computer vision experience is needed. Содержание 1 - Introduction and Setup 1. Introduction (04:21) 2. Setup and Resources (27:34)2 - Basic Python 3. Pre-Section Talk (02:20) 4. Installation (04:33) 5. Data Types (16:34) 6. Flow Control (12:00) 7. Functions (14:35) 8. Python Classes (16:55) 9. Python Modules (07:56) 10. Exception Handling (05:44) 11. Logging (04:41) 13. PROJECT Brightness Control (20:33)3 - Dive into Image Processing 14. Load Images (34:39) 15. Understand the color spaces (15:45) 16. Image Thresholding (21:51) 17. Canny Edge Detection (15:24) 18. Sobel Edge Detection (08:35) 19. Contour Detection (10:12) 20. Morphological Operation (15:20) 21. Template Matching (07:10) 22. Hough Transform (12:17) 23. Geometric Transformation (07:57) 24. Histogram Equalization (09:16) 25. Feature Matching (12:22) 26. Background Subtraction (06:14) 27. Camera Calibration (08:57) 28. Understand Homography and perspective transform (10:32) 29. Object Tracking (16:34) 30. Aruco Marker (15:45) 31. Optical Flow (14:18) 32. PROJECT1 Augmented Reality (23:10) 33. PROJECT2 Create Panoramic Scenes (22:19)4 - FastAPI Basics 34. Pre-Section Talk (02:57) 35. FastAPI Basics (27:15)5 - More Image processing project