Hi, i want to minimize my face recognition system from PC to Jetson nano board.
i use this example code:
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import numpy as np
# This is a demo of running face recognition on live video from your webcam. It's a little more complicated than the
# other example, but it includes some basic performance tweaks to make things run a lot faster:
# 1. Process each video frame at 1/4 resolution (though still display it at full resolution)
# 2. Only detect faces in every other frame of video.
# PLEASE NOTE: This example requires OpenCV (the `cv2` library) to be installed only to read from your webcam.
# OpenCV is *not* required to use the face_recognition library. It's only required if you want to run this
# specific demo. If you have trouble installing it, try any of the other demos that don't require it instead.
# Get a reference to webcam #0 (the default one)
video_capture = cv2.VideoCapture(0)
# Load a sample picture and learn how to recognize it.
obama_image = face_recognition.load_image_file("obama.jpg")
obama_face_encoding = face_recognition.face_encodings(obama_image)
i change the code to can read from multiple images folder and some set up to work in jetson nano
Using Python 3.6, OpenCV, Dlib and the face_recognition module
Reading time: 17 min read
my system works fine on the PC. on a jetson nano, when encoding images from my dataset is done the process get killed before the webcam show up
does anyone know how to solve this problem? thanks in advance!