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GOTURN Tracker results in errors #941

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bassamarshad opened this issue Jan 11, 2017 · 33 comments
Closed

GOTURN Tracker results in errors #941

bassamarshad opened this issue Jan 11, 2017 · 33 comments
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bug category: tracking

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@bassamarshad
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bassamarshad commented Jan 11, 2017 •
edited
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System information (version)
  • OpenCV => 3.2.0 & opencv_contrib 3.2
  • Operating System / Platform => Windows 10 64 Bit
  • Compiler => Visual Studio 2015
Detailed description

I have been trying to run the GOTURN tracker OpenCV implementation. I was firstly not able to find the goturn.prototxt and goturn.caffemodel (pretrained versions) on the opencv_extra github site, but was able to pull them from other github repos.

The program fails on execution with the following error, as soon as you select a ROI :

OpenCV Error: Assertion failed (input.dims() == 4 && (input.type() == CV_32F || input.type() == CV_64F)) in cv::dnn::ConvolutionLayerImpl::allocate, file E:\opencv3.2.0_sources\opencv_contrib-master\modules\dnn\src\layers\convolution_layer.cpp, line 90
OpenCV Error: Assertion failed (The following error occured while making allocate() for layer "conv11": input.dims() == 4 && (input.type() == CV_32F || input.type() == CV_64F)) in cv::dnn::ConvolutionLayerImpl::allocate, file E:\opencv3.2.0_sources\opencv_contrib-master\modules\dnn\src\layers\convolution_layer.cpp, line 90

I tried fixing this by updating the following lines of code in gtrtacker.cpp as follows :

dnn::Blob targetBlob = dnn::Blob(targetPatch);
dnn::Blob searchBlob = dnn::Blob(searchPatch);

TO

dnn::Blob targetBlob = dnn::Blob::fromImages(targetPatch);
dnn::Blob searchBlob = dnn::Blob::fromImages(searchPatch);

NOW,

I get a different error altogether that seems to have something to do with OpenCL, i get this error in the allocate() function in dnn.cpp ::

OpenCV Error: Assertion failed (dims <= 3) in cv::ocl::OpenCLAllocator::checkContinuous, file E:\opencv3.2.0_sources\3.2.0\opencv-3.2.0\modules\core\src\ocl.cpp, line 4899
OpenCV Error: Assertion failed (The following error occured while making forward() for layer "concat1": dims <= 3) in cv::ocl::OpenCLAllocator::checkContinuous, file E:\opencv3.2.0_sources\3.2.0\opencv-3.2.0\modules\core\src\ocl.cpp, line 4899
0x00007FFD18AC7788 (0x000000AAD070BBF8 0x000000AAD070BC00 0x000000AAD070BC08 0x00007FFD18D38CC1), RaiseException() + 0x68 bytes(s)
0x00007FFCF5F74582 (0x00007FFCDBED0000 0x000000AAD071BD50 0x0000021C8281D384 0x00007FFD18D30000), _CxxThrowException() + 0xC2 bytes(s)
0x00007FFCDC53A45A (0x0000000000000029 0x0000000000000000 0x0000000000000000 0x0000000000000000), cv::error() + 0x15A bytes(s), e:\opencv3.2.0_sources\3.2.0\opencv-3.2.0\modules\core\src\system.cpp, line 661 + 0x1E byte(s)
0x00007FFCDC53A5A0 (0x000000AAD071E3D0 0x0000000000000000 0x000000AAD071CB90 0x0000021C81BB9E64), cv::error() + 0x140 bytes(s), e:\opencv3.2.0_sources\3.2.0\opencv-3.2.0\modules\core\src\system.cpp, line 666 + 0x109 byte(s)
0x00007FFCDD71E173 (0x00007FFCDD71E0F0 0x000000AAD072ECD0 0x000000AAD072ECD0 0x0000000000000000), cv::dnn::Net::Impl::forwardLayer'::1'::catch$0() + 0x83 bytes(s), e:\opencv3.2.0_sources\3.2.0\opencv_contrib-3.2.0\modules\dnn\src\dnn.cpp, line 423 + 0x75 byte(s)
0x00007FFCF5F7C720 (0x00007FFCDD71E0F0 0x000000AAD071D1A8 0x0000000000000100 0x0000000000000000), __C_specific_handler() + 0x230 bytes(s)
0x00007FFCF5F72AE2 (0x0000000000000000 0x0000000000000000 0x000000AAD071E250 0x0000000000000000), __FrameUnwindFilter() + 0x432 bytes(s)
0x00007FFD1B94A193 (0x0000021CEA99E8B0 0x0000021CEAADBE08 0x0000021CE832FFE0 0x0000021C8222F7F0), RtlCaptureContext() + 0x3C3 bytes(s)
0x00007FFCDD601006 (0x0000021CEAADB720 0x0000021CEAADB748 0x0000000000000001 0x0000021CE8330008), cv::dnn::Net::Impl::forwardLayer() + 0x156 bytes(s), e:\opencv3.2.0_sources\3.2.0\opencv_contrib-3.2.0\modules\dnn\src\dnn.cpp, line 419 + 0x1B byte(s)
0x00007FFCDD600E4F (0x0000000000000000 0x000000AAD072ED90 0x0000021CE828CE70 0x0000021CE832FFE0), cv::dnn::Net::Impl::forwardAll() + 0x8F bytes(s), e:\opencv3.2.0_sources\3.2.0\opencv_contrib-3.2.0\modules\dnn\src\dnn.cpp, line 435
0x00007FFCDD600D7E (0x0000000000000046 0x000000AAD072EFA8 0x000000AAD072EEB0 0x0000000000000001), cv::dnn::Net::forward() + 0x9E bytes(s), e:\opencv3.2.0_sources\3.2.0\opencv_contrib-3.2.0\modules\dnn\src\dnn.cpp, line 503
0x00007FFCDD85CB5E (0x000000C3CD82EBAD 0x0000000000000001 0x00007FF679A68700 0x000000C3CD82EBAD), cv::gtr::TrackerGOTURNImpl::updateImpl() + 0xA5E bytes(s), e:\opencv3.2.0_sources\3.2.0\opencv_contrib-3.2.0\modules\tracking\src\gtrtracker.cpp, line 170 + 0x31 byte(s)
0x00007FF679A61FFB (0x00007FFD18E169F8 0x0000000000000000 0x00007FFD18E16A08 0x0000000000000000), main() + 0x5FB bytes(s), e:\tracking_goturn\tracking_goturn\source.cpp, line 168 + 0x1B byte(s)
0x00007FF679A632E8 (0x0000000000000000 0x0000000000000000 0x0000000000000000 0x0000000000000000), __scrt_common_main_seh() + 0x124 bytes(s), f:\dd\vctools\crt\vcstartup\src\startup\exe_common.inl, line 264 + 0x22 byte(s)
0x00007FFD1AC98364 (0x0000000000000000 0x0000000000000000 0x0000000000000000 0x0000000000000000), BaseThreadInitThunk() + 0x14 bytes(s)
0x00007FFD1B9070D1 (0x0000000000000000 0x0000000000000000 0x0000000000000000 0x0000000000000000), RtlUserThreadStart() + 0x21 bytes(s)

Not sure if there is a problem in my environment -_ i tried reverting builds to 3.1.0 , with no success. Or maybe I dont have the correct *.prototxt and *.caffemodel.

