keras-yolov3 TypeError: Expected Ptr<cv::UMat> for argument '%s'

Question

keras-yolov3にて画像ファイルを入力後、実行すると以下が表示されます。
解決方法がわかりませんので、アドバイス頂けると幸いです。

実行手順
１．python yolo_video.py --image
２．実行すると以下のような表示がされるので，使用したい画像のパスを入力してenterを押せば処理が行われます．
３．Image detection mode
Ignoring remaining command line arguments: ./path2your_video,
2019-11-20 00:28:38.457780: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
model_data/yolo.h5 model, anchors, and classes loaded.
Input image filepath:
４．画像を指定し、実行すると以下のエラーが出力される
５．Traceback (most recent call last):
File "yolo_video.py", line 77, in <module>
detect_img(YOLO(**vars(FLAGS)))
File "yolo_video.py", line 19, in detect_img
cv2.imwrite(file_path + "_out" + ext, np.asarray(r_image)[..., ::-1])
TypeError: Expected Ptrcv::UMat for argument '%s'

＊line19,line77はプログラムの右端に記載してあります。

------開発環境------
python3.7
cuda10.0
cudnn7.7
tensorflow-gpu13.1
Keras 2.1.6
opencv-python 4.1.2.30
pillow 6.2.1
matplotlib 3.1.2
numpy 1.17.4

ーーーーーーーーーーーターミナル上のエラー　ーーーーーーーーーーーー
Traceback (most recent call last):
File "yolo_video.py", line 77, in <module>
detect_img(YOLO(**vars(FLAGS)))
File "yolo_video.py", line 19, in detect_img
cv2.imwrite(file_path + "_out" + ext, np.asarray(r_image)[..., ::-1])
TypeError: Expected Ptrcv::UMat for argument '%s'

-----プログラム-----
import sys,os
import argparse
from yolo import YOLO, detect_video
from PIL import Image
import numpy as np
import cv2

def detect_img(yolo):
while True:
img = input('Input image filepath:')
try:
image = Image.open(img)
except:
print('Open Error! Try again!')
continue
else:
r_image = yolo.detect_image(image)
file_path, ext = os.path.splitext(img)
[line19] cv2.imwrite(file_path + "_out" + ext, np.asarray(r_image)[..., ::-1])
r_image.show()
yolo.close_session()

FLAGS = None

if name == 'main':
# class YOLO defines the default value, so suppress any default here
parser = argparse.ArgumentParser(argument_default=argparse.SUPPRESS)
'''
Command line options
'''
parser.add_argument(
'--model', type=str,
help='path to model weight file, default ' + YOLO.get_defaults("model_path")
)

parser.add_argument(
    '--anchors', type=str,
    help='path to anchor definitions, default ' + YOLO.get_defaults("anchors_path")
)

parser.add_argument(
    '--classes', type=str,
    help='path to class definitions, default ' + YOLO.get_defaults("classes_path")
)

parser.add_argument(
    '--gpu_num', type=int,
    help='Number of GPU to use, default ' + str(YOLO.get_defaults("gpu_num"))
)

parser.add_argument(
    '--image', default=False, action="store_true",
    help='Image detection mode, will ignore all positional arguments'
)
'''
Command line positional arguments -- for video detection mode
'''
parser.add_argument(
    "--input", nargs='?', type=str,required=False,default='./video/video08.mp4',
    help = "Video input path"
)

parser.add_argument(
    "--output", nargs='?', type=str, default="",
    help = "[Optional] Video output path"
)

FLAGS = parser.parse_args()

if FLAGS.image:
    """
    Image detection mode, disregard any remaining command line arguments
    """
    print("Image detection mode")
    if "input" in FLAGS:
        print(" Ignoring remaining command line arguments: " + FLAGS.input + "," + FLAGS.output)

[line77] detect_img(YOLO(**vars(FLAGS)))
elif "input" in FLAGS:
detect_video(YOLO(**vars(FLAGS)), FLAGS.input, FLAGS.output)
else:
print("Must specify at least video_input_path. See usage with --help.")