Deep Learning OpenCV 4 Computer Vision With Python 3 PDF

Download Deep Learning OpenCV 4 Computer Vision with Python 3 Free in PDF. This notes is very great and helpful for everyone who’s just started computer vision and who’s expert in it. By this notes you will get technique and algorithms for computer vision. In this notes you’ll learn how to solve computer vision problems and perform basic operations.

This Notes help you to understand  digital images or videos and practice to build a GUI app. In this notes you’ll also learn the concept of machine learning. In this notes there is provide example code for practicing to understand the concept.

You Will Learn These Topic From This Notes:

1.Setting Up OpenCV

• Technical Requirements
• What’s New in OpenCV 4
• Choosing and Using the Right Setup Tool
• Running Samples
• Finding Documentation, Help and Updates

2. Handling Files, Cameras and GUIs

• Technical Requirements
• Basic I/O Scripts
• Reading /Writing an Image File
• Project Cameo
• Cameo- an Object Oriented Design

3. Processing Image with OpenCV

• Technical Requirement
• Converting Images Between Different Color Models
• Exploring the Fourier Transform
• Creating Modules
• Edge Detection
• Custom Kernels Getting Convoluted
• Contour Detection

4. Depth Estimation and Segmentation

• Technical Requirements
• Creating Module
• Capturing Frame from a Depth Camera
• Creating a Mask from a Disparity Map
• Modifying the Application
• Image Segmentation with the Watershed Algorithm

5. Detecting and Recognizing Faces

• Technical Requirements
• Conceptualizing Haar Cascades
• Getting Haar Cascade Data
• Using OpenCV to Perform Face Detection

6. Retrieving Images and Searching Using Image Descriptor

• Technical Requirement
• Understanding Types of Feature Detection and Matching
• Detecting Harris Corner
• Detecting DoG Feature and SIFT Descriptor
• A Sample Application- Tattoo Forensics

7. Building Custom Object Detector

• Technical Requirements
• Understanding NMS
• Understanding SVMs
• Detecting Cars
• Detecting People with HOG Descriptor
• Creating and Training an Object Detector

8. Tracking Objects

• Technical Requirements
• Detecting Moving Objects with Background Subtraction
• Tracking Colorful Object Using Meanshift and Camshift
• Finding Trend in Motion Using the Kalman Filter
• Tracking Pedestrian

9. Camera Model and Augmented Reality

• Technical Requirement
• Understanding 3D image Tracking and Augmented Reality
• Implemented the Demo Application
• importing Modules
• Improving the 3D Tracking Algorithm

10. Introduction to Neural Network with OpenCV

• Technical Requirements
• Understanding ANNs
• Training a Basic ANNs in OpenCV
• Training an ANNs Classifier in Multiple Epochs
• Using DNNs from the Framework in OpenCV
• Detecting and Classify Object with Third Party DNNs