Opencv Image Processing Python

It's used to process images, videos, and even live streams, but in this tutorial, we will process images only as a first step. You can interactively segment image data, compare image registration techniques, and batch-process large datasets. We’ll get to the command prompt, run our script with the image option and specify an image to classify:. Installation. The work has been implemented using Python (2. PDF | This book covers how to solve image processing problems using popular Python image processing libraries (such as PIL, scikit-image, python-opencv, scipy ndimage, and SimpleITK), machine. OpenCV Python Computer Vision. The actual code is less than 40 lines of python code, thanks to the terse syntax of python and now, I am sharing with you what I did. Mastering OpenCV 4 with Python: A practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3. OpenCV-Python Tutorials Documentation, Release 1 Additional Resources 1. It depends on the requirements of the application and your skills in a particular programming language. Learn more about Contrast Stretching using C++ and OpenCV: Image Processing and more Programming Techniques. I am trying to run a very simple opencv example with the following code:. Python is a widely used general-purpose, high-level programming language. Image Blending Exercises 1. x Python API package and the matplotlib package. Detailed Description. We have collected a list of Python libraries which can help you in image processing. What is Python, NumPy and OpenCV? Python is a programming language well suited for scientific computing. The library is written in C and C++ which runs on Linux, Windows and as well as on MAC OS X. OpenCV to handle computer vision and image processing. How to set resolution of video capture in python with Logitech c910 & c920. Finally, we get our desired Output image with watermark. So what if you want to use a webcam? OpenCV grabs each frame from the webcam and you can then detect faces by processing each frame. Let’s try this gender and age classifier out on some of our own images now. 7 and python 3. 6 (Freeware) [32 bit/64 bit]. But since your project is called "Classification of breast cancer images with deep learning", and you're not using deep learning, maybe you didn't pick the right. OpenCV (Python) for Computer Vision. Now let's read the image when want to detect its edges: # read the image image = cv2. scikit-image is a Python package dedicated to image processing, and using natively NumPy arrays as image objects. Image processing is done in software by applying numerical operations on the image data. imshow() cv2. OpenCV to handle computer vision and image processing. openCV is the computer vision library specially designed for c++ and later on ported to python support also. Image Processing with OpenCV Debayan Banerjee Co-founder, Uberlabs 2. Alright, so my post Getting Webcam Images with Python and OpenCV 2 was wrong! I did not fully understand how to read the OpenCV API documentation and instead of demonstrating how to capture an image with OpenCV 2, I just demonstrated a way to capture an image with OpenCV 1. The approach I took to cell detection was template-matching and edge detection based. Image Processing with Python Desert Py Meetup OpenCV-Python is the Python API of OpenCV Matplotlib if image is read with OpenCV. Posted under python opencv local binary patterns chi-squared distance In this tutorial, I will discuss about how to perform texture matching using Local Binary Patterns (LBP). In this section, we learn about the Image Segmentation methods and methods to extract region of interests (ROIs) or contours on which we can apply any type of image processing pipeline to work with the contours. In this series of OpenCV Python Examples, you will start to write Python programs to perform basic operations in Image Processing like reading an image, resizing an image, extracting the different color channels of the image and also working around with these color channels. As usual, we will start our code by importing the cv2 module. Face Detection and Image Processing using OpenCV and Python This week, you will learn how to use the Haar Cascade classifiers for detecting eyes and faces in images. Image processing is a CPU intensive task. I didn't add my image processing part. OpenCV functions used: cv2. 7), Open Source Computer Vision Library (OpenCV) and NumPy. This type of program is most commonly used for video and image analysis such as license plate reading, facial recognition, robotics, photo editing and more within C++, Python, C and Java. We will also discuss the basic of image processing and provide the detail explanation related to the OpenCV functions. 0 and Python 2. Most common image processing techniques have a solid mathematical background. Image Processing and Computer Vision with Python & OpenCV 3. 