Does anyone use the matlab wrapper for the caffe framework? Is there a way how to extract an 4096 dimensional feature vector from an image?
I was already following
https://github.com/BVLC/caffe/issues/432
and also tried to remove the last lines in imagenet_deploy.prototxt to remove layers as suggested in another forum on github.
But still when I run "matcaffe_demo(im, 1)" I only get a 1000 dim vector of scores (for the image net classes).
Any help would be appreciated
Kind regards
It seems that you might not be calling the correct prototxt file. If the last layer defined in the prototxt has the top blob of 4096 dimension, there is no way for the output to be 1000 dimension.
To be sure, try creating a bug in the prototxt file and see whether the program crashes. If it doesn't then the program indeed is reading some other prototxt file.
Related
I am currently working on a project at home and hoping to use the Computer Vision toolbox in Matlab to retrieve images from a set that match based on my query image. In fact, the example I'm using from the Matlab documentation here: Image Matching Example
The snag I keep bumping into is that it appears the imageSet class in Matlab only works on files saved to disk. Unfortunately, the work I'm doing has a 4D matrix of an image collection I've created artificially. More specifically, it has the shape (M,N,RGB,I) where
M = number of pixels in X-dir
N = number of pixels in Y-dir
RGB =
size of 3, where each channel for RGB is stored as a page
I = the
image number (up to 10,000, for example)
It seems pretty silly that I have to write everything to files for me to employ the imageSet class object.
So, the question is: Does anyone know a way to create the imageSet object (or similar) without have to write everything to a tmp dir on disk to carry out the analysis, that is, create imageSet from workspace variables?
For the life of me this one had me stumped all weekend. I know I could capitulate and write to files, but somehow that just bothers me.
Any help is greatly appreciated.
You are correct, imageSet only stores file names, and gives you a read method to read a particular image from disk.
In general, if you already have the images in memory, you can simply store them in a cell array. Or, if your images are all the same size, you can keep them in a single multi-dimensional array.
However, in this particular case, you are using bagOfFeatures, which currently only takes imageSet. So you will have to save your images to files.
I am using Caffe to extract features with matlab wrapper.I have 5011 images as test data set.I chopped all the layers after 'relu7' in 'deploy.prototxt'. I found out if you take the same image as input of matcaffe_demo.m and matcaffe_batch.m, you will get the different 4096-dim features.
Could someone tell me why?
what is the differences between you extract features from all these images one by one with matcaffe_demo.m and extract features by listing all these images with matcaffe_batch.m?
You can find the answer to this question at caffe github.
Basically, matcaffe_demo is used for classification and it averages results of 10 crops of the input image, while matcaffe_bathc uses only a single input.
Moreover, note that these m-files are no longer available in recent caffe versions.
I tried to train my own neural net using my own imagedatabase as described in
http://caffe.berkeleyvision.org/gathered/examples/imagenet.html
However when I want to check the neural net after training on some standard images using the matlab wrapper I get the following output / error:
Done with init
Using GPU Mode
Done with set_mode
Elapsed time is 3.215971 seconds.
Error using caffe
Invalid input size
I used the matlab wrapper before to extract cnn features based on a pretrained model. It worked. So I don't think the input size of my images is the problem (They are converted to the correct size internally by the function "prepare_image").
Has anyone an idea what could be the error?
Found the solution: I was referencing the wrong ".prototxt" file (Its a little bit confusing because the files are quite similar.
So for computing features using the matlab wrapper one needs to reference the following to files in "matcaffe_demo.m":
models/bvlc_reference_caffenet/deploy.prototxt
models/bvlc_reference_caffenet/MyModel_caffenet_train_iter_450000.caffemodel
where "MyModel_caffenet_train_iter_450000.caffemodel" is the only file needed which is created during training.
In the beginning I was accidently referencing
models/bvlc_reference_caffenet/MyModel_train_val.prototxt
which was the ".prototxt" file used for training.
New with Matlab.
When I try to load my own date using the NN pattern recognition app window, I can load the source data, but not the target (it is never on the drop down list). Both source and target are in the same directory. Source is 5000 observations with 400 vars per observation and target can take on 10 different values (recognizing digits). Any Ideas?
Before you do anything with your own data you might want to try out the example data sets available in the toolbox. That should make many problems easier to find later on because they definitely work, so you can see what's wrong with your code.
Regarding your actual question: Without more details, e.g. what your matrices contain and what their dimensions are, it's hard to help you. In your case some of the problems mentioned here might be similar to yours:
http://www.mathworks.com/matlabcentral/answers/17531-problem-with-targets-in-nprtool
From what I understand about nprtool your targets have to consist of a matrix with only one 1 (for the correct class) in either row or column (depending on the input matrix), so make sure that's the case.
I've asked this before, but I feel I wasn't clear enough so I'll try again.
I am running a network simulation, and I have several hundreds output files. Each file holds the simulation's test result for different parameters.
There are 5 different parameters and 16 different tests for each simulation. I need a method to store all this information (and again, there's a lot of it) in Matlab with the purpose of plotting graphs using a script. suppose the script input is parameter_1 and test_2, so I get a graph where parameter_1 is the X axis and test_2 is the Y axis.
My problem is that I'm not quite familier to Matlab, and I need to be directed so it doesn't take me forever (I'm short on time).
How do I store this information in Matlab? I was thinking of two options:
Each output file is imported separately to a different variable (matrix)
All output files are merged to one output file and imprted together. In the resulted matrix each line is a different output file, and each column is a different test. Problem is, I don't know how to store the simulation parameters
Edit: maybe I can use a dataset?
So, I would appreciate any suggestion of how to store the information, and what functions might help me fetch the only the data I need.
If you're still looking to give matlab a try with this problem, you can iterate through all the files and import them one by one. You can create a list of the contents of a folder with the function
ls(name)
and you can import data like this:
A = importdata(filename)
if your data is in txt files, you should consider this Prev Q
A good strategy to avoid cluttering your workspace is to import them all into a single matrix. SO if you have a matrix called VAR, then VAR{1,1}.{1,1} could be where you put your test results and VAR{1,1}.{2,1} could be where you put your simulation parameters of the first file. I think that is simpler than making a data structure. Just make sure you uniformly place the information in the same indexes of the arrays. You could also organize your VAR row v col by parameter vs test.
This is more along the lines of your first suggestion
Each output file is imported separately to a different variable
(matrix)
Your second suggestion seems unnecessary since you can just iterate through your files.
You can use the command save to store your data.
It is very convenient, and can store as much data as your hard disk can bear.
The documentation is there:
http://www.mathworks.fr/help/techdoc/ref/save.html
Describe the format of text files. Because if it has a systematic format then you can use dlmread or similar commands in matlab and read the text file in a matrix. From there, you can plot easily. If you try to do it in excel, it will be much slower than reading from a text file. If speed is an issue for you, I suggest that you don't go for Excel.