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pt.py
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pt.py
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import cv2
import os
import numpy as np
####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]
################################
cam = cv2.VideoCapture(0)
face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml")
dataset_path = "./FaceData/"
labels = []
class_id = 0
names = {}
face_data = []
for fx in os.listdir(dataset_path):
if fx.endswith(".npy"):
names[class_id] = fx[:-4]
print("Loading File ",fx)
data_item = np.load(dataset_path+fx)
face_data.append(data_item)
#createLabels
target = class_id * np.ones((data_item.shape[0],))
labels.append(target)
class_id+=1
X = np.concatenate(face_data,axis = 0) # 24,30000
Y = np.concatenate(labels,axis = 0) # 24,30000
trainset = np.concatenate((X,Y.reshape(-1,1)),axis = 1)
while True:
ret,frame = cam.read()
if ret == False:
print("Something went wrong")
continue
key_pressed = cv2.waitKey(1)&0xFF
if(key_pressed == ord('q')):
break
faces = face_cascade.detectMultiScale(frame,1.3,5)
if(len(faces) == 0):
cv2.imshow("Video",frame)
continue
for face in faces:
x,y,w,h = face
face_section = frame[y-10:y+10+h,x-10:x+10+w]
face_section = cv2.resize(face_section,(100,100))
cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,255),2)
pred = knn(trainset,face_section.flatten())
name = names[int(pred)]
cv2.putText(frame,name,(x,y-20),cv2.FONT_HERSHEY_SIMPLEX,1,(255,0,0),2,cv2.LINE_AA)
#cv2.putText(frame,name,(x,y-10),cv2.FONT_HERSHEY_SIMPLEX,1,(255,0,0),2,cv2.LINE_AA)
cv2.imshow("Video",frame)
cam.release()
cv2.destroyAllWindows()