0 out of 5 stars 1. You will also build, train, and test your own custom image. I am trying to run my python code which is basically related to image processing and finding defects. VideoCapture: Cannot read from file. Explain the order of the three color values in OpenCV images. In this tutorial we will check how to flip an image, using Python and OpenCV. Welcome to another OpenCV tutorial. tile) Concatenate images with Python, Pillow; Add margins to the image with Python, Pillow like enlarging the. In this article, you’ll learn how to use a deep learning model to transfer painting. Originally written in C/C++, it now provides bindings for Python. It contains basic image processing capabilities, and convenient to use. Python & openCV image processing Posted at : 29 days ago; Share. waitKey() cv2. Today’s tutorial is a Python implementation of my favorite blog post by Félix Abecassis on the process of text skew correction (i. OpenCV is the leading open source library for computer vision, image processing and machine learning, and now features GPU acceleration for real-time operation. In this tutorial, we are going to see some more image manipulations using Python OpenCV. So, after a few hours of work, I wrote my own face recognition program using OpenCV and Python. HERE IS WHY YOU SHOULD ENROLL IN THIS COURSE: This course is your complete guide to practical image processing and computer vision tasks using Python. About pythonvision. OpenCV is a library of cross platform programming functions aimed at real time Computer Vision. Write a function which outputs all shapes in the input image as two-tone outputs, with a colored. In OpenCV, the image size (width, height) can be obtained as a tuple with the attribute shape of ndarray and the attribute size of PIL. It is mainly aimed at real time applications. A sample input…. Learn about the data and image types unique to OpenCV, and find out how to manipulate pixels and images. Conclusion: from the result we can see the effect of contrast stretching by using simple log transform using opencv and python. 6 (2010): 1635-1650. OPENCV TUTORIAL: IMAGE PROCESSING INTRODUCTION What is OpenCV? This might be the 'basic' question that comes first to your mind. Creating your own Haar Cascade OpenCV Python Tutorial – one object, two images. input image; the image can have any number of channels, which are processed independently, but the depth should be CV_8U, CV_16U, CV_16S, CV_32F or CV_64F. Image processing analytics has applications from processing a X-Ray to identifying stationary objects in a self driving car. Image Processing with OpenCV 1. Much of ROS makes use of 3D sensors and point-cloud data, but there are still many applications that use traditional 2D cameras and image processing. Given an image containing a rotated block of text at an unknown angle, we need to correct the text skew by: Detecting the block of text in the. This blog is a continuation of Basic Image Data Analysis Using Numpy and OpenCV - Part 1. scipy is a module that contains many functions for processing Photos. PDF | This book covers how to solve image processing problems using popular Python image processing libraries (such as PIL, scikit-image, python-opencv, scipy ndimage, and SimpleITK), machine. Image_Lib - contains common code files that is reused by most projects. Scikit-image is often compared to OpenCV, a collection of programs for computer vision that include live video. imread('C:\\Users\\Link\\Desktop\\image. CVIPtools, a complete GUI-based computer-vision and image-processing software environment, with C function libraries, a COM-based DLL, along with two utility programs for algorithm development and batch processing. os: We will use this Python module to read our training directories and file names. Conclusion: from the result we can see the effect of contrast stretching by using simple log transform using opencv and python. This tutorial was tested on Windows 8. Raspberry Pi for Computer Vision focuses on embedded CV and DL. Segmentation methods in image processing and analysis, MathWorks. Today’s tutorial is a Python implementation of my favorite blog post by Félix Abecassis on the process of text skew correction (i. In this article I have covered what an affine transformation is and how it can be applied to image processing using Python. In fact OPENCV is a collection of inbuilt image processing functions. OpenCV (Open Source Computer Vision) is a programming library of multiple functions designed to undertake tasks of image processing or tasks related to that. OpenCV is a great library for creating Computer Vision software using state-of-the-art techniques, and is freely available for Windows, Linux, Mac and even Android & iPhone. So what if you want to use a webcam? OpenCV grabs each frame from the webcam and you can then detect faces by processing each frame. With the SimpleBlobDetector, you can distinguish blobs in your image based on different parameters such as color, size, and shape. Image Source: DarkNet github repo If you have been keeping up with the advancements in the area of object detection, you might have got used to hearing this word 'YOLO'. Welcome to another OpenCV tutorial. To learn the basics of Image Processing refer -> Digital Image Processing (3rd Edition): Rafael C. One of the major image-processing concepts is reverse image querying (RIQ) or reverse image search. Image Processing with OpenCV 1. Weird result while finding angle. One of them is the PIL, and comes with the distribution Anaconda. Python provides lots of libraries