Image processing training with Python

Image Processing with Python

Target audience
Anyone who want to perform image analysis with Python but have not received extensive training on the subject yet
Scope
Usage of Miniconda, Visual Studio, Git, GitHub repository,
Coding with Python; openCV, matplotlib, NumPy, sci-kit learn, MediaPipe and sounddevice libraries,
Image processing; Examining image pixels, colors and their mixtures, image resizing, threshold value management, image smoothing/sharpening methods, histogram analysis, preparing and detecting handwritten numbers step by step into the model with machine learning.
Method
All written codes are explained step by step through the videos, what has been learnt is transferred to the code through assignment, at the end of the training. The project gives the participant the opportunity to use what has been learnt in a new concept.

Training Content

1. Application installations
1. Creating syllabus and repo
1. Introduction to OpenCV
2. Shape operations
3. Threshold application
4. Blur application
5. Edge detection
6. Histogram operation
7. Creating a function
1. Hand detection input
2. Hand detection algorithm
3. Visualization of hand detection
1. Opening the camera and basic operations
2. Real-time hand detection
1. Introduction to machine learning
2. Recognizing the dataset
3. Pre-processing and decision tree algorithm
4. New data test and random forest algorithm
1. Introduction to deep learning
2. Recognizing the dataset
3. One hot encoding method
4. Establishing the CNN algorithm
5. Training and testing of the CNN algorithm
1. Summary
2. Assignment

Video Training
Online Training
On-site Training

Image Processing with Python

Training Content

Application Installations

Introduction

Data Preparation

Object Detection

Object Tracking

Machine Learning

Deep Learning

Wrap-up

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