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Hi, I am trying to run a pre trained Caffe model using cv::dnn, using C++.

The model has two inputs, of different sizes, and that seems to cause a problem (a model with a single input works fine)

I do succeed in running that network using Python's caffe, and I hoped I could run it from C++ using OpenCV DNN.

When I dive into the dnn code, it seems that when it loads the network it is aware of only the first input. It crashes when it tries to apply the blob shape of the first input instead of the blob shape of the second input.

Any advice about how to run a dnn network, imported Caffe, such that the network has two input of different sizes?

Thanks.

Hi, I am trying to run a pre trained Caffe model using cv::dnn, using C++.

The model has two inputs, of different sizes, and that seems to cause a problem (a model with a single input works fine)

I do succeed in running that network using Python's caffe, and I hoped I could run it from C++ using OpenCV DNN.

When I dive into the dnn code, it seems that when it loads the network it is aware of only the first input. It crashes when it tries to apply the blob shape of the first input instead of the blob shape of the second input.

Any advice about how to run a dnn network, imported Caffe, such that the network has two input inputs of different sizes?

Will be grateful for a code sample.

Thanks.

Hi, I am trying to run a pre trained Caffe model using cv::dnn, using C++.

The model has two inputs, of different sizes, and that seems to cause a problem (a model with a single input works fine)

I do succeed in running that network using Python's caffe, and I hoped I could run it from C++ using OpenCV DNN.

When I dive into the dnn code, it seems that when it loads the network it is aware of only the first input. It crashes when it tries to apply the blob shape of the first input instead of the blob shape of the second input.

Any advice about how to run a dnn network, imported Caffe, such that the network has two inputs of different sizes?

Will be grateful for a code sample.

Thanks.

Hi, I am trying to run a pre trained Caffe model using cv::dnn, using C++.

The model has two inputs, of different sizes, and that seems to cause a problem (a model with a single input works fine)

I do succeed in running that network using Python's caffe, and I hoped I could run it from C++ using OpenCV DNN.

When I dive into the dnn code, it seems that when it loads the network it is aware of only the first input. It crashes when it tries to apply the blob shape of the first input instead of the blob shape of the second input.

Any advice about how to run a dnn network, imported Caffe, such that the network has two inputs of different sizes?

Will be grateful for a code sample.

Thanks.