Added Deepali_Kulshrestha_OpenCv Folder

Deepali_Kulshrestha_OpenCv/Module_summary.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "innocent-biology",
+   "metadata": {},
+   "source": [
+    "### Explain what ever you have understood in this module: atleast 100 words"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bound-continuity",
+   "metadata": {},
+   "source": [
+    "In this module I have learnt about different concept in computer vision like segmentation (learn how to implement marker-based</br>\n",
+    " image segmentation using water shed algorithm) ,contours( Mainly it is used in Object Detection) .</br>After that I had practically implemented the first project in this module i.e, Finding an object</br>  and mark it’s extreme points.In that given blog it demonstrates that how to  find extreme points along</br> a contour with OpenCV and Python.After that understanding the concept of shape detection (Finding specific patterns in image)</br> and learnt about the concept of face detection and description and various algorithm that is used for the face detection.</br> </br>Then understanding the haar classifier and use haar classifier algorithm in programming</br> on face and eye detection.\n",
+    "Learn about Flask ,WSGI,Jinja2 and how to install flask ,setFlask_App and run it then how to built ML Model using Flask and how it works.Next come to the</br>  second project of the module i.e, Face Detection Using OpenCV - used OpenCv modules and HaasarCodes</br> to identify the face from an camera feed and deploy it using Flask.\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}