OpenCV Training - Learn Computer Vision with Python

20 Lesson

30 Hours

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igmGuru offers OpenCV Training Online worldwide, and the course content is designed by industry experts who have more than 20 years of experience in computer vision and image processing. In this OpenCV course, you will learn key topics such as image processing fundamentals, feature detection, object tracking, face recognition, video analysis, and real-time computer vision applications using Python and OpenCV. After completing this course, a person can build strong practical skills in computer vision, work on AI-based projects, and become job-ready for roles in machine learning and image processing.

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Overview

Prerequisites

Basic knowledge of Python programming
Understanding of fundamental mathematics (algebra and matrices)
Familiarity with basic machine learning concepts is helpful
A computer system to install and practice OpenCV tools

What You Will Learn

Image and video processing using OpenCV
Core image transformations and filtering techniques
Edge detection, thresholding, and contour analysis
Feature detection and real-time object tracking
Face detection and recognition applications
Deep learning-based object detection with OpenCV DNN (YOLO, SSD)
OCR integration for text recognition
Camera calibration and basic 3D vision concepts
Building practical computer vision projects using Python and OpenCV

Key Features

Instructor Led Training : 30 Hrs
100% Job Assistance
24 X 7 Lifetime Support
Get Certified & Get Placed
Small Batches Upto 10 Participants
100% Money-Back Guarantee

Course Curriculum

Lesson 1 - Introduction to OpenCV

1. What is OpenCV?

2. Applications of Computer Vision

3. OpenCV Library Overview

4. OpenCV with Python vs C++

Lesson 2 - OpenCV Installation and Environment Setup

1. Installing OpenCV on Windows/Linux/Mac

2. Setting up Python and Jupyter Notebook

3. Installing OpenCV with pip and conda

4. Verifying OpenCV Installation

Lesson 3 - Basics of Image Handling

1. Reading and Displaying Images

2. Writing and Saving Images

3. Image Properties (shape, size, channels)

4. Working with Pixels

Lesson 4 - Image Processing Fundamentals

1. Color Spaces (BGR, RGB, HSV, Grayscale)

2. Image Resizing and Scaling

3. Cropping and Region of Interest (ROI)

4. Image Rotation and Transformation

Lesson 5 - Image Drawing and Annotation

1. Drawing Lines, Circles, Rectangles

2. Adding Text on Images

3. Creating Custom Shapes

Lesson 6 - Image Enhancement Techniques

1. Brightness and Contrast Adjustment

2. Histogram Equalization

3. Image Smoothing and Noise Removal

Lesson 7 - Image Filtering and Blurring

1. Gaussian Blur

2. Median Blur

3. Bilateral Filtering

4. Sharpening Filters

Lesson 8 - Edge Detection and Gradients

1. Sobel Operator

2. Laplacian Operator

3. Canny Edge Detection

Lesson 9 - Thresholding and Segmentation

1. Simple Thresholding, Adaptive Thresholding

2. Otsu Thresholding

3. Image Segmentation Basics

Lesson 10 - Morphological Operations

1. Erosion and Dilation, Opening and Closing

2. Morphological Transformations

Lesson 11 - Contours and Shape Analysis

1. Finding Contours

2. Contour Approximation

3. Shape Detection (circle, rectangle)

4. Object Measurement using Contours

Lesson 12 - Feature Detection and Matching

1. Corner Detection (Harris, Shi-Tomasi)

2. Keypoint Detectors (SIFT, SURF, ORB)

3. Feature Matching Techniques

4. Image Alignment and Stitching

Lesson 13 - Working with Video and Camera

1. Capturing Video from Webcam

2. Reading Video Files , Saving Video Output

3. Frame-by-Frame Processing

Lesson 14 - Object Detection and Tracking

1. Background Subtraction

2. Object Tracking Algorithms

3. Motion Detection in Video Streams

4. Multi-object Tracking Basics

Lesson 15 - Face Detection and Recognition

1. Haar Cascade Face Detection

2. Eye and Smile Detection, Face Recognition Overview

Lesson 16 - Deep Learning with OpenCV (DNN Module)

1. Introduction to OpenCV DNN

2. Loading Pre-trained Models

3. Object Detection with YOLO

4. SSD and TensorFlow Model Integration

Lesson 17 - Pose Estimation and Human Activity Detection

1. Introduction to Pose Estimation

2. Using OpenPose Models

3. Skeleton and Keypoint Detection

Lesson 18 - Optical Character Recognition (OCR) with OpenCV

1. Text Detection in Images

2. Image Preprocessing for OCR

3. Integrating Tesseract OCR

Lesson 19 - Camera Calibration and 3D Vision

1. Camera Calibration Basics , Distortion Correction

2. Stereo Vision Introduction, Depth Estimation Concepts

Lesson 20 - OpenCV Deployment

1. Optimizing OpenCV Applications

2. Using OpenCV in AI Products

3. OpenCV with Raspberry Pi and Edge Devices

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Course Fees

Online Class Room Program

US $ 799.00

100% Money Back Guarantee

Duration : 30 Hrs
Plus Self Paced

Classes Starting From

Fast Track Batch 29 May 2026
Weekday Batch 01 Jun 2026
Weekend Batch 30 May 2026

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Flexible Training Schedule Options
Industry Experienced Trainers
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Want to know Today's Offer

OpenCV Certification

After successfully completing the OpenCV Training, you will receive an igmGuru Course Completion Certificate. This certificate validates your skills in image processing, computer vision, object detection, and real-time video analysis using OpenCV. It can be added to your resume and LinkedIn profile to showcase your expertise in computer vision and AI-based application development.

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OpenCV Training - Learn Computer Vision with Python