Am using the model and prototxt file given here :
https://github.com/opencv/opencv_extra/tree/c4219d5eb3105ed8e634278fad312a1a8d2c182d/testdata/tracking

Let me know what you guys think !

Steps to reproduce
@lenlen
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lenlen commented Jan 11, 2017

/cc @Auron-X

@Auron-X
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Auron-X commented Jan 13, 2017

@bassamarshad Thank you for detailed description of the bug in GOTURN. I will try to fix it ASAP

@dev681999
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dev681999 commented Jan 30, 2017 •
edited
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Well apparently using #include <opencv2/core/ocl.hpp> this and using heaocl::setUseOpenCL(false); like 1st line in main() solves the first problem mentioned.
Don't know about second one

@serhan-gul
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I'm getting exactly the same error on OpenCV 3.2.0 & opencv_contrib 3.2.0 (Ubuntu 16.04) after the selection of a bounding box:

OpenCV Error: Assertion failed (input.dims() == 4 && (input.type() == CV_32F || input.type() == CV_64F)) in allocate, file /home/guel/opencv_contrib/modules/dnn/src/layers/convolution_layer.cpp, line 87
OpenCV Error: Assertion failed (The following error occured while making allocate() for layer "conv11": input.dims() == 4 && (input.type() == CV_32F || input.type() == CV_64F)) in allocate, file /home/guel/opencv_contrib/modules/dnn/src/layers/convolution_layer.cpp, line 87
terminate called after throwing an instance of 'cv::Exception'
  what():  /home/guel/opencv_contrib/modules/dnn/src/layers/convolution_layer.cpp:87: error: (-215) The following error occured while making allocate() for layer "conv11": input.dims() == 4 && (input.type() == CV_32F || input.type() == CV_64F) in function allocate

Could it be related to the .prototxt and .caffemodel files from opencv_extra repository? I used the same files as basamarshad.

@Auron-X
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Auron-X commented Feb 20, 2017

Hello. I am still working on this bug, apparently there is some issue with dnn/tracking modules used in combo. For now you can try GOTURN outside of the OpenCV tracking API, using an example on my Github: https://github.com/Auron-X/GOTURN-Example
It also work on GPU ~100 FPS (on my GTX 1080) as the original paper stated

@LorenaGdL LorenaGdL mentioned this issue Feb 27, 2017
Merged
@allensu0314
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allensu0314 commented Mar 7, 2017 •
edited
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Thanks to @LorenaGdL for the PR about this bug, I didn't meet this issue with latest code.
But I met another error below:
OpenCV Error: Requested object was not found (Requested blob ".data1" not found) in cv::dnn::Net::setBlob, file C:\opencv3_2\opencv_contrib-master\modules\dnn\src\dnn.cpp, line 516
It seems that there's something wrong in gtrTracker.cpp line 167:

    dnn::Blob targetBlob = dnn::Blob::fromImages(targetPatch);
    dnn::Blob searchBlob = dnn::Blob::fromImages(searchPatch);

   (line 167) net.setBlob(".data1", targetBlob);
    net.setBlob(".data2", searchBlob);

I just download *.ptototxt and *.caffemodel, and put them to my VS program folder. Then add "path to test video" in Command Arguments. BTW, my main.cpp is below:

#include <opencv2/core/utility.hpp>
#include <opencv2/tracking.hpp>
#include <opencv2/videoio.hpp>
#include <opencv2/highgui.hpp>
#include <iostream>
#include <cstring>
using namespace std;
using namespace cv;
int main(int argc, char** argv){
	// show help
	if (argc<2){
		cout <<
			" Usage: tracker <video_name>\n"
			" examples:\n"
			" example_tracking_kcf Bolt/img/%04d.jpg\n"
			" example_tracking_kcf faceocc2.webm\n"
			<< endl;
		return 0;
	}
	// declares all required variables
	Rect2d roi;
	Mat frame;
	// create a tracker object
	Ptr<Tracker> tracker = Tracker::create("GOTURN");
	// set input video
	std::string video = argv[1];
	VideoCapture cap(video);
	// get bounding box
	cap >> frame;
	roi = selectROI("tracker", frame);
	//quit if ROI was not selected
	if (roi.width == 0 || roi.height == 0)
		return 0;
	// initialize the tracker
	tracker->init(frame, roi);
	// perform the tracking process
	printf("Start the tracking process, press ESC to quit.\n");
	for (;;){
		// get frame from the video
		cap >> frame;
		// stop the program if no more images
		if (frame.rows == 0 || frame.cols == 0)
			break;
		// update the tracking result
		tracker->update(frame, roi);
		// draw the tracked object
		rectangle(frame, roi, Scalar(255, 0, 0), 2, 1);
		// show image with the tracked object
		imshow("tracker", frame);
		//quit on ESC button
		if (waitKey(1) == 27)break;
	}
	return 0;
}

I don't know how to fix it, I will be appreciate if anyone can help me.

@xiaochus
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@ChaselS314 I have the same problem with you when i use GOTURN on latest code.

It seems that getPinByAlias() return a invalid variable pin when parser the '.data1' by splitPin() in dnn.cpp line 296&266:

    LayerPin getPinByAlias(const String &pinAlias, bool isOutPin = true)
    {
        LayerPin pin;
        String layerName, outName;
        splitPin(pinAlias, layerName, outName);

        pin.lid = (layerName.empty()) ? 0 : getLayerId(layerName);

        if (pin.lid >= 0)
            pin.oid = resolvePinOutputName(getLayerData(pin.lid), outName, isOutPin);

        return pin;
    }

Therefore， setBlob() raise an error about ‘.data1’.

void Net::setBlob(String outputName, const Blob &blob)
{
    LayerPin pin = impl->getPinByAlias(outputName);
    if (!pin.valid())
        CV_Error(Error::StsObjectNotFound, "Requested blob \"" + outputName + "\" not found");

    LayerData &ld = impl->layers[pin.lid];
    ld.outputBlobs.resize( std::max(pin.oid+1, (int)ld.requiredOutputs.size()) );
    ld.outputBlobs[pin.oid] = blob;
}

But I am not familliar with C++ so i do not know how to solve it.

