OpenCV with Python (Computer Vision)
OpenCV with Python (Computer Vision), available at $79.99, has an average rating of 4.35, with 36 lectures, based on 63 reviews, and has 280 subscribers.
You will learn about Images, Video read in Python using OpenCV. Resizing, Cropping of images and videos in Python using OpenCV. Draw shapes on images such as circle, rectangle, ellipse, line. Adding text message on images. Hide a portion of images using XOR, NOT and AND operation. Image manipulation such as smoothing, blurring. Read different type of images with (single channel, 3 channel, 4 channel images). Image splitting Saving Images and Videos files using OpenCV on our PC. Color conversation of images (BGR to gray), (BGR to RGB). Reading images from different package using PILLOW. Most important: contour and its properties for analyzing the shape of the object in an image. Detect line on the image with canny algorithm. Feature detection on images and matching between the images. Common problem student face while working on OpenCV. This course is ideal for individuals who are Python developer who is interested in Computer Vision and Deep Learning to learn how image and video processing is done using OpenCV. It is particularly useful for Python developer who is interested in Computer Vision and Deep Learning to learn how image and video processing is done using OpenCV.
Enroll now: OpenCV with Python (Computer Vision)
Summary
Title: OpenCV with Python (Computer Vision)
Price: $79.99
Average Rating: 4.35
Number of Lectures: 36
Number of Published Lectures: 36
Number of Curriculum Items: 36
Number of Published Curriculum Objects: 36
Original Price: ₹799
Quality Status: approved
Status: Live
What You Will Learn
- Images, Video read in Python using OpenCV.
- Resizing, Cropping of images and videos in Python using OpenCV.
- Draw shapes on images such as circle, rectangle, ellipse, line.
- Adding text message on images.
- Hide a portion of images using XOR, NOT and AND operation.
- Image manipulation such as smoothing, blurring.
- Read different type of images with (single channel, 3 channel, 4 channel images).
- Image splitting
- Saving Images and Videos files using OpenCV on our PC.
- Color conversation of images (BGR to gray), (BGR to RGB).
- Reading images from different package using PILLOW.
- Most important: contour and its properties for analyzing the shape of the object in an image.
- Detect line on the image with canny algorithm.
- Feature detection on images and matching between the images.
- Common problem student face while working on OpenCV.
Who Should Attend
- Python developer who is interested in Computer Vision and Deep Learning to learn how image and video processing is done using OpenCV.
Target Audiences
- Python developer who is interested in Computer Vision and Deep Learning to learn how image and video processing is done using OpenCV.
Welcome to the OpenCV course. If you are interested in the field of Computer Vision or Deep Learning? Then this course is for you.
Nowadays, Computer Vision is used in Automation in every domain such as self-driving cars, warehouses, security, object tracking, feature matching, and many more.
Moreover, in this course, we are covering the basic to advance level core concepts for image and video processing. We have taken a practical approach to explain the core concept of image and video processing. This course is best for students who want to start their career as Computer Vision Engineer.
We have divided this course into Chapters. In each chapter, you will learn the core concept of Image And Video Processing. These are some of the topics that we will be covering in this course:
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Image Read
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Image Crop
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Image Resized
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Image Rotate
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Image Split
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Image Save
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Video Read
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Video Resizing
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Video Save
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Draw a Circle on the Image
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Adding Text Messages to Images
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Draw Line Segment on Image
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Draw a Rectangle on the Image
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Draw an Ellipse on the Image
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Arithmetic Operation
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Image Blending
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Threshold and Blurring
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Area and Perimeter of Contours
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Find Contours in an Image
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Fitting Shape on the Contours
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Checkpoint if inside, outside, or on the Contours
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SIFT – (Scale – Invariant Feature Transform)
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Feature Matching
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and much more!
Feel free to message me on the Udemy Q&A board, if you have any queries about the course!
Thanks for checking the course page, and I hope to see you in my Course!!!
Pooja
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Lecture 2: What is OpenCV ?
Lecture 3: Getting Setup for Course
Lecture 4: what is Image and Type of Imgaes ?
Chapter 2: OpenCV – Image Operation
Lecture 1: Image Read
Lecture 2: Image Crop
Lecture 3: Image Resized
Lecture 4: Image Rotate
Lecture 5: Image Split
Lecture 6: Image Save
Chapter 3: OpenCV – Video Operation
Lecture 1: Video Read
Lecture 2: Video Resized
Lecture 3: Video Save
Chapter 4: OpenCV – Draw Shape
Lecture 1: Draw Circle
Lecture 2: Adding Text Message
Lecture 3: Draw Line Segment
Lecture 4: Draw Rectangle
Lecture 5: Draw Eclipse
Chapter 5: OpenCV – Arithmetic Operation
Lecture 1: Not Arithmetic Operation
Lecture 2: AND Arithmetic Operation
Lecture 3: OR Arithmetic Operation
Lecture 4: Image Blending
Chapter 6: OpenCV – Threshold and Blurring
Lecture 1: Global Threshold
Lecture 2: Adaptive Thresholding
Lecture 3: Canny Edge Detection
Lecture 4: Image Blurring
Chapter 7: OpenCV – Contours and its Properties
Lecture 1: Find Contours in an Image
Lecture 2: Area And Perimeter of Counters
Lecture 3: Fitting Shape on the Contours
Lecture 4: Check Point if Inside, Outside or on the Contours
Chapter 8: OpenCV – Image feature and Matcher
Lecture 1: SIFT – (Scale-Invariant Feature Transform)
Lecture 2: Feature Matching
Chapter 9: OpenCV – Common Problem
Lecture 1: Save Images From Videos
Lecture 2: Make Video From Images
Lecture 3: Image from Pillow to OpenCV
Chapter 10: Conclusion
Lecture 1: Thank You
Instructors
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Pooja Dhouchak
Founder and CEO of FatheVision -
FatheVision AI
Now Computer Vision is easy to learn
Rating Distribution
- 1 stars: 0 votes
- 2 stars: 1 votes
- 3 stars: 4 votes
- 4 stars: 10 votes
- 5 stars: 48 votes
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