I want to create .NET application that accepts an image and scans all images in a folder and find those that look similar it.
Any suggestion where I should start? Are there any free/open source libraries?
You could use AForge.NET. The ExhaustiveTemplateMatching method does exactly that. There's an example in the documentation:
// create template matching algorithm's instance
// use zero similarity to make sure algorithm will provide anything
ExhaustiveTemplateMatching tm = new ExhaustiveTemplateMatching( 0 );
// compare two images
TemplateMatch[] matchings = tm.ProcessImage( image1, image2 );
// check similarity level
if ( matchings[0].Similarity > 0.95f )
{
// do something with quite similar images
}
Related
In an old version of my code, I used to do a hardcopy() with a given resolution, ie:
frame = hardcopy(figHandle, ['-d' renderer], ['-r' num2str(round(pixelsperinch))]);
For reference, hardcopy saves a figure window to file.
Then I would typically perform:
ZZ = rgb2gray(frame) < 255/2;
se = strel('disk',diskSize);
ZZ2 = imdilate(ZZ,se); %perform dilation.
Surface = bwarea(ZZ2); %get estimated surface (in pixels)
This worked until I switched to Matlab 2017, in which the hardcopy() function is deprecated and we are left with the print() function instead.
I am unable to extract the data from figure handler at a specific resolution using print. I've tried many things, including:
frame = print(figHandle, '-opengl', strcat('-r',num2str(round(pixelsperinch))));
But it doesn't work. How can I overcome this?
EDIT
I don't want to 'save' nor create a figure file, my aim is to extract the data from the figure in order to mesure a surface after a dilation process. I just want to keep this information and since 'im processing a LOT of different trajectories (total is approx. 1e7 trajectories), i don't want to save each file to disk (this is costly, time execution speaking). I'm running this code on a remote server (without a graphic card).
The issue I'm struggling with is: "One or more output arguments not assigned during call to "varargout"."
getframe() does not allow for setting a specific resolution (it uses current resolution instead as far as I know)
EDIT2
Ok, figured out how to do, you need to pass the '-RGBImage' argument like this:
frame = print(figHandle, ['-' renderer], ['-r' num2str(round(pixelsperinch))], '-RGBImage');
it also accept custom resolution and renderer as specified in the documentation.
I think you must specify formattype too (-dtiff in my case). I've tried this in Matlab 2016b with no problem:
print(figHandle,'-dtiff', '-opengl', '-r600', 'nameofmyfig');
EDIT:
If you need the CData just find the handle of the corresponding axes and get its CData
f = findobj('Tag','mytag')
Then depending on your matlab version use:
mycdata = get(f,'CData');
or directly
mycdta = f.CData;
EDIT 2:
You can set the tag of your image programatically and then do what I said previously:
a = imshow('peppers.png');
set(a,'Tag','mytag');
This just came up, I have an answer but I wanted to share it here...
"Is it possible to create an iris constraint based on cell_methods?"
I have a datafile which loads producing many cubes.
I would like to extract only those containing ensemble spread, which I can identify from their cell_methods, which are set to:
(CellMethod(method=u'standard_deviation', coord_names=(u'realization',), intervals=(), comments=()),)
Is there a way to filter the load so that I only read in the desired "ensemble spread" data ?
You will need to use the "cube_func" approach for this.
http://scitools.org.uk/iris/docs/latest/iris/iris.html?highlight=constraint#iris.Constraint
So, something very roughly like ...
def cube_is_mean(cube):
return any(cm.method == 'mean' for cm in cube.cell_methods)
means_constraint = iris.Constraint(cube_func=cube_is_mean)
I'm trying to figure out how to use JSL to write some of the analysis of variance variables values to a table in JMP. My idea is to write a script that runs different types of models with different parameters with R^2 and RSME logging to a table (maybe there is a better way to do this I'm on my second day of JMP). Going through the documentation it seems that different analysis have different ways of doing this and I can't find one for "fit model". I also will need to know how to do this for a neural network which I think I may have found the documentation for.
If you're doing something like screening variables to determine an optimized model, you're in the right place with the fit model platform. However, running the fit model in a loop without human judgment in model selection as you've suggested isn't necessarily expedient.
