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c++ visual studio implement of ECO: Efficient Convolution Operators for Tracking
当跟踪目标被部分遮挡,或者傍边有相似目标时,会跟错吗
Variable k1 is uninitialized.
https://github.com/martin-danelljan/ECO/search?q=k1&unscoped_q=k1
Thanks for sharing your work~
It seems not as fast as the Matlab version ? ( ~ 6 fps vs. 30 fps on my PC )
I complied CPU version and turn useDeepFeature=false, imshow is also turned off.
Is there something I missed? Thanks~
Great work! What's the speed (FPS) of this C++ version?
After I compile program successfully, I find some files are lost.
I downloaded VGG_CNN_M_2048.caffemodel and VGG_mean.binaryproto, but I can't find the file which named mean.yml.
How can I do?
或者说是否我自己比较容易实现替换成gpu版本的caffe?
这个caffe版我觉得多此一举,无gpu每秒8帧的话也太慢了,eco hc版在哪里有么?
I am trying my best to make your codes runnable the whole afternoon,but unfortunatly I failed,as although in you describination the caffe-windows is a CPU version,some of codes suffer from a CUDA-related error that I have to uncommon them to let the compiler pass, besides the caffe-windows I used did not contains some of your additional dependencies such as caffe.lib.lib, let alone cuda.lib.
Would you plz make the USAGE more detailed so that anyone interested in your work would ultimate and contribute it.
And thanks for your sharing.
When I run, why doesn't it feel good, and the box doesn't move, is it my fault?
I analyzed the program.and "Fhog" it takes a long time.
Is there a way to speed up?
ECO.cpp
大概110-120行之间:
for (size_t i = 0; i != feature_sz.size(); ++i)
{
size_t size = feature_sz[i].width + (feature_sz[i].width + 1) % 2 ;
filter_sz.push_back(cv::Size(size, size));
k1 = size > output_sz ? i : k1;
//wangsen
output_sz = std::max(size,output_sz);
//output_sz = size > output_sz ? size : output_sz;
}
output_sz好像也是随机的值,然后一直大于size,k1一直没得初始化,
您好,很高兴看到优秀的C++代码实现。我在看作者提供的原始版本的代码时,一个问题一直困扰着我。
1)在fDSST中,作者用如下代码生成ys, 在调试中发现,ys两边值最大,中间值最小,而在检测过程中,作者也是找响应最大的位置作为当前的scale。
2)在DSST中,将中间的值设置为最大,两边的值较小是,与fDSST相冲突。
如果能提供任何意见,将非常感激。
ys = [1 0.642167199144790 0.170056201828270 0.0185709050136830 0.000836315026159023 1.55311269123150e-05 1.18941188747878e-07 3.75627879293239e-10 4.89192285304428e-13 4.89192285304428e-13 3.75627879293239e-10 1.18941188747878e-07 1.55311269123150e-05 0.000836315026159023 0.0185709050136830 0.170056201828270 0.642167199144790]
scale_exp = (-floor((nScales-1)/2):ceil((nScales-1)/2)) * nScalesInterp/nScales;
scale_exp_shift = circshift(scale_exp, [0 -floor((nScales-1)/2)]);
interp_scale_exp = -floor((nScalesInterp-1)/2):ceil((nScalesInterp-1)/2);
interp_scale_exp_shift = circshift(interp_scale_exp, [0 -floor((nScalesInterp-1)/2)]);
scaleSizeFactors = scale_step .^ scale_exp;
interpScaleFactors = scale_step .^ interp_scale_exp_shift;
ys = exp(-0.5 * (scale_exp_shift.^2) /scale_sigma^2);
useDeepFeature=0能正常运行,这时候的特征是hog还是hog+cn?
Looks like there is no initialization of the variable output_sz in ECO class?
I tried to run in HOG version and looks like it is not correctly initialized so there is a segmentation fault.
您好,请问有GPU版本吗?
首先感谢nicewsyly,开源ECO c++版本给我们学习。
我在ubuntu16.04编译通过,但是运行时出错了,不管是否使用cnn特征都一样的错误,我使用的是960x540的视频,错误提示如下如下:
init obj[486 216 46 101]
img_support_sz is : [252 x 252]
eco track...0
process_frame 1
process_frame 2
process_frame 3
process_frame 4
process_frame 5
process_frame 50
process_frame 51
process_frame 52
terminate called after throwing an instance of 'cv::Exception'
what(): OpenCV(3.4.2) /home/mrsy/project/machine-learning-lib/opencv-3.4.2/modules/core/src/matrix.cpp:465: error: (-215:Assertion failed) 0 <= roi.x && 0 <= roi.wid
th && roi.x + roi.width <= m.cols && 0 <= roi.y && 0 <= roi.height && roi.y + roi.height <= m.rows in function 'Mat'
thanks for your work, i dont find the judgment that will stop tracking the target? thanks
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