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“Unknown layer type: net in function” when loading yolov3 using OpenCV's DNN library
OpenCV's clustering function cvKMeans2() - what is a type of cluster center in array?OpenCV's clustering function cvKMeans2() - why doesnt work when i use the centers parameterOpenCV Error: Bad argument <Unknown array type> in unknown function, file ......modulescoresrcmatrix.cpp, line 697Different matching results for opencv's descriptor_extractor_matcher when loading data from fileError when using two flags OpenCv's calibrateCamera functionOpenCV - Unknown array type in function cvarrToMatParsing the cfg file froom YOLO-Darknet in OpenCV DNNOpenCV unknown layer type running darknet detectopencv dnn load darknet unknow layer type sseProblems using cv::dnn::Layer cv::dnn::LayerFactory and cv::dnn::Net
.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty margin-bottom:0;
I am attempting to use Yolov3 using OpenCV's (4.0.1) DNN Library on MacOs in C++. I am trying to use cv::dnn::readNetFromDarknet to load the yolov3.cfg file but I am getting this error :
"(-212:Parsing error) Unknown layer type: net in function
'ReadDarknetFromCfgStream'"
I've made sure the yolov3.cfg that is within my project matches up with the one on the web https://github.com/pjreddie/darknet/blob/master/cfg/yolov3.cfg which it does. If I change " [net] " to something else for example " [layer] " then the error will change to :
"(-212:Parsing error) Unknown layer type: layer in function
'ReadDarknetFromCfgStream'"
Almost as if either the cfg file is wrong or opencv is not reading it correctly.
The start of the config file looks like this :
[net]
# Testing
# batch=1
# subdivisions=1
# Training
batch=64
subdivisions=16
width=608
height=608
channels=3
momentum=0.9
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1
learning_rate=0.001
burn_in=1000
max_batches = 500200
policy=steps
steps=400000,450000
scales=.1,.1
which is where I assume the problem is.
My code for loading the net is :
const char * pathStart = gGetRootAppPath();
pathEnd = "/yolo/yolov3.cfg";
std::string modelConfiguration = pathStart + pathEnd;
pathEnd = "/yolo/yolov3.weights";
std::string modelWeights = pathStart + pathEnd;
//set up the neural network
cv::dnn::readNetFromDarknet(modelConfiguration,modelWeights);
Any help would be much appreciated.
opencv yolo darknet
add a comment |
I am attempting to use Yolov3 using OpenCV's (4.0.1) DNN Library on MacOs in C++. I am trying to use cv::dnn::readNetFromDarknet to load the yolov3.cfg file but I am getting this error :
"(-212:Parsing error) Unknown layer type: net in function
'ReadDarknetFromCfgStream'"
I've made sure the yolov3.cfg that is within my project matches up with the one on the web https://github.com/pjreddie/darknet/blob/master/cfg/yolov3.cfg which it does. If I change " [net] " to something else for example " [layer] " then the error will change to :
"(-212:Parsing error) Unknown layer type: layer in function
'ReadDarknetFromCfgStream'"
Almost as if either the cfg file is wrong or opencv is not reading it correctly.
The start of the config file looks like this :
[net]
# Testing
# batch=1
# subdivisions=1
# Training
batch=64
subdivisions=16
width=608
height=608
channels=3
momentum=0.9
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1
learning_rate=0.001
burn_in=1000
max_batches = 500200
policy=steps
steps=400000,450000
scales=.1,.1
which is where I assume the problem is.
My code for loading the net is :
const char * pathStart = gGetRootAppPath();
pathEnd = "/yolo/yolov3.cfg";
std::string modelConfiguration = pathStart + pathEnd;
pathEnd = "/yolo/yolov3.weights";
std::string modelWeights = pathStart + pathEnd;
//set up the neural network
cv::dnn::readNetFromDarknet(modelConfiguration,modelWeights);
Any help would be much appreciated.
opencv yolo darknet
try to use absolute path, dont useconst char * pathStart = gGetRootAppPath()
– gameon67
Mar 28 at 0:16
thanks @gameon67, I've tried that but I'm still getting the same problem.
