The Art Of Electronics

 Hello there! Welcome to another blog. In this blog you are going to learn to detect iris using OpenCv python. Here is the video in case you missed it. So, let's get started. We will start by importing the necessary libraries. import cv2 import numpy as np Now, let us import the face and eye classifier files and set the camera resolution as follows. eye = cv2.CascadeClassifier( 'haarcascade_eye.xml' ) face = cv2.CascadeClassifier( 'haarcascade_frontalface_alt.xml' ) Kernal = np.ones(( 3 , 3 ) , np.uint8) #Declare kernal for morphology cap = cv2.VideoCapture( 0 ) cap.set(cv2.CAP_PROP_FRAME_WIDTH , 320 ) ##Set camera resolution cap.set(cv2.CAP_PROP_FRAME_HEIGHT , 240 ) In a while loop let us capture an image frame, flip it(in case your camera captures inverted images) and convert it into a gray scale image. ret , frame = cap.read() ##Read image frame frame = cv2.flip(frame , + 1 ) ##Flip the image in case your camera...

 Hello friends! Welcome to the last post on Image Editing Software. In this post, you will be learning how to apply color filters to an image. We will be doing this using the OpenCV library package. You can also check out the video below.  So let's get started. We will start by importing Opencv and Numpy to our code.  import cv2 import numpy as np And now we will start writing the callback methods for applying filters. Let us start with the  yellowButton_callback() method.  def yellowButton_callback (): opencvImage = cv2.cvtColor(np.array(originalImage) , cv2.COLOR_RGB2BGR) opencvImage[: , : , 0 ] = 20 global outputImage outputImage = Image.fromarray(cv2.cvtColor(opencvImage , cv2.COLOR_BGR2RGB)) dispayImage(outputImage) Alright. Let us understand the above code line by line. To apply a color filter I have to manipulate the image array. So I need the image in an array form. np.array(originalImage) converts the image that we read using the PI...

Hello Friends! Let us continue our development of Image editing software. In this tutorial, we will add radio buttons to our GUI. These radio buttons will be used to apply different types of color filters to the image. Check out the video below. Let us start by creating a new frame for radio buttons and let us anchor it to the north side. Frame3 = tk.Frame(window , height = 20 ) Frame3.pack( anchor =tk.N) Now, let's add radio buttons to this frame. We will be creating 5 radio buttons (pink, orange, blue, yellow, none) and pack them using the grid. yellowButton = tk.Radiobutton(Frame3 , text = "Yellow" , width = 20 , value = 1 , command =yellowButton_callback) yellowButton.grid( row = 0 , column = 0 ) blueButton = tk.Radiobutton(Frame3 , text = "Blue" , width = 20 , value = 2 , command =blueButton_callback) blueButton.grid( row = 0 , column = 1 ) orangeButton = tk.Radiobutton(Frame3 , text = "Orange" , width = 20 , value = 3 , command =orangeButton_call...

 Hello friends! Let us continue developing our GUI of image editing software. You can check out the previous post by clicking here , where we have learned to create a window and add a few buttons to it. In this post, we will be adding sliders to our GUI which will be used to adjust the brightness and contrast of the image. You can check out the video below. We will continue developing our previous code. For placing the sliders we will use another frame. For creating the frame use the code below.  Frame2 = tk.Frame(window , height = 20 ) Frame2.pack( anchor =tk.NW) Frame2 will be holding the sliders of brightness and contrast adjustments. We have anchored the Frame2 to the northwest corner in our window. Let us now create the sliders for our window.  brightnessSlider = tk.Scale(Frame2 , label = "Brightness" , from_ = 0 , to = 2 , orient =tk.HORIZONTAL , length =screen_width , resolution = 0.1 , command =brightness_callback) brightnessSlider.pack...

Hello Friends! We are going to develop an Image Editing Software in python. We will be using various libraries like Tkinter, PIL, and OpenCV. We will be developing several features like brightness adjustment, contrast adjustment, applying various filters on the image, etc. So why wait? Let's get started. Make sure to check out the video below before starting. We will start by designing the GUI and later on, we will add the required functionalities to it for image editing. In this tutorial, we will be creating a window that will hold 3 buttons(Import, Save, Close). To create the GUI we will start by importing the Tkinter in our python file as shown below. import tkinter as tk To create a window we will have to call a method called tk.Tk(). window = tk.Tk() So the window is ready. But if you run the above code, you won't see anything appearing on the screen. This is because the program has finished execution. You will have to add a loop to hold the window on the screen. For that,...

In this blog, you will learn how to make an object disappear in a video in python using the OpenCV library.  Check out the demo below. So let's get started.  We will start by importing the required libraries  and define a variable to capture the video from my webcam. import cv2 import numpy as np cap = cv2.VideoCapture( 0 ) Now, start capturing the image frames from the camera and save the first frame in a variable called replace_image . But why we did this? Keep Reading. ret , frame = cap.read() frame = cv2.flip(frame , + 1 ) ##Mirror image frame replace_image = frame ##live image to replace with Let's write a while loop to capture the image frames continuously. while ( 1 ): ret , frame = cap.read() ##Read image frame frame = cv2.flip(frame , + 1 ) ##Mirror image frame if not ret: ##If frame is not read then exit break if cv2.waitKey( 1 ) == ord ( 's' ): ##While loo...

Hello guys. Today we will learn a pattern matching algorithm in python using the OpenCV library. Check out the video below to get a gist of what we are going to build. I have black and white grid patterns with white as background and black foreground. As usual, we will start by first importing the required libraries and define a variable to capture the video from my webcam. import cv2 import numpy as np cap = cv2.VideoCapture( 0 ) Now, we write a while loop and capture the image frames. Also, we need to mirror the frames so that we can see it right. while 1 : ret , frame = cap.read() ##Read image frame frame = cv2.flip(frame , + 1 ) ##Mirror image frame if not ret: ##If frame is not read then exit break if cv2.waitKey( 1 ) == ord ( 's' ): ##While loop exit condition break In the third part, we have to convert the image frames into a binary image. But why binary images?  You must ask. 1. ...