Changed the README file

Author: Lashuk1729

Computer Vision/Face Detection/README.md

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+# Face Detection
+
+## Aim
+
+The aim of the program given is to detect object of interest(face) in real time and to keep tracking of the same object. This is a simple example of how to detect face in Python.
+
+
+## Purpose
+
+- The purpose is to Build A Real-Time Face Algorithm used to identify faces in an image or a real time video.
+- The algorithm uses edge or line detection features proposed by Viola and Jones in their research paper “Rapid Object Detection using a Boosted Cascade of Simple Features” published in 2001.
+
+
+## Short description of package/script
+
+- Face Recognition is a technology in computer vision. In Face recognition / detection we locate and visualize the human faces in any digital image.
+- The __OpenCV GitHub repository__ has the models stored in XML files, and can be read with the OpenCV methods.
+- These include models for face detection, eye detection, upper body and lower body detection, license plate detection etc.
+- In this project, I applied face detection to some photos from Harry Potter using OpenCV with Python.
+
+
+## Workflow of the Project
+
+![Professor Snape](./images/Flow_FaceDetection_OpenCV.jpg)
+
+For the classier, we have used packages contain Haar cascade files. cv2.data.haarcascades
+
+## Detailed explanation of script, if needed
+
+If code is not explainable using comments, use this sections to explain your script
+
+
+## Setup instructions \& Execution
+
+1. Make sure you have Python 3.7 and a text editor installed.
+2. Install the required packages using pip install -r requirements.txt.
+3. In the main directory Run `python3 face_detection.py` or `python face_detection.py`.
+4. Enter the path of the file.
+
+
+## Sample Test Cases
+
+Some Results of the program:
+
+![Harry Potter](./images/harry.png)
+
+![Professor Snape](./images/snape.png)
+
+
+## Author(s)
+
+Kushal Borkar

Computer Vision/Face Detection/face_detection.py

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+import os
+import cv2
+
+# cascades: https://github.com/opencv/opencv/tree/master/data/haarcascades
+face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
+
+
+def read_file(image_path):
+    if os.path.isfile(image_path):
+        img = cv2.imread(image_path)
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        return True, img, gray
+
+    else:
+        return False, False
+
+
+while(True):
+    input_path = str(input("Enter the path of the file: "))
+    val, img, gray = read_file(input_path)
+    if val == True:
+        break
+
+rects = face_cascade.detectMultiScale(gray, scaleFactor=1.05,
+                                            minNeighbors=10, minSize=(30, 30),
+                                            flags=cv2.CASCADE_SCALE_IMAGE)
+
+
+# loop over the bounding boxes
+for (x, y, w, h) in rects:
+	# draw the face bounding box on the image
+	cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
+
+
+# show the output image
+cv2.imshow("Image", img)
+cv2.waitKey(0)

Computer Vision/Face Detection/images/Flow_FaceDetection_OpenCV.jpg

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+opencv_python==4.5.1.48