@puneetdabulya
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Still getting this error on OpenCV 3.2 and Ubuntu 14.04, CUDA 8.0 Titan X GPU

@hacunamatada
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@ChaselS314, @xiaochus OpenCV Error: Requested object was not found (Requested blob ".data1" not found) in cv::dnn::Net::setBlob, file C:\opencv3_2\opencv_contrib-master\modules\dnn\src\dnn.cpp, line 516

The above error seems to be caused by the mismatching of the goturn.prototxt file.
I received the file from the following site.
Https://github.com/opencv/opencv_extra/tree/c4219d5eb3105ed8e634278fad312a1a8d2c182d/testdata/tracking
The following command merge four files into one.
cat goturn.caffemodel.zip.001 goturn.caffemodel.zip.002 goturn.caffemodel.zip.003 goturn.caffemodel.zip.004 > goturn.caffemodel
However, an error still occurs.
The error message is as follows.
OpenCV Error: Assertion failed ((bias && l-> blobs.size () == 2) || (! Bias && l-> b Lobs.size () == 1)) in cv :: dnn :: initConvDeconvLayerFromCaffe, file D: \ Program \ ope Ncv-dnn \ opencv_contrib-master \ opencv_contrib-master \ modules \ dnn \ src \ caffe \ layer_ Loaders.cpp, line 30

in my case : l-> blobs.size () is 0.

@isgursoy
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isgursoy commented Apr 5, 2017

[libprotobuf ERROR /opt/opencv/320deb/modules/dnn/3rdparty/protobuf/sources/protobuf-3.1.0/src/google/protobuf/text_format.cc:298] Error parsing text-format caffe.NetParameter: 7:1: Expected identifier, got: <
OpenCV Error: Unspecified error (FAILED: ReadProtoFromTextFile(param_file, param). Failed to parse NetParameter file: goturn.prototxt) in ReadNetParamsFromTextFileOrDie, file /opt/opencv/opencv_contrib-3.2.0/modules/dnn/src/caffe/caffe_io.cpp, line 1101
/opt/opencv/opencv_contrib-3.2.0/modules/dnn/src/caffe/caffe_io.cpp:1101: error: (-2) FAILED: ReadProtoFromTextFile(param_file, param). Failed to parse NetParameter file: goturn.prototxt in function ReadNetParamsFromTextFileOrDie

OpenCV Error: Unspecified error (GOTURN network loading error...) in cv::gtr::InitImpl, file gtrTracker.cpp, line 117
terminate called after throwing an instance of 'cv::Exception'
what(): gtrTracker.cpp:117: error: (-2) GOTURN network loading error... in function cv::gtr::InitImpl

@ahrnbom
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ahrnbom commented May 10, 2017 •
edited
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I get the following exotic errors when trying to run GOTURN via OpenCV:

OpenCV Error: Assertion failed ((bias && l->blobs.size() == 2) || (!bias && l->blobs.size() == 1)) in initConvDeconvLayerFromCaffe, file /opencv/opencv_contrib-3.2.0/modules/dnn/src/caffe/layer_loaders.cpp, line 27 OpenCV Error: Assertion failed (The following error occured while making allocate() for layer "conv11": (bias && l->blobs.size() == 2) || (!bias && l->blobs.size() == 1)) in initConvDeconvLayerFromCaffe, file /opencv/opencv_contrib-3.2.0/modules/dnn/src/caffe/layer_loaders.cpp, line 27 Traceback (most recent call last): File "pipeline.py", line 32, in <module> ok, bbox = tracker.update(im) cv2.error: /opencv/opencv_contrib-3.2.0/modules/dnn/src/caffe/layer_loaders.cpp:27: error: (-215) The following error occured while making allocate() for layer "conv11": (bias && l->blobs.size() == 2) || (!bias && l->blobs.size() == 1) in function initConvDeconvLayerFromCaffe

I am also a bit confused by the comment here https://github.com/opencv/opencv_contrib/blob/master/modules/tracking/samples/goturnTracker.cpp where it says

//Demo of GOTURN tracker
//In order to use GOTURN tracker, GOTURN architecture goturn.prototxt and goturn.caffemodel are > required to exist in root folder.
//There are 2 ways to get caffemodel:
//1 - Train you own GOTURN model using https://github.com/Auron-X/GOTURN_Training_Toolkit
//2 - Download pretrained caffemodel from https://github.com/opencv/opencv_extra

As the OpenCV Extra repo doesn't seem to contain any Goturn caffemodel, pretrained or otherwise. I downloaded it from http://cs.stanford.edu/people/davheld/public/GOTURN/trained_model/tracker.caffemodel instead. Is that is what is intended, or is it some other .caffemodel file one is supposed to use?

@LaurentBerger
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LaurentBerger commented Aug 3, 2017 •
edited by alalek
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I think something is weird in those lines. In my goturn.prototxt there is no .data1 and .data2 field only data1 and data2

if I delete point before data then exception given by @lChaselS314 doest not occur :

OpenCV Error: Requested object was not found (Requested blob ".data1" not found) in cv::dnn::Net::setBlob, file C:\opencv3_2\opencv_contrib-master\modules\dnn\src\dnn.cpp, line 516

my goturn.prototxt file is

name: "GOTURN"

input: "data1"
input_dim: 1
input_dim: 3
input_dim: 227
input_dim: 227

input: "data2"
input_dim: 1
input_dim: 3
input_dim: 227
input_dim: 227

layer {
  name: "conv11"
  type: "Convolution"
  bottom: "data1"
  top: "conv11"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    kernel_size: 11
    stride: 4
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu11"
  type: "ReLU"
  bottom: "conv11"
  top: "conv11"
}
layer {
  name: "pool11"
  type: "Pooling"
  bottom: "conv11"
  top: "pool11"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "norm11"
  type: "LRN"
  bottom: "pool11"
  top: "norm11"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "conv12"
  type: "Convolution"
  bottom: "norm11"
  top: "conv12"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 2
    kernel_size: 5
    group: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu12"
  type: "ReLU"
  bottom: "conv12"
  top: "conv12"
}
layer {
  name: "pool12"
  type: "Pooling"
  bottom: "conv12"
  top: "pool12"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "norm12"
  type: "LRN"
  bottom: "pool12"
  top: "norm12"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "conv13"
  type: "Convolution"
  bottom: "norm12"
  top: "conv13"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 384
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu13"
  type: "ReLU"
  bottom: "conv13"
  top: "conv13"
}
layer {
  name: "conv14"
  type: "Convolution"
  bottom: "conv13"
  top: "conv14"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 384
    pad: 1
    kernel_size: 3
    group: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu14"
  type: "ReLU"
  bottom: "conv14"
  top: "conv14"
}
layer {
  name: "conv15"
  type: "Convolution"
  bottom: "conv14"
  top: "conv15"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    group: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu15"
  type: "ReLU"
  bottom: "conv15"
  top: "conv15"
}
layer {
  name: "pool15"
  type: "Pooling"
  bottom: "conv15"
  top: "pool15"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}