for image processing, including − OpenCV − Image processing library mainly focused on real-time computer vision with application in wide-range of areas like 2D and 3D feature toolkits, facial & gesture recognition, Human-computer interaction, Mobile robotics, Object identification and others. This will require a lot of processing, though. Note that OpenCV uses BGR (Blue, Green, Red) so, if you load a colour image the array dimensions will be (width, heigh, channel), where channel 0 is blue, 1 is green and 2 is red. Ultimately, I'd like to use it to make a Blackjack playing Raspberry Pi robot. Pillow is an image manipulation and processing library whereas OpenCV is for computer vision. Hence when you are implementing your Image Processing algorithm, you algorithm needs to be highly efficient. Matching Features with ORB using OpenCV (Python code) going to do all the processing of the image on its gray scale version. NumPy can be downloaded from the Python Package Index(PyPI): $. OpenCV is a native cross-platform C++ Library for computer vision, machine learning, and image processing. Face detection using OpenCV and Python: A beginner's guide. There are many image processing packages for Python. OpenCV-Python is not only fast, since the background consists of code written in C/C++, but it is also easy to code and deploy (due to the Python wrapper in the. So, after a few hours of work, I wrote my own face recognition program using OpenCV and Python. OPENCV TUTORIAL: IMAGE PROCESSING INTRODUCTION What is OpenCV? This might be the 'basic' question that comes first to your mind. I am new to python. That depends on what you want to accomplish. First, you need to setup your Python Environment with OpenCV. The Raspberry Pi has a dedicated camera input port that allows users to record HD video and high-resolution photos. Batch Processing. OpenCV together with React Native enables you to process images on mobile devices (most likely you’d like to process images taken by your device’s camera). Getting single frames from video with python. A protip by abidrahmank about python, opencv, and image processing. We have already discussed the basics of CameraX here. It involves processing on large arrays. Two Days Workshop on Image Processing using OpenCV and Python; More Views. Mastering OpenCV 4 with Python: A practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3. So today, we'll see how to run OpenCV image processing on live camera feed. Saturday Jul 08, 2017 When you load an image using OpenCV, it. OpenCV is a highly optimized library with focus on real-time applications. Source code and compiled samples are now available on GitHub. Image processing is a CPU intensive task. For python it is the best use of api for computer vision and image processing. The objective of this post is to explain how to read and display an image with Python and OpenCV. This course offers Python developers a detailed introduction to OpenCV 3, starting with installing and configuring your Mac, Windows, or Linux development environment along with Python 3. You will then do a variety of hands-on labs that will teach you how to perform license plate recognition using the Tesseract OCR, colour quantization, image compression, and image. Convert BGR and RGB with Python, OpenCV (cvtColor) Crop a part of the image with Python, Pillow (trimming) Composite two images according to a mask image with Python, Pillow; Concatenate images with Python, OpenCV (hconcat, vconcat, np. Practical Python and OpenCV is a gentle intro to the world of computer vision and image processing through the OpenCV library. Use C++ with OpenCV and cvBlob to perform image processing and object tracking on the Raspberry Pi, using a webcam. 0 out of 5 stars 1. Python & openCV image processing Posted at : 29 days ago; Share. Hence when you are implementing your Image Processing algorithm, you algorithm needs to be highly efficient. pip install OpenCV for Python. If you already have jupyter notebook or an IDE with which you can run python & OpenCV installed, just skip to Execution. In this post. Learn about the data and image types unique to OpenCV, and find out how to manipulate pixels and images. OpenCV Linking Guide First, install OpenCV library and link it with C compiler ( I am using Microsoft Visual studio in Windows platform). For this example, we will be using the OpenCV library. It involves processing on large arrays. e, the input and output of the processing are both images, computer vision is an interdisciplinary field dealing with how a computer can be made to understand or gain high-level insights or information from a digital image or a video. Extracting a ROI (Region of Interest) using OpenCV and Python is not so hard as it could may sound. It has C++, C, and Python. Weird result while finding angle. A protip by abidrahmank about python, opencv, and image processing. js image processing software. Steps: Fetch all the image file names using glob; Read all the images using cv2. I am learning image processing using opencv in windows. ☞ A Complete Machine Learning Project Walk-Through in Python ☞ Top 10 Algorithms for Machine Learning Newbies ☞ Machine Learning: how to go from Zero to Hero ☞ Python Tutorial: Image processing with Python (Using OpenCV) ☞ Computer Vision Using OpenCV ☞ OpenCV Python Tutorial - Computer Vision With OpenCV In Python. OpenCV on Wheels. OpenCV alternatives and similar libraries Based on the "Image Processing" category. OpenCV functions used: cv2. