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Computer Vision and Deep Learning with OpenCV and Python ‑ Build 15 Projects

Course Details
Trainer Name

Alexandra Kropova

Skill Area

Scientific or Technical, Statistics or Research and Development

Reviews

4.5 (25 Rating)

Course Requirements

No experience is needed in this course.

Course Description

This is a project based course focusing on building projects as you will learn OpenCV. This course is suitable for beginners to a more advanced learners.

Course Outcomes

1. Learn to analyze images with OpenCV
2. Deep Learning with Neural Networks and OpenCV
3. Learn to analyze videos with OpenCV

Course Curriculum

1 Course overview - OpenCV

2 What you'll need

1 Introduction

2 Intro To Python

3 Variables

4 Type Conversion Examples

5 Operators

6 Operators Examples

7 Collections

8 Lists

9 Multidimensional List Examples

10 Tuples Examples

11 Dictionaries Examples

12 Ranges Examples

13 Conditionals

14 If Statement Examples

15 If Statement Variants Examples

16 Loops

17 While Loops Examples

18 For Loops Examples

19 Functions

20 Functions Examples

21 Parameters And Return Values Examples

22 Classes and Objects

23 Classes Example

24 Objects Examples

25 Inheritance Examples

26 Static Members Example

27 Summary and Outro

1 Detect edges in an image

2 Detect contours in an image

3 Detect corners in an image

1 Restore a damaged image

1 Detect objects in an image with masking

2 Detect faces in images

3 Extract foreground in an image

4 Find object in image with template matching

1 What is Machine Learning

2 What is Deep Learning

3 What is a Neural Network

4 What is ML-Agents

1 Extract text from an image with Tesseract

2 Improve accuracy with thresholding

3 Change perspective of an image with foreign text

4 Extract foreign language text from an image

1 Generate data

2 Build an artificial neural network

3 Visualize model results

1 Load YOLO DNN model

2 Build a neural network with OpenCV

3 Print out detected objects

4 Outline objects in the original image

1 Outline objects in a video

2 Draw contours on video

3 Save new frames as a video

1 Load a video from Drive

2 Detect faces in video

3 Detect eyes in video

4 Save new frames as a video

5 Play the new video in Colab

1 Track color in a video

2 Save new frames as a video

1 Load a driving dash cam video

2 Process each video frame

3 Outline lanes detected

4 Save new frames as a video

1 Load a video from Drive

2 Detect objects in a video with contours

3 Detect when motion begins and ends

4 Record each time motion begins

1 Detect emotion in a video

2 BuraTechVideo

1 Load images from the web into Colab

2 Get Facial Landmarks from Image

3 Build a matrix from landmark points

4 Draw a mask over facial landmarks

5 Build a warped mask

6 Combine face masks

Trainer

Trainer Name

Alexandra Kropova

4.5 Rating
25 Reviews

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This course includes:

  • Duration: 13 Hours 28 Min

  • Skill Level: Beginner

  • Lectures: 78 lessons

  • Enrolled: 1539 learners

  • Certificate of Completion

  • Lifetime access

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