Python 3 Advanced Computer Vision

Course

PYTHON 3 ADVANCED COMPUTER VISION

Category

Python Online Institute

Eligibility

Job Aspirants

Mode

Online and Offline Classes

Batches

Week Days and Week Ends

Duration :

1.5  hrs in weekdays and 3hrs during Weekend

Python What will you learn?

•How to work with Python Tool.
•What are the advantages of Python?
•A Beginner’s Guide to Python Coding from scratch
•Learn how to structure a large-scale project using Python.
•You will understand how to implement a Python job.
•Learn all the relevant skills needed to use Python efficiently
•Get straight to the point! Learn the basics of Python
•You will be able to do web development projects on your own.
•Learn and understand the fundamentals of Python and how to apply it to web development.

python 3 advanced computer vision Training Highlights

•Real-world skills + project portfolio
•Free technical support for students
•We assist on Internship on Real-Time Project 
•Create hands-on projects at the end of the course
• Greater productivity and increased workforce morale
•Hands On Experience – will be provided during the course to practice
•Curriculum based on course outlines defined by in-demand skills in Python.
•We help the students in building the resume boost their knowledge by providing useful Interview tips

Who are eligible for Python

•.Net Developer, SilverLight, MVC3, Entity Framework 4, WCF, SQL/PLSQL, c#, SQL Server 2008, HTML5, .Net
•Front End, Javascript, Computer Graphics, Html, Css, Problem Solving, CSS, Web Technologies, Design, Software Development, Full Stack Developer
•Java, Net, C#, Manual Testing, Automation Testing, Manual Testing With Healthcare, Android And Ios Developer
•QA Engineers, C++ Developers, Dot Net Developers, Mac Os Developers, Project Manager, Java Developers, Android Developers, IOS Developers
•Software Development, .net, java, Asp.net, Sql Server, database, Software Testing, javascript, Agile Methodology, Cloud Computing, html, application

