face_detection.py

import cv2
import numpy as np
import os
################   KNN CODE   #######################

def distance(v1, v2):
	#Euclidian
	return np.sqrt(((v1-v2)**2).sum())

def knn(train,test,k=5):
	dist = []

	for i in range(train.shape[0]):
		#Get the vector and label
		ix = train[i, :-1]
		iy = train[i, -1]
		#Compute the distance from test point
		d = distance(test, ix)
		dist.append([d,iy])

	#sort based on distance and get top k
	dk = sorted(dist, key = lambda x: x[0])[:k]
	#Retrieve only the labels
	labels = np.array(dk)[:, -1]

	#Get frequencies
	output = np.unique(labels, return_counts=True)
	#Find max frequency and corresponding label
	index = np.argmax(output[1])
	return output[0][index]

	#######################################################


#Camera

cap = cv2.VideoCapture(0)

#Face Detection
face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml")

skip = 0
dataset_path = './data/'

face_data = []
labels = []

class_id = 0 #labels for the given file
names = {} #Mapping btw id - name

# Data Preparation
for fx in os.listdir(dataset_path):
	if fx.endsmith('.npy'):

		names[class_id] = fx[:-4]
		print("Loaded "+fx)

		data_item = np.load(dataset_path+fx)
		face_data.append(data_item)

		#Create Labels for the class
		target = class_id*np.ones((data_item.shape[0],))
		class_id += 1
		labels.append(target)

face_dataset = np.concatenate(face_data,axis=0)
face_labels = np.concatenate(labels,axis=0).reshape((-1,1))

print(face_dataset.shape)
print(face_labels.shape)

trainset = np.concatenate((face_dataset,face_labels),axis=1)
print(trainset.shape)

# Testing

while True:
	ret,frame = cap.read()
	if ret == False:
		continue

	faces = face_cascade.detectMultiScale(frame,1.3,5)

	for face in faces:
		x,y,w,h = face 
		
		#Get the face ROI
		offset = 10
		face_section = frame[y-offset:y+h+offset,x-offset:x+w+offset]
		face_section = cv2.resize(face_section,(100,100))

		#Predicted Label (out)
		out = knn(trainset,face_section.flatten())

		#Display on the screen the name and rectangle around it
		pred_name = name[int(out)]
		cv2.putText(frame,pred_name,(x-y-10),cv2.FONT_HERSHEY_SIMPLEX,1(255,0,0),2,cv2.LINE_AA)
        cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,255),2)
    cv2.imshow("Faces",frame)

    key = cv2.waitKey(1) & 0xFF
    if key==ord('q'):
    	break

cap.release()
cv2.destroyALlWindows()