The code below is for facial recognition on OpenCV using the Jetson Nano.I’ve installed the DLib 19.24.2 Library and need help incorporating the DLib Library on the code below:
import face_recognition
import cv2
import os
import pickle
import time
print(cv2.__version__)
Encodings=[]
Names=[]
with open('train.pkl','rb') as f:
Names=pickle.load(f)
Encodings=pickle.load(f)
font=cv2.FONT_HERSHEY_SIMPLEX
cam= cv2.VideoCapture(1)
while True:
_,frame=cam.read()
frameSmall=cv2.resize(frame,(0,0),fx=.25,fy=.25)
frameRGB=cv2.cvtColor(frameSmall,cv2.COLOR_BGR2RGB)
facePositions=face_recognition.face_locations(frameRGB,model='cnn')
allEncodings=face_recognition.face_encodings(frameRGB,facePositions)
for (top,right,bottom,left),face_encoding in zip(facePositions,allEncodings):
name='Unkown Person'
matches=face_recognition.compare_faces(Encodings,face_encoding)
if True in matches:
first_match_index=matches.index(True)
name=Names[first_match_index]
top=top*4
right=right*4
bottom=bottom*4
left=left*4
cv2.rectangle(frame,(left,top),(right, bottom),(0,0,255),2)
cv2.putText(frame,name,(left,top-6),font,.75,(0,0,255),2)
cv2.imshow('Picture',frame)
cv2.moveWindow('Picture',0,0)
if cv2.waitKey(1)==ord('q'):
break
cam.release()
cv2.destroyAllWindows()
The code above gives a really low output video frame rate(about ~1fps) on the Jetson nano, need help incorporating the DLib library on the code above.
Also, how can I improve the output video frame rate on the Jetson Nano? I wish to achieve a outut video frame rate of about 25-30FPS on the Jetson nano, kindly please suggest how I can achieve this.
Kindly please help.