layer {
  name: "conv21"
  type: "Convolution"
  bottom: "data2"
  top: "conv21"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 96
    kernel_size: 11
    stride: 4
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu21"
  type: "ReLU"
  bottom: "conv21"
  top: "conv21"
}
layer {
  name: "pool21"
  type: "Pooling"
  bottom: "conv21"
  top: "pool21"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "norm21"
  type: "LRN"
  bottom: "pool21"
  top: "norm21"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "conv22"
  type: "Convolution"
  bottom: "norm21"
  top: "conv22"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 2
    kernel_size: 5
    group: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu22"
  type: "ReLU"
  bottom: "conv22"
  top: "conv22"
}
layer {
  name: "pool22"
  type: "Pooling"
  bottom: "conv22"
  top: "pool22"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}
layer {
  name: "norm22"
  type: "LRN"
  bottom: "pool22"
  top: "norm22"
  lrn_param {
    local_size: 5
    alpha: 0.0001
    beta: 0.75
  }
}
layer {
  name: "conv23"
  type: "Convolution"
  bottom: "norm22"
  top: "conv23"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 384
    pad: 1
    kernel_size: 3
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "relu23"
  type: "ReLU"
  bottom: "conv23"
  top: "conv23"
}
layer {
  name: "conv24"
  type: "Convolution"
  bottom: "conv23"
  top: "conv24"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 384
    pad: 1
    kernel_size: 3
    group: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu24"
  type: "ReLU"
  bottom: "conv24"
  top: "conv24"
}
layer {
  name: "conv25"
  type: "Convolution"
  bottom: "conv24"
  top: "conv25"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  convolution_param {
    num_output: 256
    pad: 1
    kernel_size: 3
    group: 2
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu25"
  type: "ReLU"
  bottom: "conv25"
  top: "conv25"
}
layer {
  name: "pool25"
  type: "Pooling"
  bottom: "conv25"
  top: "pool25"
  pooling_param {
    pool: MAX
    kernel_size: 3
    stride: 2
  }
}

layer {
	name: "concat1"
	type: "Concat"
	bottom: "pool15"
	bottom: "pool25"
	top: "poolConcat"
}

layer {
  name: "fc6"
  type: "InnerProduct"
  bottom: "poolConcat"
  top: "fc6"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 4096
    weight_filler {
      type: "gaussian"
      std: 0.005
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu6"
  type: "ReLU"
  bottom: "fc6"
  top: "fc6"
}
layer {
  name: "drop6"
  type: "Dropout"
  bottom: "fc6"
  top: "fc6"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layer {
  name: "fc7"
  type: "InnerProduct"
  bottom: "fc6"
  top: "fc7"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 4096
    weight_filler {
      type: "gaussian"
      std: 0.005
    }
    bias_filler {
      type: "constant"
      value: 1
    }
  }
}
layer {
  name: "relu7"
  type: "ReLU"
  bottom: "fc7"
  top: "fc7"
}
layer {
  name: "drop7"
  type: "Dropout"
  bottom: "fc7"
  top: "fc7"
  dropout_param {
    dropout_ratio: 0.5
  }
}
layer {
  name: "fc8"
  type: "InnerProduct"
  bottom: "fc7"
  top: "fc8"
  param {
    lr_mult: 1
    decay_mult: 1
  }
  param {
    lr_mult: 2
    decay_mult: 0
  }
  inner_product_param {
    num_output: 4
    weight_filler {
      type: "gaussian"
      std: 0.01
    }
    bias_filler {
      type: "constant"
      value: 0
    }
  }
}
layer {
  name: "scale"
  bottom: "fc8"
  top: "out"
  type: "Power"
  power_param {
    power: 1
    scale: 10
    shift: 0
  }
}

@YuehChuan YuehChuan mentioned this issue Aug 7, 2017
Closed
@mohandsp
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Dear All,

Has this issue been fixed ?, is there a example code for the same .

@nefethael
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nefethael commented Aug 18, 2017 •
edited
Loading

I changed

net.setInput(targetBlob, ".data1");
net.setInput(searchBlob, ".data2");

to

net.setInput(targetBlob, "data1");
net.setInput(searchBlob, "data2");

and it no longer crashes, (btw very slow)

@nisssal
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nisssal commented Oct 28, 2017

In goturn.prototxt,
replace all "data1" to ".data1" & "data2" to ".data2"
It's working for me

@gloomyfish1998
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OpenCV Error: Requested object was not found (Requested blob "data1" not found)

@gloomyfish1998
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OpenCV goturn did not work at all, i just download the files and run from my machine with codes not Tracker API, i get this issue, anyone else got the same issue on this, or any suggestion //?
thanks in advance

@gloomyfish1998
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//Convert to Float type
targetPatch.convertTo(targetPatch, CV_32F);
searchPatch.convertTo(searchPatch, CV_32F);

Mat targetBlob = blobFromImage(targetPatch);
Mat searchBlob = blobFromImage(searchPatch);

net.setInput(targetBlob, "data1");
net.setInput(searchBlob, "data2");

Mat res = net.forward("scale");
Mat resMat = res.reshape(1, 1);

@gloomyfish1998
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can work now, i loaded the wrong net var...

@nvnnghia
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nvnnghia commented Nov 9, 2017

Hi, I got the same error as yours. Could you gui me how to load the right net var?? Thank you.

@gloomyfish1998
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just refer to the source code - gtrTracker.cpp
and run net file with dnn modules, everything will run correctly! forget tracking module.....

@nvnnghia
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Thank for your reply. I spent one day to get goturn to work. But not success. I got this error:
OpenCV Error: Assertion failed ((bias && l->blobs.size() == 2) || (!bias && l->blobs.size() == 1)) in initConvDeconvLayerFromCaffe, file /home/nghia/opencv/modules/dnn/src/layers/convolution_layer.cpp, line 1204
terminate called after throwing an instance of 'cv::Exception'
what(): /home/nghia/opencv/modules/dnn/src/layers/convolution_layer.cpp:1204: error: (-215) (bias && l->blobs.size() == 2) || (!bias && l->blobs.size() == 1) in function initConvDeconvLayerFromCaffe.

I got the model here: https://github.com/opencv/opencv_extra/tree/c4219d5eb3105ed8e634278fad312a1a8d2c182d/testdata/tracking

Could you please share your model and a test code. Or do you have any suggestion. Thank you very much.

@nvnnghia
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can work now, performance and speed are not good

@gloomyfish1998
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ohh~~~
paper said -> 100FPS based on GPU, very poor on my machine with CPU core i5,

@adavoudi
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I think there is an error in TrackerGOTURNImpl::updateImpl function:
https://github.com/opencv/opencv_contrib/blob/master/modules/tracking/src/gtrTracker.cpp#L152
//Mean Subtract
targetPatch = targetPatch - 128; searchPatch = searchPatch - 128;

targetPatch and searchPatch are of type unsigned char which means the result of the above commands will be saturated to zero for elements smaller than 128.

