matconvnet

Matconvnet output of deep network's marix is uniform valued instead of varying values?

由 扶醉桌前 提交于 2020-02-27 13:05:24
问题 Im trying to achieve a density map from network output of dimension 20x20x1x50. Here 20x20 is the output map and 50 is the batch size. The issue is that the value of output X is equal 0.098 across each output matrix..20x20. There is no gaussian shape like density map but a flat similar valued output map 20x20x1x50. The issue is shown in the figure attached. What am i missing here? The euclidean loss for backpropagation is given as: case {'l2loss'} res=(c-X); n=1; if isempty(dzdy) %forward Y =

how to change softmaxlayer with regression in matconvnet

由 喜你入骨 提交于 2020-01-05 07:33:37
问题 I am trying to train MNIST data set with single output. It means when i give an 28*28 input (image) the model gives us a just number. For example i give '5', the model give me as a result 4.9,5, 5.002 or close to 5. So I have red some documents. People tells softmaxlayer have to be changed with regression layer. For doing do this. I am using matconvnet library and its mnist example. I have changed my network and written regression layer loss function. these are my codes: net.layers = {} ; net

how to change softmaxlayer with regression in matconvnet

由 无人久伴 提交于 2020-01-05 07:33:21
问题 I am trying to train MNIST data set with single output. It means when i give an 28*28 input (image) the model gives us a just number. For example i give '5', the model give me as a result 4.9,5, 5.002 or close to 5. So I have red some documents. People tells softmaxlayer have to be changed with regression layer. For doing do this. I am using matconvnet library and its mnist example. I have changed my network and written regression layer loss function. these are my codes: net.layers = {} ; net

Can't replicate a matconvnet CNN architecture in Keras

由 心已入冬 提交于 2020-01-04 01:51:41
问题 I have the following architecture of a Convolutional Neural Network in matconvnet which I use to train on my own data: function net = cnn_mnist_init(varargin) % CNN_MNIST_LENET Initialize a CNN similar for MNIST opts.batchNormalization = false ; opts.networkType = 'simplenn' ; opts = vl_argparse(opts, varargin) ; f= 0.0125 ; net.layers = {} ; net.layers{end+1} = struct('name','conv1',... 'type', 'conv', ... 'weights', {{f*randn(3,3,1,64, 'single'), zeros(1, 64, 'single')}}, ... 'stride', 1, .

win10+matconvnet+matlab2019a+visual studio 2017配置方式

由 |▌冷眼眸甩不掉的悲伤 提交于 2019-12-17 01:11:19
配置 MatConvNet 官网的安装配置指南链接： http://www.vlfeat.org/matconvnet/install/ 配置的目的是： 将 MatConvNet 和 自己写的程序融合，使用框架应为： CPU版编译 在 matlab 命令行输入 % 这个命令是来寻找vs编译器的 mex -setup %设置matlab的C++编译器，根据提示信息， 选择VS C++ mex -setup C++ 操作如图： 使用 mex -setup 命令的原因是，MatConvNet 文件中的matlab文件夹下的src文件里的.cu文件，所以需要链接c++编译器 在 matlab 命令行 输入 % cd到解压的matconvnet目录下 % 将matlab工作路径切换到matconvnet所在文件夹，添加搜索路径 addpath matlab % 运行程序（该程序具体位置在matlab下），生成mex文件夹（编译过程） vl_compilenn 编译成功的结果图如下： 测试 matlab中输入如下指令： run matlab\vl_setupnn vl_testnn 测试成功图如下： 到此为止，matconvnet的CPU编译过程完成。 期间遇到的问题 1、在运行vl_compilenn的时候，提示错误：CL.EXE not found in PATH 解决方法

win10+GPU+MATLAB+MatConvNet配置

由 ☆樱花仙子☆ 提交于 2019-12-14 19:25:03
@article{hu2016finding, title={Finding Tiny Faces}, author={Hu, Peiyun and Ramanan, Deva}, journal={arXiv preprint arXiv:1612.04402}, year={2016} } 1、首先根据自己的英伟达型号去官网下载对应的英伟达驱动 我的是gtx1050,计算能力是6.1,在默认路径下安装。 2、根据自己安装的matlab版本，下载最新的对应cuda 一定要下载对应matlab版本的cuda,一开始我安装最新cuda8.0出错了，我的matlab是R2016a，重新安装了最新的cuda7.5,安装在默认路径下。 3、配置VS2013+cuda7.5 具体参考http://blog.csdn.NET/listening5/article/details/50240147 4、安装matconvnet 我用来做人脸检测，所以这里配置了Finding Tiny Faces (1)首先下载tiny git clone git@github.com:MarleyLee/tiny.git (2)CPU编译 两个命令： mex -setup vl_compilenn 编译完之后会多了一个mex文件夹，在matlab文件夹下面 编译完之后应该有除了cudnn64_4

Compiling MatConvNet on Windows

由 戏子无情 提交于 2019-12-11 03:22:26
问题 I am trying to compile MatConvNet on Windows 8.1. Since it seems that I need to use the "Makefile" to do that, I downloaded GNUWin Make, which allows to use the make command on Windows. The error I get is the following one: process_begin: CreateProcess(NULL, C:\Program Files\MATLAB\R2014a\bin\mexext, ...) failed. while the file C:\Program Files\MATLAB\R2014a\bin\mexext.bat exists. Do you have any clue on that please? 回答1: I also tried to compile MatConvNet on Windows with MinGW and I faced

Matconvnet error cl.exe not found

由 给你一囗甜甜゛ 提交于 2019-12-10 11:21:28
问题 I have installed MatConvNet from VLFeat and I am trying to compile it. But as I am trying to run vl_compilenn it shows the following error: vl_compilenn Warning: CL.EXE not found in PATH. Trying to guess out of mex setup. > In vl_compilenn>check_clpath (line 580) In vl_compilenn (line 413) 'cl.exe' is not recognized as an internal or external command, operable program or batch file. Error using vl_compilenn>check_clpath (line 591) Unable to find cl.exe Error in vl_compilenn (line 413) check

Matconvnet error cl.exe not found

由 情到浓时终转凉″ 提交于 2019-12-06 07:15:52
I have installed MatConvNet from VLFeat and I am trying to compile it. But as I am trying to run vl_compilenn it shows the following error: vl_compilenn Warning: CL.EXE not found in PATH. Trying to guess out of mex setup. > In vl_compilenn>check_clpath (line 580) In vl_compilenn (line 413) 'cl.exe' is not recognized as an internal or external command, operable program or batch file. Error using vl_compilenn>check_clpath (line 591) Unable to find cl.exe Error in vl_compilenn (line 413) check_clpath(); % check whether cl.exe in path install visual studio community edition ( it's the free edition

Matconvnet output of deep network's marix is uniform valued instead of varying values?

由 [亡魂溺海] 提交于 2019-12-04 21:19:37
Im trying to achieve a density map from network output of dimension 20x20x1x50. Here 20x20 is the output map and 50 is the batch size. The issue is that the value of output X is equal 0.098 across each output matrix..20x20. There is no gaussian shape like density map but a flat similar valued output map 20x20x1x50. The issue is shown in the figure attached. What am i missing here? The euclidean loss for backpropagation is given as: case {'l2loss'} res=(c-X); n=1; if isempty(dzdy) %forward Y = sum((res(:).^2))/numel(res); else Y_= -1.*(c-X); Y = 2*single (Y_ * (dzdy / n) ); end Found the
订阅 matconvnet