Face recognition

import cv2
import numpy as np
import os

########## KNN CODE ############
def distance(v1, v2):

Eucledian

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

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

#Init Camera
cap = cv2.VideoCapture(0)

Face Detection

face_cascade = cv2.CascadeClassifier(path)

skip = 0
dataset_path = “C:/Users/J P PANDEY/Desktop/opencv/opencv-master/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.endswith(’.npy’):
#Create a mapping btw class_id and name
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)
if(len(faces)==0):
    continue

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 = names[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()
i m having error in this project.#Create Labels for the class
—> 59 target = class_id*np.ones((data_item.shape[0],))
60 class_id += 1
61 labels.append(target)

IndexError: tuple index out of range