47 lines
1.7 KiB
Python
47 lines
1.7 KiB
Python
# 这是一个在树莓派上运行人脸识别的案例
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# 本案例会在命令行控制面板上输出识别出的人脸数量和身份结果。
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# 你需要一个2代以上的树莓派，并在树莓派上安装face_recognition，并连接上picamera摄像头
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# 并确保picamera这个模块已经安装（树莓派一般会内置安装）
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# 你可以参考这个教程配制你的树莓派：
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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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# 你需要在sudo raspi-config中把camera功能打开
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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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# 载入样本图片（奥巴马和拜登）
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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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# 初始化变量
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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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# 以numpy array的数据结构从picamera摄像头中获取一帧图片
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camera.capture(output, format="rgb")
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# 获得所有人脸的位置以及它们的编码
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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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# 将每一个人脸与已知样本图片比对
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for face_encoding in face_encodings:
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# 看是否属于奥巴马或者拜登
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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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