断言OpenCV Mobilenet SSD转发功能失败

此openCV代码用于检测由AirSim（虚幻插件）API流式传输的视频中的对象。该脚本能够检测网络摄像头视频中的对象，但是我想从client.simGetImage传递视频流，但我得到断言失败错误：

，第103行，检测次数= net.forward（）cv2.error：OpenCV（3.4.3）/io/opencv/modules/dnn/src/layers/convolution_layer.cpp:1021：错误：（-215：断言失败）函数“ forward”中的inputs [0]-> size [1]％blobs [0] .size [1] == 0

码：

from imutils.video import VideoStream
from imutils.video import FPS
import numpy as np
import argparse
import imutils
import time
import cv2
import setup_path 
import airsim
import sys

ap = argparse.ArgumentParser()
ap.add_argument("-p", "--prototxt", required=True,
    help="path to Caffe 'deploy' prototxt file")
ap.add_argument("-m", "--model", required=True,
    help="path to Caffe pre-trained model")
ap.add_argument("-c", "--confidence", type=float, default=0.2,
    help="minimum probability to filter weak detections")
args = vars(ap.parse_args())

cameraType = "scene"

cameraTypeMap = { 
 "depth": airsim.ImageType.DepthVis,
 "segmentation": airsim.ImageType.Segmentation,
 "seg": airsim.ImageType.Segmentation,
 "scene": airsim.ImageType.Scene,
 "disparity": airsim.ImageType.DisparityNormalized,
 "normals": airsim.ImageType.SurfaceNormals
}

client = airsim.MultirotorClient()
client.confirmConnection()
client.enableApiControl(True)
client.armDisarm(True)
client.takeoffAsync().join()

fontFace = cv2.FONT_HERSHEY_SIMPLEX
fontScale = 0.5
thickness = 2
textSize, baseline = cv2.getTextSize("FPS", fontFace, fontScale, thickness)
print (textSize)
textOrg = (10, 10 + textSize[1])
frameCount = 0
startTime=time.clock()
fps = 0


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(args["prototxt"], args["model"])


print("[INFO] starting video stream...")

time.sleep(2.0)
fps = FPS().start()

while True:    
    rawImage = client.simGetImage("3", cameraTypeMap[cameraType])
    if (rawImage == None):
        print("Camera is not returning image, please check airsim for error messages")
        sys.exit(0)
    else:
        png = cv2.imdecode(airsim.string_to_uint8_array(rawImage), cv2.IMREAD_UNCHANGED)



    frame = imutils.resize(png, 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()

    for i in np.arange(0, detections.shape[2]):
        confidence = detections[0, 0, i, 2]

        if confidence > args["confidence"]:
            idx = int(detections[0, 0, i, 1])
            box = detections[0, 0, i, 3:7] * np.array([w, h, w, h])
            (startX, startY, endX, endY) = box.astype("int")

            label = "{}: {:.2f}%".format(CLASSES[idx],
                confidence * 100)
            cv2.rectangle(frame, (startX, startY), (endX, endY),
                COLORS[idx], 2)
            y = startY - 15 if startY - 15 > 15 else startY + 15
            cv2.putText(frame, label, (startX, y),
                cv2.FONT_HERSHEY_SIMPLEX, 0.5, COLORS[idx], 2)

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

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

    fps.update()

fps.stop()
print("[INFO] elapsed time: {:.2f}".format(fps.elapsed()))
print("[INFO] approx. FPS: {:.2f}".format(fps.fps()))

cv2.destroyAllWindows()