openvino-ncs2-python-samples/async_api.py at master · decemberpei/openvino-ncs2-python-samples · GitHub

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#!/usr/bin/env python3

from openvino.inference_engine import IENetwork, IEPlugin
import cv2
import os
import time

model_dir = os.environ['HOME'] + "/model_downloader/object_detection/common/mobilenet-ssd/caffe/FP16/"
model_xml = model_dir + "mobilenet-ssd.xml"
model_bin = model_dir + "mobilenet-ssd.bin"
plugin = IEPlugin(device="MYRIAD")
net = IENetwork(model=model_xml, weights=model_bin)
input_blob = next(iter(net.inputs))
out_blob = next(iter(net.outputs))
n, c, h, w = net.inputs[input_blob].shape
exec_net = plugin.load(network=net, num_requests=2)

start_time = time.time()
current_inference, next_inference = 0, 1
# for test purpose only
image_number = 200
inferred_images = 0
for i in range(0, image_number):
    image = cv2.imread("/opt/intel/computer_vision_sdk/deployment_tools/demo/car.png")
    image = cv2.resize(image, (w, h))
    image = image.transpose((2, 0, 1))
    image = image.reshape((n, c, h, w))
    exec_net.start_async(request_id=current_inference, inputs={input_blob: image})
    if exec_net.requests[next_inference].wait(-1) == 0:
        inferred_images = inferred_images + 1
        res = exec_net.requests[next_inference].outputs[out_blob]
        #print("infer result: label:%f confidence:%f left:%f top:%f right:%f bottom:%f" %(res[0][0][0][1], res[0][0][0][2], res[0][0][0][3], res[0][0][0][4], res[0][0][0][5], res[0][0][0][6]))
    duration = time.time() - start_time
    print("inferred frames: " + str(inferred_images) + ", average fps: " + str(inferred_images/duration) +"\r", end = '', flush = False)
    current_inference, next_inference = next_inference, current_inference
# one more inference result left to check
if exec_net.requests[next_inference].wait(-1) == 0:
    inferred_images = inferred_images + 1
    res = exec_net.requests[next_inference].outputs[out_blob]
    #print("infer result: label:%f confidence:%f left:%f top:%f right:%f bottom:%f" %(res[0][0][0][1], res[0][0][0][2], res[0][0][0][3], res[0][0][0][4], res[0][0][0][5], res[0][0][0][6]))
    duration = time.time() - start_time
    print("inferred frames: " + str(inferred_images) + ", average fps: " + str(inferred_images/duration) +"\r", end = '', flush = False)

print()

del exec_net
del net
del plugin