openvino_icnet_test.py

import sys
import cv2
import numpy as np
from PIL import Image
import time
from openvino.inference_engine import IENetwork, IEPlugin

model_xml='/opt/intel/computer_vision_sdk_2018.4.420/deployment_tools/model_optimizer/10_lrmodels/ICNet/FP32/semanticsegmentation_ICNet.xml'
model_bin='/opt/intel/computer_vision_sdk_2018.4.420/deployment_tools/model_optimizer/10_lrmodels/ICNet/FP32/semanticsegmentation_ICNet.bin'
net = IENetwork.from_ir(model=model_xml, weights=model_bin)
seg_image = Image.open("data/input/009649.png")
palette = seg_image.getpalette() # Get a color palette
index_void = 2 # Define index_void Back Ground
camera_width = 320
camera_height = 240
fps = ""
elapsedTime = 0

#plugin = IEPlugin(device="HETERO:MYRIAD,CPU")
#plugin.set_config({"TARGET_FALLBACK": "HETERO:MYRIAD,CPU"})
#plugin.set_initial_affinity(net)

#plugin = IEPlugin(device="MYRIAD")
plugin = IEPlugin(device="CPU")

plugin.add_cpu_extension("/home/alpha/inference_engine_samples_build/intel64/Release/lib/libcpu_extension.so")
exec_net = plugin.load(network=net)

input_blob = next(iter(net.inputs))        #input_blob = 'input'
out_blob   = next(iter(net.outputs))       #out_blob   = 'ResizeBilinear_19'
print(net.inputs[input_blob].shape)
h, w, c    = net.inputs[input_blob].shape  #h, w, c = 256, 512, 3

del net

cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FPS, 30)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, camera_width)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, camera_height)
time.sleep(1)

while cap.isOpened():
    t1 = time.time()
    #ret, frame = cap.read()
    #if not ret:
    #    break
    frame = cv2.imread('data/input/000003.jpg')
    prepimg = frame[:, :, ::-1].copy()
    prepimg = frame
    prepimg = Image.fromarray(prepimg)
    prepimg = prepimg.resize((512, 256), Image.ANTIALIAS)
    if prepimg.mode == "RGBA":
        prepimg = prepimg.convert("RGB")
    #prepimg = np.asarray(prepimg) / 255.0
    #print(np.asarray(prepimg).shape)
    #prepimg = prepimg.transpose((2, 0, 1)).reshape((1, c, h, w))

    t2 = time.perf_counter()
    exec_net.start_async(request_id=0, inputs={input_blob: prepimg})

    if exec_net.requests[0].wait(-1) == 0:
        outputs = exec_net.requests[0].outputs[out_blob] # (1, 19, 256, 512)

    print(outputs[0].shape)
    print("SegmentationTime = {:.7f}".format(time.perf_counter() - t2))
    outputs = outputs[0] # (256, 512, 19)
    outputs = np.argmax(outputs, axis=0) # (256, 512)
    print(outputs.shape)

    # View
    image = Image.fromarray(np.uint8(outputs), mode="P")
    image.putpalette(palette)
    image = image.convert("RGB")
    #image = image.resize((camera_width, camera_height)) # (320, 240)
    image = image.resize((512, 256)) # (512, 256)
    image.save("2.jpg")
    image = np.asarray(image)

    print("frame =", frame.shape)
    print("image =", image.shape)
    #image = 0.5 * frame + 0.5 * image
    sys.exit(0)

    cv2.putText(image, fps, (camera_width-180,15), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (38,0,255), 1, cv2.LINE_AA)
    cv2.imshow("Result", image)

    if cv2.waitKey(1)&0xFF == ord('q'):
        break
    elapsedTime = time.time() - t1
    fps = "(Playback) {:.1f} FPS".format(1/elapsedTime)

cv2.destroyAllWindows()
del exec_net
del plugin