imshow

I have computed an image with values between 0 and 255. When I use imageview(), the image is correctly displayed, in grey levels, but when I want to save this image or display it with imshow, I have a white image, or sometimes some black pixels here and there: Whereas with imageview(): Can some one help me? Matlab expects images of type double to be in the 0..1 range and images that are uint8 in the 0..255 range. You can convert the range yourself (but change values in the process), do an explicit cast (and potentially loose precision) or instruct Matlab to use the minimum and maximum value

In the .pro file: QT += core QT -= gui TARGET = latihan_2 CONFIG += console CONFIG -= app_bundle TEMPLATE = app SOURCES += main.cpp INCLUDEPATH += E:\OpenCV\OpenCV\opencv\build\include LIBS += E:\OpenCV\OpenCV\opencv\build\x86\mingw\lib\libopencv_core246.dll.a LIBS += E:\OpenCV\OpenCV\opencv\build\x86\mingw\lib\libopencv_highgui246.dll.a LIBS += E:\OpenCV\OpenCV\opencv\build\x86\mingw\lib\libopencv_imgproc246.dll.a LIBS += E:\OpenCV\OpenCV\opencv\build\x86\mingw\lib\libopencv_features2d246.dll.a LIBS += E:\OpenCV\OpenCV\opencv\build\x86\mingw\lib\libopencv_calib3d246.dll.a In main.cpp :

I'm currently working to plot some labels over the x,y axis in imshow, but over 95% of the points sit in the 0-0.2 range, whereas less than 10% sit in the 0.2-1.0 range. Using the default 'jet' colourmap, this results in almost all the plots showing up as blue, even though there is variance in 95% of the data that becomes visually unobservable. Is there a way to tell matplotlib to, for example, quadruple the rate at which the colours change in the 0.0-0.1 range, and scale the remaining 0.2-1.0 range accordingly? Any help would be greatly appreciated. Thanks in advance! EDIT: Seeing at this is

I have imported an image. I have parsed it to double precision and performed some filtering on it. When I plot the result with imshow , the double image is too dark. But when I use imshowpair to plot the original and the final image, both images are correctly displayed. I have tried to use uint8 , im2uint8 , multiply by 255 and then use those functions, but the only way to obtain the correct image is using imshowpair . What can I do? It sounds like a problem where the majority of your intensities / colour data are outside the dynamic range of what is accepted for imshow when showing double

I'm making a figure with a total of 68 subplots and want to remove the empty space between them all. Here's what I have: . How would I go about doing this? EDIT: using plt.tight_layout() makes it even worse: Here's my code: for j in range(0,len(sort_yf)): for i in range(0,len(yf)): if yf[i]==sort_yf[j]: sort_ID=np.append(sort_ID,'output/'+ID[i]+'.png') for i in range (1,69): plt.subplot(17,4,i,aspect='equal') plots=img.imread(sort_ID[i]) plt.imshow(plots) plt.axis('off') plt.show() Have you tried the tight layout functionality? plt.tight_layout() See also HERE EDIT : Alternatively, you can use

I'd like to display some images while doing a numpy computation: import numpy as np import matplotlib.pyplot as plt plt.ion() # Turn the interactive mode on. for i in range(100): A = np.random.randn(10,10) plt.imshow(A) plt.pause(0.001) # do some other numpy computations here (they take < 1 ms) Instead of displaying the images quickly, it is rather slow . I'm not asking for 100 frames per second, but I thought 30 fps would be possible, but it's not: after a few iterations, I'm close to 2 fps on my standard i5 laptop (Windows 7 x64). How to have a faster imshow refresh rate? Notes: I've already