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OpenCV with Python
Parsa
Salamatian
Omar
Alam
Introduction
Computer Vision in 2022
- A.I. object recognition
- Computational photography
- Autonomous vehicles
- Security and Encryption
The leading computer vision library
• First version released in 2000 by Intel Research.
• Provides basic computer vision infrastructure.
• Libraries available for all major programming languages.
• Currently maintained by big research firms.
OpenCV
• The workshop will use the PyCharm IDE.
○ Feel free to use your preferred IDE
• OpenCV supports Python versions up to 3.10.
○ Download the latest version from python.org
Project Setup
Python + PyCharm installation
1.Install the latest version of Python
python.org
1.Do
2.Install the community version of
PyCharm
1.Do
2.I
3.Create a PyCharm Project
This is your
project name.
2.I
3.Install the opencv package on PyCharm
File > Settings > Project
> Python Interpreter
2.I
3.Install the opencv-python package on PyCharm
1.Download all files from the following GDrive folder and move them to the
project directory: Workshop Files
1.Use the Github for reference when following the workshop: Github Repo
Required Files
GDrive and Github
Basic OpenCV Concepts
Vision Pipeline
Example 1
• Multiple input sources
○ Webcam, Video, Image, Network etc.
• Setting parameters
○ API, Resolution, Brightness etc.
Video Inputs
Color Spaces
HSV, HSL, RGB
Examples 2 - 4
• Blur Algorithms
○ Blur, Gaussian Blur.
• Color Space Filters
○ HSV, HSL.
• Edge Detection
○ Concept, Canny.
Basic Pipeline Algorithms
- Binary Classification problem
- Input: Video/Image
- Output: 1 or 0
- 1 = Face found in input -> construct rectangular block around it
- 0 = No face found in input
- pre-trained on 1000’s of faces
- Not the most accurate algorithm, but very fast and relevant today
Haar Cascade
Viola-Jones Face Detection Technique
Resources
1)OpenCV Website
1)The Practical Applications of Mathematics in CS
1)how to use OpenCV and Python for computer vision
- Larry David

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OpenCV with Python