import numpy as np
import cv2
import time

IM_SIZE = 224

print("LOADING....")
net = cv2.dnn.readNetFromCaffe('channel_pruning_VGG-16_3C4x.prototxt', 'channel_pruning_VGG-16_3C4x.caffemodel')
print("LOADED")

sum_t = 0
num_runs = 10
for i in range(num_runs):
    x_image = np.asarray(np.random.rand(IM_SIZE, IM_SIZE, 3), dtype=np.float32)
    t = time.time()
    inputBlob = cv2.dnn.blobFromImage(x_image)
    net.setInput(inputBlob)
    result = net.forward()
    sum_t += time.time()-t

print("Inference done in {}s".format(sum_t/num_runs))