Does opencv_dnn use gpu?

edit

I tried to run the code in Jetson GPU but I can't?

I just obtained 5 fps, this means that use CPU not GPU

this is my full code

from imutils.video import VideoStream
from imutils.video import FPS
import numpy as np
import argparse
import imutils
import time
import cv2
CLASSES = ["background", "aeroplane", "bicycle", "bird", "boat",
           "bottle", "bus", "car", "cat", "chair", "cow", "diningtable",
           "dog", "horse", "motorbike", "person", "pottedplant", "sheep",
           "sofa", "train", "tvmonitor"]
COLORS = np.random.uniform(0, 255, size=(len(CLASSES), 3))
print("[INFO] loading model...")
net = cv2.dnn.readNetFromCaffe('prototxt.txt', 'caffemodel')  # deep neural network ( dnn )
print("[INFO] starting video stream...")
vs = cv2.VideoCapture(0)
vs.release()
vs = cv2.VideoCapture(0)
time.sleep(2.0)
fps = FPS().start()

while True:

    ret, frame = vs.read()  # add ret,

    frame = imutils.resize(frame, width=400)

    (h, w) = frame.shape[:2]
    blob = cv2.dnn.blobFromImage(cv2.resize(frame, (300, 300)),
                                 0.007843, (300, 300), 127.5)

    net.setInput(blob)
    detections = net.forward()
    big_area = 0
    big_center = 320
    detected = 0
    # loop over the detections
    for i in np.arange(0, detections.shape[2]):

        confidence = detections[0, 0, i, 2]
        object_type = int(detections[0, 0, i, 1])

        if object_type == 15 and confidence > 0.2:  # it was if confidence > args["confidence"]:

            box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
            (startX, startY, endX, endY) = box.astype("int")

            label = "{}: {:.2f}%".format('person', confidence * 100)

            cv2.rectangle(frame, (startX, startY), (endX, endY), [0, 0, 255], 2)
            y = startY - 15 if startY - 15 > 15 else startY + 15
            cv2.putText(frame, label, (startX, y), cv2.FONT_HERSHEY_SIMPLEX, 0.5, [0, 0, 255], 2)

            rect_area = (endX - startX) * (endY - startY)

            detected = 1
            if rect_area > big_area:  # big_area and big_center are used so that the TurtleBot always tracks the closest person
                big_area = rect_area

    cv2.imshow("Frame", frame)
    key = cv2.waitKey(1) & 0xFF

    if key == ord("q"):
        break

    fps.update()

    # stop the timer and display FPS information
    fps.stop()

vs.release()
cv2.destroyAllWindows()

any ideas or suggestions?

thank you in advance