ERROR CudaFormNumpy

[XuanHoai02]

Hi Mr.dusty-nv @dusty-nv

When I install Jetson Inference and Jetson Utils, I get the error message:

jetson.utils -- compiled without NumPy array conversion support (warning)
jetson.utils -- if you wish to have support for converting NumPy arrays,
jetson.utils -- first run 'sudo apt-get install python-numpy python3-numpy'

Currently, I need to use cudaFromNumpy to convert NumPy arrays to CUDA so that my Jetson Nano can use them. Below are the hardware and code I am using."

Hardware:
Jetson nano - Jetpack 4.6 - Ubuntu 20.04
Camera raspberry pi v2

Code:

import cv2
import jetson_inference
import jetson_utils
import pyglet


class Point:
    def __init__(self, x, y):
        self.x = x
        self.y = y

    def getPoint(self):
        return (self.x, self.y)

    def translate(self, dx, dy):
        return Point(self.x + dx, self.y + dy)


class Zone:
    def __init__(self, top_left_point, bottom_right_point):
        # top-left point
        self.tl_point = top_left_point
        # bottom-right point
        self.br_point = bottom_right_point

    def getCenterPoint(self):
        return Point(
            (self.tl_point.x + self.br_point.x) / 2,
            (self.tl_point.y + self.br_point.y) / 2
        )

    def getWidth(self):
        return abs(self.tl_point.x - self.br_point.x)

    def getHeight(self):
        return abs(self.tl_point.y - self.br_point.y)

    def isOverlap(self, otherZone, adjustment=0):
        center = self.getCenterPoint()
        otherZoneCenter = otherZone.getCenterPoint()
        # distance of 2 center points
        distanceX = abs(otherZoneCenter.x - center.x)
        distanceY = abs(otherZoneCenter.y - center.y)
        return (
            distanceX < (self.getWidth() / 2 + otherZone.getWidth() / 2) - adjustment
        ) and (
            distanceY < (self.getHeight() / 2 + otherZone.getHeight() / 2) - adjustment
        )


def draw_warning_zone(warning_zone, img):
    FPS_string = "FPS {:.0f} FPS".format(net.GetNetworkFPS())
    top_left = warning_zone.tl_point.getPoint()
    bottom_right = warning_zone.br_point.getPoint()
    cv2.rectangle(img, top_left, bottom_right, (0, 255, 0), 2)
    cv2.putText(
        img, FPS_string, (30, 30), cv2.FONT_HERSHEY_DUPLEX, 1, (255, 0, 0), 2
    )


def play_sound(sound_name):
    WarningSound = pyglet.resource.media(sound_name)
    WarningSound.play()


net = jetson_inference.detectNet("ssd-mobilenet-v2", threshold=0.5)
cap = cv2.VideoCapture(
    'nvarguscamerasrc ! video/x-raw(memory:NVMM), width=940, height=480, format=(string)NV12, framerate=(fraction)60/1 ! nvvidconv flip-method=2 ! video/x-raw, format=(string)BGRx ! videoconvert ! video/x-raw, format=(string)BGR ! appsink',
    cv2.CAP_GSTREAMER,
)

count1 = 0
count2 = 0

while True:
    success, img = cap.read()
    imgCuda = jetson_utils.cudaFromNumpy(img)
    detections = net.Detect(imgCuda)

    warning_zone = Zone(Point(240, 130), Point(660, 490))
    draw_warning_zone(warning_zone, img)

    for d in detections:
        count2 += 1

        # position of detected object
        top_left_point = Point(int(d.Left), int(d.Top))
        bottom_right_point = Point(int(d.Right), int(d.Bottom))
        object_zone = Zone(top_left_point, bottom_right_point)

        center_x = int(d.Center[0])
        center_y = int(d.Center[1])

        # Draw cross-line of object
        cv2.line(
            img,
            (top_left_point.x, center_y),
            (bottom_right_point.x, center_y),
            (255, 0, 255),
            1,
        )
        cv2.line(
            img,
            (center_x, top_left_point.y),
            (center_x, bottom_right_point.y),
            (255, 0, 255),
            1,
        )
        # Draw center point
        cv2.circle(img, (center_x, center_y), 5, (255, 0, 255), 2)
        # Draw bounding box
        cv2.rectangle(
            img,
            (int(d.Left), int(d.Top)),
            (int(d.Right), int(d.Bottom)),
            (255, 0, 255),
            2,
        )
        # Put the object name in bounding box
        object_name = net.GetClassDesc(d.ClassID)
        cv2.putText(
            img,
            object_name,
            object_zone.tl_point.translate(5, 15).getPoint(),
            cv2.FONT_HERSHEY_DUPLEX,
            0.75,
            (255, 0, 255),
            2,
        )

        objectTypeId = d.ClassID

        if count2 == 40:
            count2 = 0
            if objectTypeId == 10:
                play_sound('ngatu.wav')
            elif objectTypeId == 13:
                play_sound('stop.wav')

        if warning_zone.isOverlap(object_zone, 5):
            count1 += 1
            cv2.putText(
                img,
                'NGUY HIEM',
                warning_zone.tl_point.getPoint(),
                cv2.FONT_HERSHEY_SIMPLEX,
                1,
                (5, 0, 255),
                3,
            )
            if count1 == 50:
                count1 = 0
                if objectTypeId == 1:
                    play_sound('nguoi.wav')
                elif objectTypeId in [2, 3, 4, 6, 10]:
                    play_sound('xe.wav')

    cv2.imshow("Detection frame", img)
    if cv2.waitKey(1) == ord('q'):
        break

cv2.destroyAllWindows()
cap.release()