In this blog, I will share the way I implement this paper.

I will follow the below path in explaining this whole work.

  1. Problem statement
  2. Source of data
  3. About data
  4. Losses we use
  5. Preparing data for detection
  6. Preparing data for recognition
  7. Training detection model and recognition model
  8. Making pipeline
  9. Showing results
  10. Conclusion
  11. Profile
  12. References

1. Problem statement

Here we have to detect the text region from any image(containing text), this image could be of anything with a different background. After detecting an image we have to recognize it also.

FOTS full form is Fast oriented text spotting. This is the case-study for detecting…

Here I will share how I solved this problem.

So let’s start — -

Here is the path, which I will pick and explain one by one.

  1. Introduction
  2. Business Problem
  3. Mapping to ML/DL problem
  4. Understanding the data
  5. First cut solution
  6. EDA
  7. Feature Engineering
  8. Modelling
  9. Results
  10. Conclusions and Future Work
  11. Profile
  12. References

Let’s dive in and understand each section.

1. Introduction —

Mercari is the shopping app of japan. They want to suggest prices to sellers, but this is not easy, so they want a system or algo which suggests prices for products automatically. …

In this blog we will learn about Mean, Median, Mode.

we will understand these three topics through this data.
Pizza Prices Data

In this post we will know about data and its type.

Data is collection of any information, the information can be anything.
For example-collection of students name in the class.

Data can be classify in two main ways — Types of Data and Measurement level

There are two types of Data — Categorical and Numerical.

Categorical data describes groups or any name. For example — car brands-audi,tata,mercedes etc.
Numerical Data describes any numeric value, means any number.
There are two types of Numerical Data — Discrete and Continuous.

Discrete means any finite number.In other words we can say that there…

Hello, In this post we will know about Selection Bias.
So, First we will focus on name Selection Bias, selection means selecting or choosing from something and bias means partiality.
So whole term selection bias means selecting anything with partiality.

For example, Suppose your college teacher is selecting a team for a cricket match and he selects all batsman or all bowler, So here your teacher is biasing in selecting the team, So due to this selection your team can lose the match.

From the above example one thing is confirmed that the selection bias is problem.This problem also occurs…

So In this blog we will create CSV files from the other file.
So let’s move on topic —

Let’s see the file from which we will make the csv file.
you can download the file from here. Download the file.

let’s start —


Suppose we have array or list [2,4,7,8,2,3,9] and you are searching for a value in this list.So what you would do.

In this algorithm we take a value and compare with all elements in the list one by one, if value exists we return found neither not found.
So, we can compare the value one by one by for loop.

if SearchItem(a,4):
print('not found')

In the above code we are checking if SearchItem() function return true then the element exist neither element does not exist. In SearchItem() function we are passing list…

Kris Gage Pyth Agoras Opencv Funs

OPEN CV part 4

For part 3 click here.

In this blog we will understand about some arithmetic and bitwise operations on image with open cv. So let’s start —

First we will see how to add add two images in open cv —


open cv (part-3)

For part-2 click here and for part-1 click here.

In this part first I will show some handling mouse events on image and some on video also.

Now let’s start with lists of mouse events in OPEN CV —

evt=[i for i in dir(cv2) if 'EVENT' in i]

Here we are making list of events you can see events in output.

So, like first two parts we have to import cv2 so that we can work on it. Here we…

open cv (part-II)

You can read part-I here

In part 1 we learned about imread() method, imshow() method and showing images in window and destroying it by pressing any key so In this part I will not explain those lines. Let’s start — —

First we will see how to draw some shape or how to write text on image from OPEN CV. As you know first we import libraries for doing stuffs related to it so I am not going to tell it in every part but when to import new libraries i will explain you.

Here is code —


Currently working on Data Science.Python Developer(Django Framework)

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