49 lines
1.9 KiB
Python
49 lines
1.9 KiB
Python
# This is a demo of running face recognition on a Raspberry Pi.
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# This program will print out the names of anyone it recognizes to the console.
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# To run this, you need a Raspberry Pi 2 (or greater) with face_recognition and
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# the picamera[array] module installed.
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# You can follow this installation instructions to get your RPi set up:
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# https://gist.github.com/ageitgey/1ac8dbe8572f3f533df6269dab35df65
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import face_recognition
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import picamera
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import numpy as np
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# Get a reference to the Raspberry Pi camera.
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# If this fails, make sure you have a camera connected to the RPi and that you
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# enabled your camera in raspi-config and rebooted first.
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camera = picamera.PiCamera()
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camera.resolution = (320, 240)
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output = np.empty((240, 320, 3), dtype=np.uint8)
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# Load a sample picture and learn how to recognize it.
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print("Loading known face image(s)")
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obama_image = face_recognition.load_image_file("obama_small.jpg")
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obama_face_encoding = face_recognition.face_encodings(obama_image)[0]
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# Initialize some variables
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face_locations = []
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face_encodings = []
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while True:
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print("Capturing image.")
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# Grab a single frame of video from the RPi camera as a numpy array
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camera.capture(output, format="rgb")
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# Find all the faces and face encodings in the current frame of video
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face_locations = face_recognition.face_locations(output)
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print("Found {} faces in image.".format(len(face_locations)))
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face_encodings = face_recognition.face_encodings(output, face_locations)
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# Loop over each face found in the frame to see if it's someone we know.
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for face_encoding in face_encodings:
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# See if the face is a match for the known face(s)
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match = face_recognition.compare_faces([obama_face_encoding], face_encoding)
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name = "<Unknown Person>"
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if match[0]:
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name = "Barack Obama"
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print("I see someone named {}!".format(name))
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