117 lines
3.5 KiB
Python
117 lines
3.5 KiB
Python
import os, sys, time
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import dlib
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import cv2
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import numpy as np
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import DBHelper
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import time
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import Upload_Thief
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def inference():
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try:
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import cPickle # Python 2
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except ImportError:
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import _pickle as cPickle # Python 3
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pwd = sys.path[0]
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PREDICTOR_PATH = pwd + '/Facial_models/shape_predictor_68_face_landmarks.dat'
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FACE_RECOGNITION_MODEL_PATH = pwd + '/Facial_models/dlib_face_recognition_resnet_model_v1.dat'
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SKIP_FRAMES = 1
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THRESHOLD = 0.4
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faceDetector = dlib.get_frontal_face_detector()
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shapePredictor = dlib.shape_predictor(PREDICTOR_PATH)
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faceRecognizer = dlib.face_recognition_model_v1(FACE_RECOGNITION_MODEL_PATH)
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index = np.load(pwd + '/Facial_models/index.pkl', allow_pickle=True)
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faceDescriptorsEnrolled = np.load(pwd + '/Facial_models/descriptors.npy')
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cam = cv2.VideoCapture(0)
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count = 0
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x1 = x2 = y1 = y2 = 0
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cond = False
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t = 0
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while DBHelper.get_power() == "on":
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t = time.time()
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success, im = cam.read()
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if not success:
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print('cannot capture input from camera')
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break
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if (count % SKIP_FRAMES) == 0:
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img = cv2.cvtColor(im, cv2.COLOR_BGR2RGB)
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faces = faceDetector(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
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for face in faces:
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shape = shapePredictor(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), face)
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x1 = face.left()
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y1 = face.top()
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x2 = face.right()
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y2 = face.bottom()
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faceDescriptor = faceRecognizer.compute_face_descriptor(img, shape)
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# dlib format to list
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faceDescriptorList = [m for m in faceDescriptor]
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# to numpy array
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faceDescriptorNdarray = np.asarray(faceDescriptorList, dtype=np.float64)
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faceDescriptorNdarray = faceDescriptorNdarray[np.newaxis, :]
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# Euclidean distances
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distances = np.linalg.norm(faceDescriptorsEnrolled - faceDescriptorNdarray, axis=1)
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# Calculate minimum distance and index of face
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argmin = np.argmin(distances) # index
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minDistance = distances[argmin] # minimum distance
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if minDistance <= THRESHOLD:
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label = DBHelper.get_firstname(index[argmin]) + "_" + DBHelper.get_lastname(index[argmin])
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cond = True
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else:
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label = 'unknown'
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cond = False
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# print("time taken = {:.3f} seconds".format(time.time() - t))
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cv2.rectangle(im, (x1, y1), (x2, y2), (0, 255, 0), 2)
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font_face = cv2.FONT_HERSHEY_SIMPLEX
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font_scale = 0.8
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text_color = (0, 255, 0)
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printLabel = '{} {:0.4f}'.format(label, minDistance)
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cv2.putText(im, printLabel, (int(x1), int(y1)), font_face, font_scale, text_color, thickness=2)
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cv2.imshow('img', im)
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k = cv2.waitKey(1) & 0xff
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if k == 27:
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break
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count += 1
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if cond:
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DBHelper.set_motor("on")
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DBHelper.set_alarm("off")
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time.sleep(1)
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elif not cond:
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DBHelper.set_motor("off")
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DBHelper.set_alarm("on")
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t += 1
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time.sleep(1)
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if t == 120:
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Upload_Thief.upload_thief_face()
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DBHelper.set_power("off")
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DBHelper.set_alarm("off")
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DBHelper.set_motor("off")
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cv2.destroyAllWindows()
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if __name__ == "__main__":
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inference()
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