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Trainer Name

Alexandra Kropova

Skill Area

Scientific or Technical, Statistics or Research and Development

Reviews

4.5 (20 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


Learner Feedback

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

5

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