Image Processing and Computer Vision with Python & OpenCV – Shiv Onkar Deepak Kumar

What you'll learn

• Image Processing with Python (skimage) (90% hands on and 10% theory)
• Image Processing and Computer Vision with OpenCV (90% hands on and 10% theory)
• Morphological operations with OpenCV (90% hands on and 10% theory)
• Face detection with OpenCV (90% hands on and 10% theory)
• Feature detection with OpenCV (90% hands on and 10% theory)
• Image matching with skimage (90% hands on and 10% theory)
• Object detection with OpenCV (90% hands on and 10% theory)
• Digit recognition with OpenCV (90% hands on and 10% theory)

Course content

12 sections • 77 lectures • 9h 20m total length

• Introduction and Foundation
• sklearn – Image processing
• opencv – Image processing
• Morphological operations
• Face detection
• Feature detection
• Image matching
• Object detection
• Digit recognition
• Image segmentation
• Vehicle detection
• Miscellaneous

Requirements

• 1. Passion for Learning 2. Curiosity for image analysis 3. NumPy knowledge

Description

The Image Processing and Computer Vision world is too big to comprehend.  It has been backbone of many industry including Deep Learning. It is used across multiple places. As practitioner, I am trying to bring many relevant topics  under one umbrella in following topics.

• 1. Image Processing with Python (skimage) (90% hands on and 10% theory)
• 2. Image Processing and Computer Vision with OpenCV (90% hands on and 10% theory)
• 3. Morphological operations with OpenCV (90% hands on and 10% theory)
• 4. Face detection with OpenCV (90% hands on and 10% theory)
• 5. Feature detection with OpenCV (90% hands on and 10% theory)
• 6. Image matching with skimage (90% hands on and 10% theory)
• 7. Object detection with OpenCV (90% hands on and 10% theory)
• 8. Digit recognition with OpenCV (90% hands on and 10% theory)

Who this course is for:

• Any one eager to know about Image Processing and Computer Vision

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