start_live_feed.py

'''

Running The Spatiotemporal autoencoder on live webcam field


run python3 start_live_feed.py 'path_to_model' to start the feed and processing





Author: Harsh Tiku


'''





import cv2
from model import load_model
import numpy as np 
# from scipy.misc import imresize
from PIL import Image
from test import mean_squared_loss
from keras.models import load_model
import argparse



parser=argparse.ArgumentParser()

# parser.add_argument('modelpath',type=str)

parser.add_argument('model.py')

args=parser.parse_args()

modelpath=args.modelpath


vc=cv2.VideoCapture(0)
rval=True
print('Loading model')
model=load_model(modelpath)
print('Model loaded')

threshold=0.1
while True:
	imagedump=[]
	for i in range(10):
		rval,frame=vc.read()
		frame=Image.fromarray(frame).resize(size=(227,227,3))

		#Convert the Image to Grayscale


		gray=0.2989*frame[:,:,0]+0.5870*frame[:,:,1]+0.1140*frame[:,:,2]
		gray=(gray-gray.mean())/gray.std()
		gray=np.clip(gray,0,1)
		imagedump.append(gray)


	imagedump=np.array(imagedump)

	imagedump.resize(227,227,10)
	imagedump=np.expand_dims(imagedump,axis=0)
	imagedump=np.expand_dims(imagedump,axis=4)


	print('Processing data')

	output=model.predict(imagedump)



	loss=mean_squared_loss(imagedump,output)


	if loss>threshold:
		print('Anomalies Detected')