@silentshitx
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I got this error:
OpenCV Error: Assertion failed (blobs.size() != 0) in getMemoryShapes, file /tmp/opencv-20171112-69002-161xh9l/opencv-3.3.1/modules/dnn/src/layers/convolution_layer.cpp, line 175
libc++abi.dylib: terminating with uncaught exception of type cv::Exception: /tmp/opencv-20171112-69002-161xh9l/opencv-3.3.1/modules/dnn/src/layers/convolution_layer.cpp:175: error: (-215) blobs.size() != 0 in function getMemoryShapes

what is the reason

@HnanYang
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HnanYang commented Aug 20, 2018 •
edited by alalek
Loading

Dear Author:
I got this error:

yanghongnan@TITAN-X:/home/sdc/yanghongnan/GOTURN-master$ bash scripts/train.sh /home/sdc/yanghongnan/GOTURN-master/data/ImageNet/Image/ /home/sdc/yanghongnan/GOTURN-master/data/ImageNet/Annotations/ /home/sdc/yanghongnan/GOTURN-master/data/ALOV/Image/ /home/sdc/yanghongnan/GOTURN-master/data/ALOV/Annotation/
FOLDER: GOTURN1
LAMBDA_SCALE: 15
LAMBDA_SHIFT: 5
Using random seed: 800
Setting up Caffe in GPU mode with ID: 0
Found 7 subfolders...
Loading images, please wait...
Found 9999 annotations
*** Error in `build/train': free(): invalid pointer: 0x000000000c506040 ***
======= Backtrace: =========
/lib/x86_64-linux-gnu/libc.so.6(+0x777e5)[0x7fbdcdc6e7e5]
/lib/x86_64-linux-gnu/libc.so.6(+0x8037a)[0x7fbdcdc7737a]
/lib/x86_64-linux-gnu/libc.so.6(cfree+0x4c)[0x7fbdcdc7b53c]
build/train(_ZN17LoaderImagenetDet18LoadAnnotationFileERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEEPSt6vectorI10AnnotationSaIS9_EE+0xb6)[0x42e456]
build/train(_ZN17LoaderImagenetDetC1ERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEES7_+0x9db)[0x42f82b]
build/train(main+0x178)[0x40ff58]
/lib/x86_64-linux-gnu/libc.so.6(__libc_start_main+0xf0)[0x7fbdcdc17830]
build/train(_start+0x29)[0x410ed9]
======= Memory map: ========
00400000-00449000 r-xp 00000000 08:20 105906349                          /home/sdc/yanghongnan/GOTURN-master/build/train
00649000-0064a000 r--p 00049000 08:20 105906349                          /home/sdc/yanghongnan/GOTURN-master/build/train
0064a000-0064b000 rw-p 0004a000 08:20 105906349                          /home/sdc/yanghongnan/GOTURN-master/build/train
024f4000-0c5c8000 rw-p 00000000 00:00 0                                  [heap]
10000000-10001000 rw-s 00000000 00:06 623                                /dev/nvidia3
10001000-10002000 rw-s 00000000 00:06 623                                /dev/nvidia3
10002000-10003000 rw-s 00000000 00:06 623                                /dev/nvidia3
10003000-10004000 rw-s 00000000 00:06 623                                /dev/nvidia3
10004000-10005000 rw-s 00000000 00:06 623                                /dev/nvidia3
10005000-10006000 rw-s 00000000 00:06 623                                /dev/nvidia3
10006000-10007000 rw-s 00000000 00:06 623                                /dev/nvidia3
10007000-10008000 rw-s 00000000 00:06 623                                /dev/nvidia3
10008000-10009000 rw-s 00000000 00:06 623                                /dev/nvidia3
10009000-1000a000 rw-s 00000000 00:06 623                                /dev/nvidia3
1000a000-1000b000 rw-s 00000000 00:06 623                                /dev/nvidia3
1000b000-1000c000 rw-s 00000000 00:06 623                                /dev/nvidia3
1000c000-1000d000 rw-s 00000000 00:06 623                                /dev/nvidia3
1000d000-1000e000 rw-s 00000000 00:06 623                                /dev/nvidia3
1000e000-1000f000 rw-s 00000000 00:06 623                                /dev/nvidia3
1000f000-10010000 rw-s 00000000 00:06 623                                /dev/nvidia3
10010000-20000000 ---p 00000000 00:00 0 
200000000-200200000 rw-s 00000000 00:06 622                              /dev/nvidiactl
200200000-200400000 ---p 00000000 00:00 0 
200400000-200404000 rw-s 00000000 00:06 622                              /dev/nvidiactl
200404000-200600000 ---p 00000000 00:00 0 
200600000-200a00000 rw-s 00000000 00:06 622                              /dev/nvidiactl
200a00000-201600000 ---p 00000000 00:00 0 
201600000-201604000 rw-s 00000000 00:06 622                              /dev/nvidiactl
201604000-201800000 ---p 00000000 00:00 0 
201800000-201c00000 rw-s 00000000 00:06 622                              /dev/nvidiactl
201c00000-202800000 ---p 00000000 00:00 0 
202800000-202804000 rw-s 00000000 00:06 622                              /dev/nvidiactl
202804000-202a00000 ---p 00000000 00:00 0 
202a00000-202e00000 rw-s 00000000 00:06 622                              /dev/nvidiactl
202e00000-203a00000 ---p 00000000 00:00 0 
203a00000-203a04000 rw-s 00000000 00:06 622                              /dev/nvidiactl
203a04000-203c00000 ---p 00000000 00:00 0 
203c00000-204000000 rw-s 00000000 00:06 622                              /dev/nvidiactl
204000000-204c00000 ---p 00000000 00:00 0 
204c00000-204c04000 rw-s 00000000 00:06 622                              /dev/nvidiactl
204c04000-204e00000 ---p 00000000 00:00 0 
204e00000-205200000 rw-s 00000000 00:06 622                              /dev/nvidiactl
205200000-205e00000 ---p 00000000 00:00 0 
205e00000-205e04000 rw-s 00000000 00:06 622                              /dev/nvidiactl
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206000000-206400000 rw-s 00000000 00:06 622                              /dev/nvidiactl
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207000000-207004000 rw-s 00000000 00:06 622                              /dev/nvidiactl
207004000-207200000 ---p 00000000 00:00 0 
207200000-207600000 rw-s 00000000 00:06 622                              /dev/nvidiactl
207600000-208200000 ---p 00000000 00:00 0 
208200000-208204000 rw-s 00000000 00:06 622                              /dev/nvidiactl
208204000-208400000 ---p 00000000 00:00 0 
208400000-208800000 rw-s 00000000 00:06 622                              /dev/nvidiactl
208800000-209400000 ---p 00000000 00:00 0 
209400000-209404000 rw-s 00000000 00:06 622                              /dev/nvidiactl
209404000-209600000 ---p 00000000 00:00 0 
209600000-209a00000 rw-s 00000000 00:06 622                              /dev/nvidiactl
209a00000-209a04000 rw-s 00000000 00:06 622                              /dev/nvidiactl
209a04000-209c00000 ---p 00000000 00:00 0 
209c00000-20a000000 rw-s 00000000 00:06 622                              /dev/nvidiactl
20a000000-20a004000 rw-s 00000000 00:06 622                              /dev/nvidiactl
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20a600000-20a604000 rw-s 00000000 00:06 622                              /dev/nvidiactl
20a604000-20a800000 ---p 00000000 00:00 0 
20a800000-20ac00000 rw-s 00000000 00:06 622                              /dev/nvidiactl