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language. OpenCV is a library of cross platform programming functions aimed at real time Computer Vision. Getting started. Image storage. We're going to learn in this tutorial how to track the movement of the eye using Opencv and Python. This course offers Python developers a detailed introduction to OpenCV 3, starting with installing and configuring your Mac, Windows, or Linux development environment along with Python 3. OpenCV is a free open source library used in real-time image processing. While image processing deals with image-to-image transformations i. OPENCV TUTORIAL: IMAGE PROCESSING INTRODUCTION What is OpenCV? This might be the 'basic' question that comes first to your mind. Image Blending Exercises 1. Creating your own Haar Cascade OpenCV Python Tutorial – one object, two images. In this process we use raspberry Pi, Python Programming for image processing using OpenCV and a surveillance camera to meet our need. OpenCV is an open-source image processing library that deploys on many platforms, including with C++, python, and mobile apps. I'm concerned about compatibility and performance of these lowlevel libraries on Raspbian and an ARM processor. Initially, we will use the USB web camera as the video input coupled with the HDMI output before looking at the benefits of using both HDMI in and out. scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications. Since the tools are open source, researchers can exploit the freedom and possibilities of expansion. Detailed Description. 2 contains only dist-packages. destroyAllWindows() The code [crayon-5db2acc6f3311295340139/] Boilerplate code [crayon-5db2acc6f3319432953149/] Where to next? Open Multiple Images with OpenCV in Python. One of them is the PIL, and comes with the distribution Anaconda. import cv2 Then we. "Enhanced local texture feature sets for face recognition under difficult lighting conditions. Here, the method of acquiring the image size (width, height) will be described. OpenCV Python Computer Vision. In this video, we will learn how we can perform visual object recognition using CNNs and we will also implement the project for scene understanding and an automatic labelling from images. We’re going to discuss how to put text on images. Often there would be a need to read images and display them if required. Let’s start. Raspberry Pi for Computer Vision focuses on embedded CV and DL. We can do image processing, machine learning, etc using OpenCV. Open up your favorite code editor, create a new file named find_books. The top advantages of. We often face the problems in image detection and classification. Python Project Examples for Gender and Age Detection. In this article, I will go through some basic building blocks of image processing, and share some code and approaches to basic how-tos. com, a blog all about computer vision, image processing, and building image search engines. We're going to discuss how to put text on images. But what if we want to process the image files without using any external library like OpenCV. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. imread("little_flower. It's used to process images, videos, and even live streams, but in this tutorial, we will process images only as a first step. Now let's read the image when want to detect its edges: # read the image image = cv2. It contains basic image processing capabilities, and convenient to use. 7 contains dist-packages and site-packages while python 3. waitKey() cv2. This repository is a collection of all things fun in image processing achieved with opencv and python. Table of Contents Random Forest Regression Using Python Sklearn From Scratch Recognise text and digit from the image with Python, OpenCV and Tesseract OCR Real-Time Object Detection Using YOLO Model Deep Learning Object Detection Model Using TensorFlow on Mac OS Sierra Anaconda Spyder Installation on Mac & Windows Install XGBoost on Mac OS. Welcome to my OpenCV Tutorial. It depends on the requirements of the application and your skills in a particular programming language. Cross-Platform C++, Python and Java interfaces support Linux, MacOS, Windows, iOS, and Android. Organizing information (eg, indexing databases of images and image sequences) 3. Python image processing libraries performance: OpenCV vs Scipy vs Scikit-Image feb 16, 2015 image-processing python numpy scipy opencv scikit-image. In this article, you will learn about the function library ‘OpenCV’ in a general way, along with a slight inclination to the programming language Python. This course offers Python developers a detailed introduction to OpenCV 3, starting with installing and configuring your Mac, Windows, or Linux development environment along with Python 3. Changing Colorspaces; Image Thresholding; Geometric Transformations of Images; Smoothing Images; Morphological Transformations; Image Gradients; Canny Edge Detection; Image Pyramids; Contours in OpenCV; Histograms in OpenCV. Learn about the data and image types unique to OpenCV, and find out how to manipulate pixels and images. Mastering OpenCV 4 with Python: A practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3. Alberto Powers on Python Program to Calculate. Welcome to this tutorial covering OpenCV. With careful experimental design, a digital camera or a flatbed scanner, in conjunction with some Python code, can be a powerful instrument in answering many different kinds of problems. 