PYTHON 3 ADVANCED COMPUTER VISION Topics

•Become a Master in Image Processing and Computer Vision with Python 3 and acquire employers’ one of the most requested skills of 21st Century! An expert level Image Processing and Computer Vision Professional can earn minimum $100000 (that’s five zeros after 1) in today’s economy.
•(Note, we also provide you PDFs and Jupyter Notebooks in case you need them)
•With over 105 lectures and more than 12 hours of video this comprehensive course leaves no stone unturned in teaching you Image Processing and Computer Vision with Python 3, NumPy, matplotlib, Scikit-image, and OpenCV!
•This course will teach you Image Processing and Computer Vision in a very practical manner, with every lecture comes a programming video and a corresponding Jupyter notebook that has Python 3 code! Learn in whatever manner is the best for you!
•We will start by helping you get Python3, NumPy, matplotlib, Jupyter, Scikit-image, and OpenCV installed on your Windows computer and Raspberry Pi.
•We cover a wide variety of topics, including:
•Basics of Scientific Python Ecosystem
•Basics of OpenCV
•Basics of NumPy and Matplotlib
•Installation of Python 3 on Windows
•Setting up Raspberry Pi
•Tour of Python 3 environment on Raspberry Pi
•Jupyter installation and basics
•NumPy Ndarrays
•Array Creation Routines
•Basic Visualization with Matplotlib
•Ndarray Manipulation
•Random Array Generation
•Bitwise Operations
•Statistical Functions
•Basics of Matplotlib
•Image Processing with NumPy and Matplotlib
•Installation of OpenCV on Windows and RPi
•OpenCV and Matplotlib
•OpenCV and webcam on Windows and RPi
•Getting Started with Scikit-image
•Advanced OpenCV and Scikit-image
•Combining OpenCV and Scikit-image for live webcam processing
•You will get lifetime access to over 105 lectures plus corresponding PDFs, Image Datasets, and the Jupyter notebooks for the lectures! 
•So what are you waiting for? Learn Computer Vision and Image Processing with Python 3 in a way that will advance your career and increase your knowledge, all in a fun and practical way!
•Who this course is for:
•Computer Vision and image Processing Professionals
•Data Science Professionals: Data Scientists and Data Engineers
•Robotics and Machine Vision Professionals
•AI and Machine Learning Professionals
•Scientists, Mathematicians, Physicists, and Engineers
•Python Developers and Programmers
•Managers and Business Professionals
•Anyone who wants to learn
•Objectives, Audience, and Prerequisites
•Course Topics Overview
•Please leave your feedback
•Scientific Python Ecosystem
•URLs of important projects in Scientific Python Ecosystem
•What is Digital Image Processing?
•What is Computer Vision
•Scikit-image
•Install Python 3 on Windows
•Python 3 installation on Windows
•Verify Python 3 environment on Windows
•Raspberry Pi and Python 3
•What is Raspberry Pi
•Unboxing of Raspberry Pi 3B+
•URLS for the Softwares used in the Setup
•Raspberry Pi Raspbian OS Setup Part 1
•Raspberry Pi Raspbian OS Setup Part 2
•Remote desktop with VNC
•Linux Commands used in the Section
•Install IDLE3 on Raspberry Pi Raspbian
•Python 3 on Raspberry Pi
•Python 3 Basics
•Hello World! on Windows
•Hello World! on Raspberry Pi
•Interpreter vs Script Mode
•IDLE
•Raspberry Pi vs PC
•PyPI and pip
•Python Package Index and pip
•pip on Windows
•pip3 on Raspberry Pi
•Installing NumPy and Matplotlib
•Install NumPy and Matplotlib on Windows
•Install NumPy and Matplotlib on Raspberry Pi
•Jupyter Notebook
•Jupyter and IPython
•Jupyter installation on Windows
•Jupyter installation on Raspberry Pi
•PuTTY
•Connecting to the Remote Jupyter Server
•A brief tour of Jupyter
•Commands used in the Section
•Getting Started with NumPy
•Introduction to NumPy
•Ndarrays, Indexing, and Slicing
•Ndarray Properties
•NumPy constants
•NumPy DataTypes
•Creation of Arrays and Matplotlib
•Ones and Zeros improved
•Matrices
•Matplotlib
•Numerical ranges visualized
•Random Sampling
•Array Manipulation
•Plotting in detail
•Single Line Plots
•Multiline Plots
•Grid, Axes, and Labels
•Color, Line, and Markers
•NumPy and Matplotlib for Image Processing
•Image Datasets
•Install pillow on Windows and Raspberry Pi
•Read, save, and display images with Matplotlib
•NumPy for Images
•Image Statistics
•Image Masks
•Image Channels
•Arithmetic Operations
•Logical Operations
•Histogram with NumPy and Matplotlib
•Getting Started with OpenCV
•Installation of OpenCV
•Read, display, and save images
•Draw Shapes
•Trackbar Applications
•Drawing Application
•Colorspace Conversion
•Working with Webcam
•Capture a still photo with webcam
•Live Video
•Resolution
•Video Recording
•Show FPS
•Playing back a video
•Track an object by color
•KMeans Clustering and Quantization
•KMeans
•KMeans for 1D and 2D data
•Scikit-image Installation on Windows PC and Raspberry Pi
•Install SciPy on Windows
•Install SciPy on Raspberry Pi
•Scikit-image Installation on Windows
•Scikit-image Installation on Raspberry Pi
•Installation instructions
•Scikit-image Basics
•Getting started
•Shapes Shapes
•Feature Detection
•Canny Edge Detection
•Harris Corner Detection
•Advanced Operations on images with scikit-image
•Scientific Images
•Marching Cubes
•Approximate and Subdivide Polygons
•Hough Transform for circles and ellipses
•Histogram Matching
•Hysteresis Thresholding
•Mean Filter
•Unsharp Masking
•Entropy
•DAISY Features
•Chan-vase Segmentation
•Niblack and Sauvola Segmentation
•Flood Fill
•Advanced Operations with OpenCV
•Optical Flow
•Background Subtraction
•Swirl on Live Video
•Segmentation on Live Video
•More Scikit-image
•Detecting Ridges
•Multiblock Local Binary Patterns for texture classification
•Computing Extremas
•Downloadable Contents
•Code Bundle