Merge pull request #183 from Lashuk1729/main

Added Face Detection Algorithm using Haar Cascade

Author: prathimacode-hub

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

Computer Vision/Face Detection/images/harry.png

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+# Face Detection with Haar Cascade
+
+---
+
+Face detection is one of the fundamental applications used in face recognition that determines the locations and sizes of human faces in arbitrary (digital) images. It detects only the facial features.
+
+---
+
+### What is Haar Cascade?
+
+It is an Object Detection 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.
+
+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.
+
+---
+
+### Steps
+
+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.
+
+---
+
+### Results
+
+Some Results of the program:
+
+![Harry Potter](./images/harry.png)
+
+![Professor Snape](./images/snape.png)

Computer Vision/Face Detection/images/snape.png

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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)