20ac00000-20ac04000 rw-s 00000000 00:06 622                              /dev/nvidiactl
20ac04000-20ae00000 ---p 00000000 00:00 0 
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20b204000-20b400000 ---p 00000000 00:00 0 
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20b800000-20b804000 rw-s 00000000 00:06 622                              /dev/nvidiactl
20b804000-20ba00000 ---p 00000000 00:00 0 
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20be00000-20be04000 rw-s 00000000 00:06 622                              /dev/nvidiactl
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20c000000-20c400000 rw-s 00000000 00:06 622                              /dev/nvidiactl
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20ca00000-600200000 ---p 00000000 00:00 0 
10000000000-10504400000 ---p 00000000 00:00 0 
10504400000-10504600000 rw-s 00000000 00:05 294842641                    /dev/zero (deleted)
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10504800000-10504a00000 rw-s 00000000 00:05 294842642                    /dev/zero (deleted)
10504a00000-10504c00000 rw-s 00000000 00:06 622                          /dev/nvidiactl
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7fbdad785000-7fbdad85c000 r-xp 00000000 fc:00 7209178                    /lib/x86_64-linux-gnu/libgcrypt.so.20.0.5
7fbdad85c000-7fbdada5c000 ---p 000d7000 fc:00 7209178                    /lib/x86_64-linux-gnu/libgcrypt.so.20.0.5
7fbdada5c000-7fbdada5d000 r--p 000d7000 fc:00 7209178                    /lib/x86_64-linux-gnu/libgcrypt.so.20.0.5
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7fbdada65000-7fbdada66000 rw-p 00000000 00:00 0 
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7fbdada8d000-7fbdadc8d000 ---p 00027000 fc:00 8008032                    /usr/lib/x86_64-linux-gnu/libkj-0.5.3.so
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7fbdadc8f000-7fbdadca6000 r-xp 00000000 fc:00 8005185                    /usr/lib/x86_64-linux-gnu/libboost_filesystem.so.1.58.0
7fbdadca6000-7fbdadea5000 ---p 00017000 fc:00 8005185                    /usr/lib/x86_64-linux-gnu/libboost_filesystem.so.1.58.0
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7fbdae2d5000-7fbdae313000 r-xp 00000000 fc:00 8000038                    /usr/lib/x86_64-linux-gnu/libquadmath.so.0.0.0
7fbdae313000-7fbdae512000 ---p 0003e000 fc:00 8000038                    /usr/lib/x86_64-linux-gnu/libquadmath.so.0.0.0
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7fbdae51b000-7fbdae71a000 ---p 00007000 fc:00 8004825                    /usr/lib/x86_64-linux-gnu/libaec.so.0.0.3
7fbdae71a000-7fbdae71b000 r--p 00006000 fc:00 8004825                    /usr/lib/x86_64-linux-gnu/libaec.so.0.0.3
7fbdae71b000-7fbdae71c000 rw-p 00007000 fc:00 8004825                    /usr/lib/x86_64-linux-gnu/libaec.so.0.0.3
7fbdae71c000-7fbdae721000 r-xp 00000000 fc:00 8001983                    /usr/lib/x86_64-linux-gnu/libXdmcp.so.6.0.0
7fbdae721000-7fbdae920000 ---p 00005000 fc:00 8001983                    /usr/lib/x86_64-linux-gnu/libXdmcp.so.6.0.0
7fbdae920000-7fbdae921000 r--p 00004000 fc:00 8001983                    /usr/lib/x86_64-linux-gnu/libXdmcp.so.6.0.0
7fbdae921000-7fbdae922000 rw-p 00005000 fc:00 8001983                    /usr/lib/x86_64-linux-gnu/libXdmcp.so.6.0.0
7fbdae922000-7fbdae924000 r-xp 00000000 fc:00 8001981                    /usr/lib/x86_64-linux-gnu/libXau.so.6.0.0
7fbdae924000-7fbdaeb24000 ---p 00002000 fc:00 8001981                    /usr/lib/x86_64-linux-gnu/libXau.so.6.0.0
7fbdaeb24000-7fbdaeb25000 r--p 00002000 fc:00 8001981                    /usr/lib/x86_64-linux-gnu/libXau.so.6.0.0
7fbdaeb25000-7fbdaeb26000 rw-p 00003000 fc:00 8001981                    /usr/lib/x86_64-linux-gnu/libXau.so.6.0.0
7fbdaeb26000-7fbdaeb56000 r-xp 00000000 fc:00 8005115                    /usr/lib/x86_64-linux-gnu/libprotobuf-lite.so.9.0.1
7fbdaeb56000-7fbdaed55000 ---p 00030000 fc:00 8005115                    /usr/lib/x86_64-linux-gnu/libprotobuf-lite.so.9.0.1
7fbdaed55000-7fbdaed56000 r--p 0002f000 fc:00 8005115                    /usr/lib/x86_64-linux-gnu/libprotobuf-lite.so.9.0.1
7fbdaed56000-7fbdaed57000 rw-p 00030000 fc:00 8005115                    /usr/lib/x86_64-linux-gnu/libprotobuf-lite.so.9.0.1
7fbdaed57000-7fbdaed5a000 r-xp 00000000 fc:00 8005164                    /usr/lib/x86_64-linux-gnu/libboost_system.so.1.58.0
7fbdaed5a000-7fbdaef59000 ---p 00003000 fc:00 8005164                    /usr/lib/x86_64-linux-gnu/libboost_system.so.1.58.0
7fbdaef59000-7fbdaef5a000 r--p 00002000 fc:00 8005164                    /usr/lib/x86_64-linux-gnu/libboost_system.so.1.58.0
7fbdaef5a000-7fbdaef5b000 rw-p 00003000 fc:00 8005164                    /usr/lib/x86_64-linux-gnu/libboost_system.so.1.58.0
7fbdaef5b000-7fbdaef62000 r-xp 00000000 fc:00 8007828                    /usr/lib/x86_64-linux-gnu/libmircore.so.1
7fbdaef62000-7fbdaf162000 ---p 00007000 fc:00 8007828                    /usr/lib/x86_64-linux-gnu/libmircore.so.1
7fbdaf162000-7fbdaf163000 r--p 00007000 fc:00 8007828                    /usr/lib/x86_64-linux-gnu/libmircore.so.1
7fbdaf163000-7fbdaf164000 rw-p 00008000 fc:00 8007828                    /usr/lib/x86_64-linux-gnu/libmircore.so.1
7fbdaf164000-7fbdaf1e9000 r-xp 00000000 fc:00 8008034                    /usr/lib/x86_64-linux-gnu/libcapnp-0.5.3.so
7fbdaf1e9000-7fbdaf3e8000 ---p 00085000 fc:00 8008034                    /usr/lib/x86_64-linux-gnu/libcapnp-0.5.3.so
7fbdaf3e8000-7fbdaf3eb000 r--p 00084000 fc:00 8008034                    /usr/lib/x86_64-linux-gnu/libcapnp-0.5.3.so
7fbdaf3eb000-7fbdaf3ec000 rw-p 00087000 fc:00 8008034                    /usr/lib/x86_64-linux-gnu/libcapnp-0.5.3.so
7fbdaf3ec000-7fbdaf45b000 r-xp 00000000 fc:00 8007830                    /usr/lib/x86_64-linux-gnu/libmirprotobuf.so.3
7fbdaf45b000-7fbdaf65a000 ---p 0006f000 fc:00 8007830                    /usr/lib/x86_64-linux-gnu/libmirprotobuf.so.3
7fbdaf65a000-7fbdaf65d000 r--p 0006e000 fc:00 8007830                    /usr/lib/x86_64-linux-gnu/libmirprotobuf.so.3
7fbdaf65d000-7fbdaf65e000 rw-p 00071000 fc:00 8007830                    /usr/lib/x86_64-linux-gnu/libmirprotobuf.so.3
7fbdaf65e000-7fbdaf6a2000 r-xp 00000000 fc:00 8007829                    /usr/lib/x86_64-linux-gnu/libmircommon.so.7
7fbdaf6a2000-7fbdaf8a2000 ---p 00044000 fc:00 8007829                    /usr/lib/x86_64-linux-gnu/libmircommon.so.7
7fbdaf8a2000-7fbdaf8a4000 r--p 00044000 fc:00 8007829                    /usr/lib/x86_64-linux-gnu/libmircommon.so.7
7fbdaf8a4000-7fbdaf8a5000 rw-p 00046000 fc:00 8007829                    /usr/lib/x86_64-linux-gnu/libmircommon.so.7
7fbdaf8a5000-7fbdaf8bc000 r-xp 00000000 fc:00 7209158                    /lib/x86_64-linux-gnu/libresolv-2.23.so
