block3.python

import sys 
import os 
import cv2
import numpy as np 
import logging as log 
from openvino.inference_engine import IECore 
import time 
 
model_xml = 'model.xml' 
model_bin = 'model.bin' 
 
ie = IECore() 
 
net = ie.read_network(model=model_xml, weights=model_bin) 

input_blob = next(iter(net.input_info)) out_blob = next(iter(net.outputs)) net.batch_size = 1 
 
n, c, h, w = net.input_info[input_blob].input_data.shape 
 
images = np.ndarray(shape=(n, c, h, w)) 
 
image = cv2.imread('dog.4001.jpg') image = cv2.resize(image, (w, h)) image = image.transpose((2, 0, 1)) images[0] = image 
 
exec_net = ie.load_network(network=net, device_name='CPU') res = exec_net.infer(inputs={input_blob: images}) 
 
res = res[out_blob] 
 
for i, probs in enumerate(res): 
    probs = np.squeeze(probs)     
    top_ind = np.argmax(probs) 
 
if(top_ind == 0):     
    print("Cat detected") 
elif(top_ind == 1): 
    print("Dog detected") 
else: 
    print("Failed to detect either a dog or a cat")