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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

4.4 (19 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 What you'll need

2 Course overview - OpenCV

1 Dictionaries Examples

2 Functions Examples

3 Functions

4 For Loops Examples

5 While Loops Examples

6 Loops

7 If Statement Variants Examples

8 If Statement Examples

9 Conditionals

10 Ranges Examples

11 Parameters And Return Values Examples

12 Tuples Examples

13 Multidimensional List Examples

14 Lists

15 Collections

16 Operators Examples

17 Operators

18 Type Conversion Examples

19 Variables

20 Intro To Python

21 Introduction

22 Summary and Outro

23 Static Members Example

24 Inheritance Examples

25 Objects Examples

26 Classes Example

27 Classes and Objects

1 Detect edges in an image

2 Detect corners in an image

3 Detect contours in an image

1 Restore a damaged image

1 Find object in image with template matching

2 Extract foreground in an image

3 Detect faces in images

4 Detect objects in an image with masking

1 What is ML-Agents

2 What is a Neural Network

3 What is Deep Learning

4 What is Machine Learning

1 Extract foreign language text from an image

2 Change perspective of an image with foreign text

3 Improve accuracy with thresholding

4 Extract text from an image with Tesseract

1 Visualize model results

2 Build an artificial neural network

3 Generate data

1 Build a neural network with OpenCV

2 Outline objects in the original image

3 Print out detected objects

4 Load YOLO DNN model

1 Save new frames as a video

2 Draw contours on video

3 Outline objects in a video

1 Save new frames as a video

2 Detect eyes in video

3 Detect faces in video

4 Load a video from Drive

5 Play the new video in Colab

1 Save new frames as a video

2 Track color in a video

1 Save new frames as a video

2 Outline lanes detected

3 Process each video frame

4 Load a driving dash cam video

1 Detect when motion begins and ends

2 Record each time motion begins

3 Detect objects in a video with contours

4 Load a video from Drive

1 BuraTechVideo

2 Detect emotion in a video

1 Combine face masks

2 Build a warped mask

3 Draw a mask over facial landmarks

4 Build a matrix from landmark points

5 Get Facial Landmarks from Image

6 Load images from the web into Colab

Trainer

Trainer Name

Alexandra Kropova

4.4 Rating
19 Reviews

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This course includes:

  • Duration: 13 Hours 28 Min

  • Skill Level: Beginner

  • Lectures: 78 lessons

  • Enrolled: 1134 learners

  • Certificate of Completion

  • Lifetime access

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