7fbdaf8bc000-7fbdafabc000 ---p 00017000 fc:00 7209158                    /lib/x86_64-linux-gnu/libresolv-2.23.so
7fbdafabc000-7fbdafabd000 r--p 00017000 fc:00 7209158                    /lib/x86_64-linux-gnu/libresolv-2.23.so
7fbdafabd000-7fbdafabe000 rw-p 00018000 fc:00 7209158                    /lib/x86_64-linux-gnu/libresolv-2.23.so
7fbdafabe000-7fbdafac0000 rw-p 00000000 00:00 0 
7fbdafac0000-7fbdafadf000 r-xp 00000000 fc:00 7209552                    /lib/x86_64-linux-gnu/libselinux.so.1
7fbdafadf000-7fbdafcde000 ---p 0001f000 fc:00 7209552                    /lib/x86_64-linux-gnu/libselinux.so.1
7fbdafcde000-7fbdafcdf000 r--p 0001e000 fc:00 7209552                    /lib/x86_64-linux-gnu/libselinux.so.1
7fbdafcdf000-7fbdafce0000 rw-p 0001f000 fc:00 7209552                    /lib/x86_64-linux-gnu/libselinux.so.1
7fbdafce0000-7fbdafce2000 rw-p 00000000 00:00 0 
7fbdafce2000-7fbdafd08000 r-xp 00000000 fc:00 7208992                    /lib/x86_64-linux-gnu/libexpat.so.1.6.0
7fbdafd08000-7fbdaff08000 ---p 00026000 fc:00 7208992                    /lib/x86_64-linux-gnu/libexpat.so.1.6.0
7fbdaff08000-7fbdaff0a000 r--p 00026000 fc:00 7208992                    /lib/x86_64-linux-gnu/libexpat.so.1.6.0
7fbdaff0a000-7fbdaff0b000 rw-p 00028000 fc:00 7208992                    /lib/x86_64-linux-gnu/libexpat.so.1.6.0
7fbdaff0b000-7fbdaff13000 r-xp 00000000 fc:00 8004271                    /usr/lib/x86_64-linux-gnu/libthai.so.0.2.4
7fbdaff13000-7fbdb0112000 ---p 00008000 fc:00 8004271                    /usr/lib/x86_64-linux-gnu/libthai.so.0.2.4
7fbdb0112000-7fbdb0113000 r--p 00007000 fc:00 8004271                    /usr/lib/x86_64-linux-gnu/libthai.so.0.2.4
7fbdb0113000-7fbdb0114000 rw-p 00008000 fc:00 8004271                    /usr/lib/x86_64-linux-gnu/libthai.so.0.2.4
7fbdb0114000-7fbdb0170000 r-xp 00000000 fc:00 8004275                    /usr/lib/x86_64-linux-gnu/libharfbuzz.so.0.10000.1
7fbdb0170000-7fbdb0370000 ---p 0005c000 fc:00 8004275                    /usr/lib/x86_64-linux-gnu/libharfbuzz.so.0.10000.1
7fbdb0370000-7fbdb0371000 r--p 0005c000 fc:00 8004275                    /usr/lib/x86_64-linux-gnu/libharfbuzz.so.0.10000.1
7fbdb0371000-7fbdb0372000 rw-p 0005d000 fc:00 8004275                    /usr/lib/x86_64-linux-gnu/libharfbuzz.so.0.10000.1
7fbdb0372000-7fbdb03bc000 r-xp 00000000 fc:00 7213251                    /lib/x86_64-linux-gnu/libdbus-1.so.3.14.6
7fbdb03bc000-7fbdb05bc000 ---p 0004a000 fc:00 7213251                    /lib/x86_64-linux-gnu/libdbus-1.so.3.14.6
7fbdb05bc000-7fbdb05bd000 r--p 0004a000 fc:00 7213251                    /lib/x86_64-linux-gnu/libdbus-1.so.3.14.6
7fbdb05bd000-7fbdb05be000 rw-p 0004b000 fc:00 7213251                    /lib/x86_64-linux-gnu/libdbus-1.so.3.14.6
7fbdb05be000-7fbdb05ea000 r-xp 00000000 fc:00 8008020                    /usr/lib/x86_64-linux-gnu/libatspi.so.0.0.1
7fbdb05ea000-7fbdb07e9000 ---p 0002c000 fc:00 8008020                    /usr/lib/x86_64-linux-gnu/libatspi.so.0.0.1
7fbdb07e9000-7fbdb07ec000 r--p 0002b000 fc:00 8008020                    /usr/lib/x86_64-linux-gnu/libatspi.so.0.0.1
7fbdb07ec000-7fbdb07ed000 rw-p 0002e000 fc:00 8008020                    /usr/lib/x86_64-linux-gnu/libatspi.so.0.0.1
7fbdb07ed000-7fbdb20a3000 r-xp 00000000 fc:00 7996122                    /usr/lib/x86_64-linux-gnu/libicudata.so.55.1
7fbdb20a3000-7fbdb22a2000 ---p 018b6000 fc:00 7996122                    /usr/lib/x86_64-linux-gnu/libicudata.so.55.1
7fbdb22a2000-7fbdb22a3000 r--p 018b5000 fc:00 7996122                    /usr/lib/x86_64-linux-gnu/libicudata.so.55.1
7fbdb22a3000-7fbdb22a4000 rw-p 018b6000 fc:00 7996122                    /usr/lib/x86_64-linux-gnu/libicudata.so.55.1
7fbdb22a4000-7fbdb23cd000 r-xp 00000000 fc:00 7995896                    /usr/lib/x86_64-linux-gnu/libgfortran.so.3.0.0
7fbdb23cd000-7fbdb25cc000 ---p 00129000 fc:00 7995896                    /usr/lib/x86_64-linux-gnu/libgfortran.so.3.0.0
7fbdb25cc000-7fbdb25cd000 r--p 00128000 fc:00 7995896                    /usr/lib/x86_64-linux-gnu/libgfortran.so.3.0.0
7fbdb25cd000-7fbdb25cf000 rw-p 00129000 fc:00 7995896                    /usr/lib/x86_64-linux-gnu/libgfortran.so.3.0.0
7fbdb25cf000-7fbdb2966000 r-xp 00000000 fc:00 9833117                    /usr/lib/atlas-base/libatlas.so.3.0
7fbdb2966000-7fbdb2b66000 ---p 00397000 fc:00 9833117                    /usr/lib/atlas-base/libatlas.so.3.0
7fbdb2b66000-7fbdb2b6d000 rw-p 00397000 fc:00 9833117                    /usr/lib/atlas-base/libatlas.so.3.0
7fbdb2b6d000-7fbdb2b6f000 r-xp 00000000 fc:00 7209162                    /lib/x86_64-linux-gnu/libutil-2.23.so
7fbdb2b6f000-7fbdb2d6e000 ---p 00002000 fc:00 7209162                    /lib/x86_64-linux-gnu/libutil-2.23.so
7fbdb2d6e000-7fbdb2d6f000 r--p 00001000 fc:00 7209162                    /lib/x86_64-linux-gnu/libutil-2.23.so
7fbdb2d6f000-7fbdb2d70000 rw-p 00002000 fc:00 7209162                    /lib/x86_64-linux-gnu/libutil-2.23.so
7fbdb2d70000-7fbdb2d77000 r-xp 00000000 fc:00 8004437                    /usr/lib/x86_64-linux-gnu/libsnappy.so.1.3.0
7fbdb2d77000-7fbdb2f76000 ---p 00007000 fc:00 8004437                    /usr/lib/x86_64-linux-gnu/libsnappy.so.1.3.0
7fbdb2f76000-7fbdb2f77000 r--p 00006000 fc:00 8004437                    /usr/lib/x86_64-linux-gnu/libsnappy.so.1.3.0
7fbdb2f77000-7fbdb2f78000 rw-p 00007000 fc:00 8004437                    /usr/lib/x86_64-linux-gnu/libsnappy.so.1.3.0
7fbdb2f78000-7fbdb2f7a000 r-xp 00000000 fc:00 8005046                    /usr/lib/x86_64-linux-gnu/libsz.so.2.0.1
7fbdb2f7a000-7fbdb3179000 ---p 00002000 fc:00 8005046                    /usr/lib/x86_64-linux-gnu/libsz.so.2.0.1
7fbdb3179000-7fbdb317a000 r--p 00001000 fc:00 8005046                    /usr/lib/x86_64-linux-gnu/libsz.so.2.0.1
7fbdb317a000-7fbdb317b000 rw-p 00002000 fc:00 8005046                    /usr/lib/x86_64-linux-gnu/libsz.so.2.0.1
7fbdb317b000-7fbdb3180000 r-xp 00000000 fc:00 8004498                    /usr/lib/x86_64-linux-gnu/libIlmThread-2_2.so.12.0.0
7fbdb3180000-7fbdb3380000 ---p 00005000 fc:00 8004498                    /usr/lib/x86_64-linux-gnu/libIlmThread-2_2.so.12.0.0
7fbdb3380000-7fbdb3381000 r--p 00005000 fc:00 8004498                    /usr/lib/x86_64-linux-gnu/libIlmThread-2_2.so.12.0.0
7fbdb3381000-7fbdb3382000 rw-p 00006000 fc:00 8004498                    /usr/lib/x86_64-linux-gnu/libIlmThread-2_2.so.12.0.0
7fbdb3382000-7fbdb339d000 r-xp 00000000 fc:00 8004497                    /usr/lib/x86_64-linux-gnu/libIex-2_2.so.12.0.0scripts/train.sh: line 48: 11809 Aborted                 (core dumped) build/train $VIDEOS_FOLDER_IMAGENET $ANNOTATIONS_FOLDER_IMAGENET $VIDEOS_FOLDER $ANNOTATIONS_FOLDER $CAFFE_MODEL $TRAIN_PROTO $SOLVER_TEMP $LAMBDA_SHIFT $LAMBDA_SCALE $MIN_SCALE $MAX_SCALE $GPU_ID $RANDOM_SEED 2> $RESULT_DIR/results.txt
Could you help me find the reason? Thanks a lot!

