Dear Readers,

In this blog, I will try to explain how we can perform Number Plate Recognition in Python using Tesseract-OCR.

It can also be performed in Matlab using steps:
• Read the number plate.
• Resize the image to keep the aspect ratio same.
• Convert the image into a greyscale image.
• Apply a median filter to remove noise.
• Use a structuring element to perform morphological operations.
• Dilate the grey image with the structuring element
• Use morphological gradient for edge enhancement.
• Convert the class to double.
• Perform the convolution of the doubled image for brightening the images.
• Scale the intensity between 0…

Dear readers,

The top industries that use Javascript are:

  • finance: 7%
  • advertising and marketing: 5%
  • education: 5%
  • entertainment: 5%
  • business support and logistics: 4%
  • healthcare: 4%
  • retail: 3%
  • government: 2%
  • manufacturing: 2%

There were meaningful differences across industries in how and why people use JavaScript. There were also some clear commonalities, not all of which we’re going to mention. But from a statistician’s point of view, the questions where all the industries answered very similarly are useful because it indicates the differences in other questions are “real” and not just random variation.

Dear Readers,

This article includes the code and explaination for training model for face recognition, face detection and sending message through whatsapp once face is recognized.

Collection of Samples

import cv2
import numpy as np
face_classifier = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
# Load haar classifier
# Load functions

def face_extractor(img):
# Function detects faces and returns the cropped face
# If no face detected, it returns the input image

gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
# We convert our color image to grayscale format for faster calculation
faces = face_classifier.detectMultiScale(gray)
# Detecting face
if faces is ():
#Empty round…

Dear Readers,

This article is on how we can perform basic image operations in Python using OpenCV.

Basic knowledge of OpenCV is recommended.

Creating an image.

Confusion Matrix

Dear Readers,

This article is for those who want to understand the concept of Confusion Matrix in Cyber Security domain using a real life case study.

Confusion Matrix is used to describe the performance of a model by determining its accuracy, precision, etc. It uses predicted and actual values to find the accuracy, precision, recall of the algorithm.

Case : Intrusion Detection System

True Positive (TP) : The IDS detects that there is no malicious activity happening and it turns out to be true.

True Negative (TN) : The IDS detects that there is some kind of malicious activity happening…

Yash Lahoti

MLOps Enthusiast and an Avid Learner

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