– Joachim.A
Mar 28 at 8:45
add a comment |
I am attempting to use Yolov3 using OpenCV's (4.0.1) DNN Library on MacOs in C++. I am trying to use cv::dnn::readNetFromDarknet to load the yolov3.cfg file but I am getting this error :
"(-212:Parsing error) Unknown layer type: net in function
'ReadDarknetFromCfgStream'"
I've made sure the yolov3.cfg that is within my project matches up with the one on the web https://github.com/pjreddie/darknet/blob/master/cfg/yolov3.cfg which it does. If I change " [net] " to something else for example " [layer] " then the error will change to :
"(-212:Parsing error) Unknown layer type: layer in function
'ReadDarknetFromCfgStream'"
Almost as if either the cfg file is wrong or opencv is not reading it correctly.
The start of the config file looks like this :
[net]
# Testing
# batch=1
# subdivisions=1
# Training
batch=64
subdivisions=16
width=608
height=608
channels=3
momentum=0.9
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1
learning_rate=0.001
burn_in=1000
max_batches = 500200
policy=steps
steps=400000,450000
scales=.1,.1
which is where I assume the problem is.
My code for loading the net is :
const char * pathStart = gGetRootAppPath();
pathEnd = "/yolo/yolov3.cfg";
std::string modelConfiguration = pathStart + pathEnd;
pathEnd = "/yolo/yolov3.weights";
std::string modelWeights = pathStart + pathEnd;
//set up the neural network
cv::dnn::readNetFromDarknet(modelConfiguration,modelWeights);
Any help would be much appreciated.
opencv yolo darknet
I am attempting to use Yolov3 using OpenCV's (4.0.1) DNN Library on MacOs in C++. I am trying to use cv::dnn::readNetFromDarknet to load the yolov3.cfg file but I am getting this error :
"(-212:Parsing error) Unknown layer type: net in function
'ReadDarknetFromCfgStream'"
I've made sure the yolov3.cfg that is within my project matches up with the one on the web https://github.com/pjreddie/darknet/blob/master/cfg/yolov3.cfg which it does. If I change " [net] " to something else for example " [layer] " then the error will change to :
"(-212:Parsing error) Unknown layer type: layer in function
'ReadDarknetFromCfgStream'"
Almost as if either the cfg file is wrong or opencv is not reading it correctly.
The start of the config file looks like this :
[net]
# Testing
# batch=1
# subdivisions=1
# Training
batch=64
subdivisions=16
width=608
height=608
channels=3
momentum=0.9
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1
learning_rate=0.001
burn_in=1000
max_batches = 500200
policy=steps
steps=400000,450000
scales=.1,.1
which is where I assume the problem is.
My code for loading the net is :
const char * pathStart = gGetRootAppPath();
pathEnd = "/yolo/yolov3.cfg";
std::string modelConfiguration = pathStart + pathEnd;
pathEnd = "/yolo/yolov3.weights";
std::string modelWeights = pathStart + pathEnd;
//set up the neural network
cv::dnn::readNetFromDarknet(modelConfiguration,modelWeights);
Any help would be much appreciated.
opencv yolo darknet
opencv yolo darknet
edited Mar 28 at 17:09
Joachim.A
asked Mar 27 at 13:59
Joachim.AJoachim.A
12 bronze badges
12 bronze badges
try to use absolute path, dont useconst char * pathStart = gGetRootAppPath()
– gameon67
Mar 28 at 0:16
thanks @gameon67, I've tried that but I'm still getting the same problem.
– Joachim.A
Mar 28 at 8:45
add a comment |
try to use absolute path, dont useconst char * pathStart = gGetRootAppPath()
– gameon67
Mar 28 at 0:16
thanks @gameon67, I've tried that but I'm still getting the same problem.
– Joachim.A
Mar 28 at 8:45
try to use absolute path, dont use
const char * pathStart = gGetRootAppPath()– gameon67
Mar 28 at 0:16
try to use absolute path, dont use
const char * pathStart = gGetRootAppPath()– gameon67
Mar 28 at 0:16
thanks @gameon67, I've tried that but I'm still getting the same problem.
– Joachim.A
Mar 28 at 8:45
thanks @gameon67, I've tried that but I'm still getting the same problem.
– Joachim.A
Mar 28 at 8:45
add a comment |
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try to use absolute path, dont use
const char * pathStart = gGetRootAppPath()– gameon67
Mar 28 at 0:16
thanks @gameon67, I've tried that but I'm still getting the same problem.
– Joachim.A
Mar 28 at 8:45