@alalek
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alalek commented Aug 20, 2018

@HnanYang Why do you think that this problem should be fixed in OpenCV? I don't see any OpenCV calls in stacktraces.

@HnanYang
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@alalek emm... I asked a question in the wrong place. But this Error bothered me for a long time

@RJVisee44
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RJVisee44 commented Sep 4, 2018 •
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Hi all,

Does anyone know what this error means:

File "<ipython-input-10-dbddf5ead724>", line 1, in <module> ok = tracker.init(frame,bbox)

error: OpenCV(3.4.1) C:\bld\opencv_1520732263159\work\opencv-3.4.1\modules\core\src\matrix.cpp:362: error: (-215) u != 0 in function cv::Mat::create

I compiled opencv 3.4.1 from anaconda using:
conda install -c conda-forge opencv conda install -c conda-forge/label/broken opencv

The tracker can be created but cannot be initialized. Using the .prototxt and .caffemodel from this tutorial: https://www.learnopencv.com/goturn-deep-learning-based-object-tracking/

Running in Spyder, Python 3.6.2, Anaconda custom (32-bit), Windows 7. Do I need to build opencv from source?

@p779
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p779 commented Jan 26, 2020

Hey everyone
I try to use goturn tracker and it gave me this error when I try do to init

cv2.error: OpenCV(4.1.2) /io/opencv/modules/dnn/src/caffe/caffe_io.cpp:1121: error: (-2:Unspecified error) FAILED: fs.is_open(). Can't open "goturn.prototxt" in function 'ReadProtoFromTextFile'

I like to know what do you think

@zihaozhang9
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Take a closer look at the solution in the tutorial.

@ieliz ieliz mentioned this issue Aug 14, 2020
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@alalek alalek mentioned this issue Aug 16, 2020
Merged
@muare muare mentioned this issue Dec 2, 2020
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@muhammad-faizan-122
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Hey everyone I try to use goturn tracker and it gave me this error when I try do to init

cv2.error: OpenCV(4.1.2) /io/opencv/modules/dnn/src/caffe/caffe_io.cpp:1121: error: (-2:Unspecified error) FAILED: fs.is_open(). Can't open "goturn.prototxt" in function 'ReadProtoFromTextFile'

I like to know what do you think
I got same issue. can anyone help me?

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