7 Alberto Fernández… 4. Building blocks. Projects and implementations are ever so on random topics but interesting ones nevertheless. OpenCV+Python:Part 2–Image Arithmetics. OpenCV has lot of inbuilt functions that you can use for your image processing and computer vision needs. OpenCV-Python is the Python API for OpenCV. waitKey() cv2. Mastering OpenCV 4 with Python: A practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3. About pythonvision. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. This type of program is most commonly used for video and image analysis such as license plate reading, facial recognition, robotics, photo editing and more within C++, Python, C and Java. OpenCV-Python is not only fast (since the background consists of code written in C/C++) but is also easy to code and deploy(due to the Python wrapper in foreground). In Image Processing applications, it is often necessary to know the size of an image that is loaded or transformed through various stages. OpenCV-Python. In this section, we learn about the Image Segmentation methods and methods to extract region of interests (ROIs) or contours on which we can apply any type of image processing pipeline to work with the contours. Gaussian Blur Syntax C++: void GaussianBlur(InputArray src, OutputArray dst, Size ksize, double sigmaX, double sigmaY=0, int borderType=BORDER_DEFAULT ). OpenCV has been a vital part in the development of software for a long time. In this tutorial we will learn about Computer Vision, how to install opencv in windows and learn some basic image processing using opencv like grey scale image, color space, histogram representation, RGB component of image etc. OpenCV-Python Tutorials. OpenCV Python - Read and Display Image In Computer Vision applications, images are an integral part of the development process. Read, display, and save images using OpenCV. It contains basic image processing capabilities, and convenient to use. processing for which the input is an image, such as a photograph or video frame; the output of image processing may be either an image or, a set of characteristics or parameters related to the image. I'm trying to detect the white dots in the following image using OpenCV and Python. I am using Opencv and python to detect shapes and then crop them. Let’s start. A sample input…. This tutorial describes a method for filling holes in a binary image in OpenCV ( C++ / Python ). Open source library for computer vision, image processing and machine learning Permissible BSD license Freely available (www. Detailed Description. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language. More luck that the guys like Adrian has done a great service by releasing both book and blog on a similar topic. In this article, I will go through some basic building blocks of image processing, and share some code and approaches to basic how-tos. Finally, we get our desired Output image with watermark. 7 and python 3. Perform simple image thresholding with NumPy array operations. I want to get this code on GPU (it works perfectly fine using CPU but takes time due to many libraries) and was suggested using opencv gpu accelerated library. In this tutorial, you will use a pre-trained Haar Cascade model from OpenCV and Python to detect and extract faces from an image. This paper explains a method simpler when compared to RADAR system using Doppler Shift. Practical OpenCV 3 Image Processing with Python; Practical OpenCV 3 Image Processing with Python; Practical OpenCV 3 Image Processing with Python; Machine Learning and Data Science Hands-on with Python and R; Machine Learning and Data Science Hands-on with Python and R; Machine Learning for OpenCV - Advanced Methods and Deep Learning. In fact OPENCV is a collection of inbuilt image processing functions. By the end of this course, users will have enough knowledge about Raspberry Pi, its components, basic Python programming, and execution of Image Processing applications in the real time scenario. I saw close to 90% CPU usage on my laptop. Given an image containing a rotated block of text at an unknown angle, we need to correct the text skew by: Detecting the block of text in the. Published by SuperDataScience Team. Python Project Examples for Gender and Age Detection. Browse other questions tagged image-processing computer-vision opencv or ask your own question. Note that OpenCV uses BGR (Blue, Green, Red) so, if you load a colour image the array dimensions will be (width, heigh, channel), where channel 0 is blue, 1 is green and 2 is red. The goal of Poisson image editing is to perform seamless blending of an object or a texture from a source image (captured by a mask image) to a target image. x