Ravindra Naik

Things to note for Local SEO optimization SEO for local business is really important and it’s been proved over the last couple of years. From the last couple of years, it has become really easy to find neighborhood businesses or products nearby, thereby creating a shift in user’s intent and search pattern. Things to keep in Mind for Local SEO A couple of years ago, for a person searching for the coffee shop from Jubilee hills, would have been “Coffee shops in Jubilee hill” in Google. But of late people have stopped giving in their location and trend of “near me” search query has risen. Now the same person searching for a coffee shop would have been searching for “Coffee shops near me” in Google. And Google fetches Coffee shop nearby his location. Hence it validates the point, now is the time to optimize both off site and on site strategies for local SEO. Here are few things to keep in mind for optimization for local SEO: Title and Meta Tags: Title and Meta tags stil

Here is how you can implement Face detection with Python and  OpenCV  in less than 25 lines of code: Face detection with Python and OpenCV Install OpenCV. Now download the code from  repo Now Let's break down the code # Get user supplied values imagePath   =   sys . argv [ 1 ] cascPath   =   sys . argv [ 2 ] The above lines takes image and cascade as input. The default cascade will help in detecting image with OpenCV. # Create the haar cascade faceCascade   =   cv2 . CascadeClassifier ( cascPath ) Now we create a cascade, this loads the face cascade into memory for its use. Cascade is just an XML which contains data to detect faces. # Read the image image   =   cv2 . imread ( imagePath ) gray   =   cv2 . cvtColor ( image ,   cv2 . COLOR_BGR2GRAY ) Here we read the image and convert it into Grayscale. A lot of operations in OpenCV are done in GrayScale. # Detect faces in the image faces   =   faceCascade . detectMultiScale (   gray ,  

Face detection with OpenCV OpenCV is the most popular library for computer vision. Originally written in C/C++, it now provides bindings for Python. OpenCV uses machine learning algorithms to search for faces within a picture. For something as complicated as a face, there isn’t one simple test that will tell you if it found a face or not. Instead, there are thousands of small patterns/features that must be matched. The algorithms break the task of identifying the face into thousands of smaller, bite-sized tasks, each of which is easy to solve. These tasks are also called  classifiers . For something like a face, you might have 6,000 or more classifiers, all of which must match for a face to be detected (within error limits, of course). But therein lies the problem: For face detection, the algorithm starts at the top left of a picture and moves down across small blocks of data, looking at each block, constantly asking, “ Is this a face? … Is this a face? … Is this a face ?” Si

Launching a new website yet, then hold on for a second. Here is the SEO checklist for new launching website: SEO Checklist for website Keyword and Url map:  The first thing to do would be keyword research and create a list which maps all the keywords to that content present in targeting URLs. The URL /seo-checklist-for-new-website, target keyword would be "SEO checklist" and page title would be "SEO checklist for the new website". If you have an important keyword which you have not targeted or if you have an URL which you have not targeted then do so. This will help when you do rank tracking and also on your on-page optimization too. Accessibility and UX: Firstly, one needs to check if all the pages and content of the website is accessible to search engines or not. You can use Google search console or OnPage.org to do a basic check on all the pages and make sure that you don't have duplicate content, that you don't have pages that have no c