How to run "ssd_object_detection.cpp"? - c++

Question

I'm trying to learn about objects detection with Deep Learning, and I'm actually trying to run the sample code "ssd_object_detection.cpp". In this code it's necessary to input the following parameters:
const char* params
= "{ help | false | print usage }"
"{ proto | | model configuration }"
"{ model | | model weights }"
"{ camera_device | 0 | camera device number}"
"{ video | | video or image for detection}"
"{ min_confidence | 0.5 | min confidence }";
Following the instructions of this code, I downloaded some pretrained models from this web: https://github.com/weiliu89/caffe/tree/ssd#models\n
So, I obtained a folder with the next archives:
deploy.prototxt
finetune_ssd_pascal.py
solver.prototxt
test.prototxt
train.prototxt
VGG_VOC0712Plus_SSD_300x300_ft_iter_160000.caffemodel
Then, I copied all this data to my project folder, and tried this code:
const char* params
= "{ help | false | print usage }"
"{ proto |test.prototxt| model configuration }"
"{ model |VGG_VOC0712Plus_SSD_300x300_ft_iter_160000.caffemodel| model weights }"
"{ camera_device | 0 | camera device number}"
"{ video |MyRoute...| video or image for detection}"
"{ min_confidence | 0.5 | min confidence }";
But at output I get the following error:
[libprotobuf ERROR
C:\build\master_winpack-build-win64-vc14\opencv\3rdparty\protobuf\src\google\protobuf\text_format.cc:298] Error parsing text-format opencv_caffe.NetParameter: 13:18: Message
type "opencv_caffe.TransformationParameter" has no field named
"resize_param". OpenCV Error: Unspecified error (FAILED:
ReadProtoFromTextFile(param_file, param).
Failed to parse NetParameter
file: test.prototxt) in cv::dnn::ReadNetParamsFromTextFileOrDie, file
C:\build\master_winpack-build-win64-vc14\opencv\modules\dnn\src\caffe\caffe_io.cpp,
line 1145
I used all the .prototxt archives, and tried other possible solutions, but I still cant run the example code.
Can someone explain me what parameters should I write in this code or what am i doing wrong?
Sorry about my bad English and thanks in advance.