So at the expense of trying to make JMP/JSL do something it's not really suited for, one way to achieve your generic goal of grabbing text from the fit model platform output is to send your platform to a "report" and then pull from that "report" the data you want, and then send it to a data table. From that data table, you can concatenate it with another data table and you would have your log. That's the idea, here's an example, for some dummy data "Ydata" and "Xdata":
thing = Fit Model(
Y( :Ydata ),
Effects( :Xdata ),
Personality( Standard Least Squares ),
Emphasis( Minimal Report ),
Run(
:Ydata << {Plot Actual by Predicted( 0 ),
Plot Residual by Predicted( 0 ), Plot Effect Leverage( 0 )}
)
);
thing_report = thing<<report;
thing_report_dt_ref = thing_report["Summary of Fit"][1] << make into data table;
//alternatively
//thing_report_dt_ref = thing_report[TableBox(1)] << make into data table;
thing_report_dt_ref << Set Name("Choose_a_name_for_your_new_data_table");
You'd have to handle the looping part, but if you can do it once, you can do it N times.
Because JMP/JSL is stupid, you can alternatively call the "Summary of Fit" directly if your know it's name in the tree structure. In my case, its name was "TableBox(1)". Do:
thing << show tree structure
To see where your data lives in the platform display box.
I'm looking at implementing a Caffe CNN which accepts two input images and a label (later perhaps other data) and was wondering if anyone was aware of the correct syntax in the prototxt file for doing this? Is it simply an IMAGE_DATA layer with additional tops? Or should I use separate IMAGE_DATA layers for each?
Thanks,
James
Edit: I have been using the HDF5_DATA layer lately for this and it is definitely the way to go.
HDF5 is a key value store, where each key is a string, and each value is a multi-dimensional array. Thus, to use the HDF5_DATA layer, just add a new key for each top you want to use, and set the value for that key to store the image you want to use. Writing these HDF5 files from python is easy:
import h5py
import numpy as np
filelist = []
for i in range(100):
image1 = get_some_image(i)
image2 = get_another_image(i)
filename = '/tmp/my_hdf5%d.h5' % i
with hypy.File(filename, 'w') as f:
f['data1'] = np.transpose(image1, (2, 0, 1))
f['data2'] = np.transpose(image2, (2, 0, 1))
filelist.append(filename)
with open('/tmp/filelist.txt', 'w') as f:
for filename in filelist:
f.write(filename + '\n')
Then simply set the source of the HDF5_DATA param to be '/tmp/filelist.txt', and set the tops to be "data1" and "data2".
I'm leaving the original response below:
====================================================
There are two good ways of doing this. The easiest is probably to use two separate IMAGE_DATA layers, one with the first image and label, and a second with the second image. Caffe retrieves images from LMDB or LEVELDB, which are key value stores, and assuming you create your two databases with corresponding images having the same integer id key, Caffe will in fact load the images correctly, and you can proceed to construct your net with the data/labels of both layers.
The problem with this approach is that having two data layers is not really very satisfying, and it doesn't scale very well if you want to do more advanced things like having non-integer labels for things like bounding boxes, etc. If you're prepared to make a time investment in this, you can do a better job by modifying the tools/convert_imageset.cpp file to stack images or other data across channels. For example you could create a datum with 6 channels - the first 3 for your first image's RGB, and the second 3 for your second image's RGB. After reading this in using the IMAGE_DATA layer, you can split the stream into two images using a SLICE layer with a slice_point at index 3 along the slice_dim = 1 dimension. If further down the road, you decide that you want to load even more complex assortments of data, you'll understand the encoding scheme and can write your own decoding layer based off of src/caffe/layers/data_layer.cpp to gain full control of the pipeline.
You may also consider using HDF5_DATA layer with multiple "top"s
I need to create a simple array of some images. So that later on I can traverse through the array easily using a loop and access all the images one by one.
Just tell me the declaration part of storing the images into an array.
I will be having 5 images named as 1.png to 5.png which I need to access.
Will it be a string array or integer array ?
Array of ImageIcon:
ImageIcon[] images = new ImageIcon[5];
images[0] = new ImageIcon("path/to/image");
....
Your question is confusing. You clearly know what an array is and how to use it, but you don't know what type to use? Why, whichever type you want to use, of course. You could use String, or whatever class you usually use to represent an image.