in a way different from the example I…. For Image processing Python with OpenCV library is widely used. Note that you can do the reverse conversion, from dlib to OpenCV, using the toMat routine. OpenCV has lot of inbuilt functions that you can use for your image processing and computer vision needs. Often there would be a need to read images and display them if required. Python has a library that handles images such as OpenCV and Pillow (PIL). Introduction to OpenCV; Gui Features in OpenCV; Core Operations; Image Processing in OpenCV. Steps: Fetch all the image file names using glob; Read all the images using cv2. Mastering OpenCV 4 with Python: A practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3. Alberto Powers on Python Program to Calculate. Many image processing libraries, such as OpenCV and scikit-image come pre-installed with a number of de-noising algorithms, such as the total variation filter and the bilateral filter. This project is entirely based on what we read in Chapter 1 and 2. Matching Features with ORB using OpenCV (Python code) going to do all the processing of the image on its gray scale version. Installation and Usage. width and ksize. They apply a structuring element to an input image and generate an output image. Image Blending Exercises 1. x in a way different from the example I…. , "deskewing text") using OpenCV and image processing functions. Continue reading A guide to finding books in images using Python and OpenCV. OpenCV has been a vital part in the development of software for a long time. Much of ROS makes use of 3D sensors and point-cloud data, but there are still many applications that use traditional 2D cameras and image processing. In other words, image processing techniques are like building blocks that should be kept in mind when processing your images. In this article, I will go through some basic building blocks of image processing, and share some code and approaches to basic how-tos. 6 (Freeware) [32 bit/64 bit]. weighted(), Image overlay, image processing, live camera feed, opencv python on 18 Mar 2019 by kang & atul. This course offers Python developers a detailed introduction to OpenCV 3, starting with installing and configuring your Mac, Windows, or Linux development environment along with Python 3. Plus, you might not need to see all the tutorials depending upon your needs. Let's look at the pros and cons. Since 2001, Processing has promoted software literacy within the visual arts and visual literacy within technology. OpenCV (Image Analysis Technology ) 15. Practical OpenCV 3 Image Processing with Python SN 1 | EP 18 | Visual Object Recognition and Classification Using CNNs. 1 works with Python 2. OpenCV is used for all sorts of image and video analysis, like facial recognition and detection, license plate reading, photo editing, advanced robotic vision, optical character recognition, and a whole lot more. As an OpenCV novice, I searched Google to help me get started with the Python OpenCV code. Image Processing in OpenCV In this section you will learn different image processing functions inside OpenCV. I believe python bindings for OpenCV have contributed quite a bit to its popularity. Resize images with OpenCV. We are going to compare the performance of different methods of image processing using three Python libraries (scipy, opencv and scikit-image). The Python interface is still being developed whereas the C++ interface (especially with the new Mat class) is quite mature. Often there would be a need to read images and display them if required. FACE PRE-PROCESSING. Make sure you have these libraries installed! Finding books in images using Python and OpenCV. There are a couple of ways to do this in python to convert image to grayscale. The image has a circle inside and surrounded by gray color. A popular computer vision library written in C/C++ with bindings for Python, OpenCV provides easy ways of manipulating color spaces. OpenCV is a native cross-platform C++ Library for computer vision, machine learning, and image processing. Python has a library that handles images such as OpenCV and Pillow (PIL). Basic structures of images and how to manipulate them. Image Source: DarkNet github repo If you have been keeping up with the advancements in the area of object detection, you might have got used to hearing this word 'YOLO'. in internet Basic skills in Image Processing and Linear Algebra 16. OpenCV Python Tutorial. The Visualization ToolKit (VTK) is an open source, freely available software system for 3D computer graphics, image processing, and visualization used by thousands of researchers and developers around the world. Erosion and Dilation of images using OpenCV in python Morphological operations are a set of operations that process images based on shapes. Color detection using opencv has many advantages like, it allows the detection of a specific color in a livestream video content. Our hero today is Anaconda. Since you are "learning python and image processing with python", it seems you picked some related methods to explore, which is good. First, you need to setup your Python Environment with OpenCV. Hello, and welcome to the "Image processing with Python & Open-CV tutorial series".