I am trying to debug a custom loss function and I would like to visualize the images generated during the intermediate computation step in the objective function. A tf_summary_image or a simple imshow would be perfect, but the summary it is not working without calling a sess.run() with a proper feed_dict. For simplicity, let's say I have:
def custom_objective(y_pred, y_true):
diff = y_pred - y_true
#Here I would need something to save and/or show the diff image
square = K.square(diff)
#Here I would need something to save and/or show the square image
mean = K.mean(square, axis=-1)
return mean
Any suggestions?
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');
I am using Paraview 5.0.1. If any solution requires updating, I can try.
I want to programmatically obtain field plots (and corresponding PlotOverLine) of displacements and stresses in rotated coordinate systems.
What are appropriate/convenient/possible ways of doing this?
So far, I have created one Calculator filter for each component of displacements and stresses.
For instance, I used Calculators in 2D with results
(displacement.iHat)*cos(0.7853981625)+(displacement.jHat)*sin(0.7853981625)
(stress_3-stress_0)*sin(45.0*3.14159265/180)*cos(45.0*3.14159265/180)+stress_1*((cos(45.0*3.14159265/180))^2-(sin(45.0*3.14159265/180))^2)
It works fine, but it is quite cumbersome, in several aspects:
Creating them (one filter per component).
Plotting several of them in a single XY plot
Exporting them (one export per component).
Is there a simple way to do this?
PS: The Transform filter does not accomplish this. It rotates the view, not the fields.
Two solutions:
Ugly, inneficient solution
Use Transform and check "Transform All Input vectors"
Add a calculator and add a dummy array
Use transform the other way around, without checking "Transform All Input vectors"
Correct solution :
Compute the transformation yourself in a programmable filter
input = self.GetUnstructuredGridInput();
output = self.GetUnstructuredGridOutput();
output.ShallowCopy(input)
data = input.GetPointData().GetArray("YourArray")
vec = vtk.vtkDoubleArray();
vec.SetNumberOfComponents(3);
vec.SetName("TransformedVectors");
numPoints = input.GetNumberOfPoints()
for i in xrange(0, numPoints):
tuple = data.GetTuple(i)
transform(tuple) # implement the transform in python
vec.InsertNextTuple(tuple)
output.GetPointData().AddArray(vec)
Using python 3.4 in linux and windows, I'm trying to create qr code images from a list of string objects. I don't want to just store the image as a file because the list of strings may change frequently. I want to then tile all the objects and display the resulting image on screen for the user to scan with a barcode scanner. For the user to know which code to scan I need to add some text to the qr code image.
I can create the list of image objects correctly and they are in a list and calling .show on these objects displays them properly but I don't know how to treat these objects as a file object to open them. The object that is given to the open function, (img_list[0] in my case), in my add_text_to_img needs to support read, seek and tell methods. When I try this as is I get an attribute error. I've tried BytesIO and StringIO but I get an error message that Image.open does not support buffer interface. Maybe I am not doing that part correctly.
I'm sure there are several ways to do this, but what is the best way to open in memory objects as a file object?
from io import BytesIO
import qrcode
from PIL import ImageFont, ImageDraw, Image
def make_qr_image_list(code_list):
"""
:param code_list: a list of string objects to encode into QR code image
:return: a list of image or some type of other data objects
"""
img_list = []
for item in code_list:
qr = qrcode.QRCode(
version=None,
error_correction=qrcode.ERROR_CORRECT_L,
box_size=4,
border=10
)
qr.add_data(item)
qr_image = qr.make_image(fit=True)
img_list.append(qr_image)
return img_list
def add_text_to_img(text_list, img_list):
"""
While I was working on this, I am only saving the first image. Once
it's working, I'll save the rest of the images to a list.
:param text_list: a list of strings to add to the corresponding image.
:param img_list: the list containing the images already created from
the text_list
:return:
"""
base = Image.open(img_list[0])
# img = Image.frombytes(mode='P', size=(164,164), data=img_list[0])
text_img = Image.new('RGBA', base.size, (255,255,255,0))
font = ImageFont.truetype('sans-serif.ttf', 10)
draw = ImageDraw.Draw(text_img)
draw.text((0,-20),text_list[0], (0,0,255,128), font=font)
# include some method to save the images after the text
# has been added here. Shouldn't actually save to a file.
# Should be saved to memory/img_list
output = Image.alpha_composite(base,text_img)
output.show()
if __name__ == '__main__':
test_list = ['AlGaN','n-AlGaN','p-AlGaN','MQW','LED AlN-AlGaN']
image_list = make_qr_image_list(test_list)
add_text_to_img(test_list, image_list)
im = image_list[0]
im.save('/my_save_path/test_image.png')
im.show()
Edit: I've been using python for about a year and I feel like this is a pretty common thing to do but I'm not even sure that I'm looking up/searching for the right terms. What topics would you search for to answer this? If anyone can post a link or two to what I need to read up on regarding this, that would be very appreciated.
You already have PIL image objects; qr.make_image() returns the (a wrapper around) the right type of object and you do not need to open them again.
As such, all you need to do is:
base = img_list[0]
and go from there.
You do need to match image modes when compositing; QR codes are black-and-white images (mode 1), so either convert that or use the same mode in your text_img image object. The Image.alpha_composite() operation does require that both images have an alpha channel. Converting the base is easy:
base = img_list[0].convert('RGBA')
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 have a folder which contains images (100) from the experiment that I did. I also have another folder which contains the background images (100 also) from the detector.
I have written a code that does something like this:
% Define images directory
% Define detector bg directory
% Loop over each frame and do some processing
for a=1:length(image directory)
%read files from directory
bg_corrected_image = frame#-bg_image# % # begins with 1
n=size(image directory)
new_images=zeros(n)
% Now sort through each pixel in bg_corrected image and assign value according to a criterion
for ii=1:size(bg_corrected_image,1)
jj=1:size(bg_corrected_image,2)
pixel=bg_corrected_image(ii,jj);
if pixel>500
pix_mod=0;
elseif pixel<30
pix_mod=0;
else
pix_mod=pixel;
end
new_image(ii,jj)=pix_mod;
end
******************* CODE TO SAVE IMAGE AND NOT OVERWRITE AFTER EACH
ITERATION OF LOOP?
end
What I want to do now is to save each image(frame) after it had gone through the pixel sorting regimen so that I can just sum them all after the loop has ended. I am not too sure what is the best way to do it? I think what I need to do is to create a cell array which saves a "new_image" after each iteration and the code for that should go where I put asteriks. Please note I don't want to save images earlier in my code. Any help much appreciated.
Maybe something like the below - load in all your images to a 3D matrix "imagestack", then process them all, then output them all. Note the vectorization on the pixel replacement here will be much faster than your for-loop iteration over the pixels.
IMAGECOUNT=100;
FILEPATH_IN='images/input/%d.jpg';
FILEPATH_OUT='images/output/%d.jpg';
I=imread(sprintf(FILEPATH,1));
[hei wid]=size(I);
imagestack=zeros(hei,wid,100);
for n=1:IMAGECOUNT
imagestack(:,:,n)=imread(sprintf(FILEPATH_IN,n));
end
imagestack(imagestack>500)=0;
imagestack(imagestack<30)=0;
for n=1:IMAGECOUNT
imwrite(imagestack(:,:,n),sprintf(FILEPATH_OUT,n));
end