
Explore the core and additional packages of the scientific Python ecosystem, including NumPy, SciPy, Matplotlib, SymPy, Pandas, IPython, and Jupyter, with scikit-image and scikit-learn for image processing and machine learning.
Explore scikit-image, a NumPy-based image processing library in the SciPy ecosystem. It provides user-friendly modules for transformations, thresholding, filtering, morphology, and segmentation.
Install Python 3 on a Windows computer by downloading the installer, running the installation wizard, and enabling command prompt access with admin privileges.
Verify the Python 3 environment on Windows by checking environment variables and the PATH, locating the installation directory, and launching Python from the command prompt to confirm the setup.
Set up a Raspberry Pi 4 headless by flashing Raspberry Pi OS with the imager, then enable wifi, hostname, and remote desktop access.
Learn to write and run a simple hello world program on Windows using the interpreter and command prompt, and understand the basics of compiling and executing.
Compare Raspberry Pi with MacBook Pro and a custom PC, highlighting power, price, and size trade-offs; learn when Raspberry Pi suits teaching, simple Python programs, data visualization, and light tasks.
Install NumPy and Matplotlib on Windows using admin command prompt and pip, then verify by importing numpy and matplotlib in Python.
Install PuTTY on Windows by downloading the correct 64-bit installer, running the setup with admin rights, adding PuTTY to the environment path, and verifying the installation in CMD.
Explore ndarrays in Python, mastering indexing and slicing across one-, two-, and three-dimensional arrays. Learn slicing techniques that simplify multi-dimensional data access and compare with C-style indexing.
Explore numpy constants by examining infinity, negative infinity, not a number, and zero representations, along with key mathematical and scientific constants like e and gamma, through hands-on demonstrations.
Explore matplotlib, the python visualization library that powers scientific data visualization with advanced and basic plotting, 3d capabilities, and a matlab-like pyplot interface.
Learn to generate numpy arrays with random integers using randint, specifying low, high, and size, and extend to multidimensional arrays for random noise applications.
Become a Master in Image Processing 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.
This is the most comprehensive, yet straight-forward course for the Image Processing and Computer Vision with Python 3 on Udemy! Whether you have never worked with Image Processing before, already know basics of Python, or want to learn the advanced features of scikit-image with Python 3, this course is for you! In this course we will teach you Scikit-image with Python 3, Jupyter, NumPy, and Matplotlib.
(Note, we also provide you PDFs and Jupyter Notebooks in case you need them)
With over 100 lectures and more than 12 hours of video this comprehensive course leaves no stone unturned in teaching you Image Processing with Python 3!
This course will teach you Image Processing 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, and Scikit-learn installed on your Windows computer and Raspberry Pi.
We cover a wide variety of topics, including:
Basics of Scientific Python Ecosystem
Basics of Digital Image Processing
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 Image Processing with NumPy and Matplotlib
Installation of Scikit-image
Reading and Displaying Images
Shapes
Transformations on images
Histogram Equalization
Thresholding
Filtering
Morphology
Improving Images
Feature Detection
Segmentation
Miscellaneous operations on images
and much more.....
You will get lifetime access to over 100 lectures plus corresponding PDFs, Image Datasets, and the Jupyter notebooks for the lectures!
So what are you waiting for? Learn Image Processing with Python 3 in a way that will advance your career and increase your knowledge, all in a fun and practical way!