Mailman 3 December 2016 - scikit-image

Re: [scikit-image] pixel value changes during reading image and showing images using skimage and matplotlib
by Imanol Luengo 11 Dec '16

11 Dec '16

Dear Yuanyuan, The reason why you are looking at a *color* image is due to the colormaps: http://matplotlib.org/users/colormaps.html The default colormap (to map from numbers to colors) is not grayscale, as matplotlib is not primarly focus on images, and grayscale is not an *adequate* colormap to represent other types of plots. To properly visualize your image specify a colormap to the plot function: plt.imshow(output, 'gray') Cheers, Imanol On 11/12/16 06:46, wine lover wrote: > Dear All, > > I have a tif images, its type is |float32|, shape is |(128*128)| (a > grayscale image). All the pixel values are of range |[0.0, 1.0]| > > I am trying to read it using |skimage| and show it on screen using > |matplotlib|. > > |fromskimage importio importmatplotlib.pyplot asplt > output=io.imread(os.path.join(image_path,raw_image_name))print(output.dtype)print(output.shape)print(output.max())print(output.min())plt.imshow(output)plt.show()| > > The output image looks like color image instead of gray image as shown > originally. I attached the screenshot as the capture-1.jpg. > > However, when I read the image using |matplotlib| instead,i.e., > |output=plt.imread(os.path.join(image_path,raw_image_name))|. I found > that pixel value will become 255 and 0. The dtype is still float32. > But when I print output, the pixel values are either 0. or 255. > > The output image will become black as shown in the second image > (capture-2.jpg). I am confused how does this work? My guess is that > there are some dtype changes happening during the reading image and > showing image, > > > Thanks, > > Yuanyuan > > > > _______________________________________________ > scikit-image mailing list > scikit-image(a)python.org > https://mail.python.org/mailman/listinfo/scikit-image This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please send it back to me, and immediately delete it. Please do not use, copy or disclose the information contained in this message or in any attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. This message has been checked for viruses but the contents of an attachment may still contain software viruses which could damage your computer system, you are advised to perform your own checks. Email communications with the University of Nottingham may be monitored as permitted by UK legislation.

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pixel value changes during reading image and showing images using skimage and matplotlib
by wine lover 11 Dec '16

11 Dec '16

Dear All, I have a tif images, its type is float32, shape is (128*128) (a grayscale image). All the pixel values are of range [0.0, 1.0] I am trying to read it using skimage and show it on screen using matplotlib . from skimage import ioimport matplotlib.pyplot as plt output=io.imread(os.path.join(image_path,raw_image_name))print(output.dtype)print(output.shape)print(output.max())print(output.min()) plt.imshow(output) plt.show() The output image looks like color image instead of gray image as shown originally. I attached the screenshot as the capture-1.jpg. However, when I read the image using matplotlib instead,i.e., output=plt.imread(os.path.join(image_path,raw_image_name)). I found that pixel value will become 255 and 0. The dtype is still float32. But when I print output, the pixel values are either 0. or 255. The output image will become black as shown in the second image (capture-2.jpg). I am confused how does this work? My guess is that there are some dtype changes happening during the reading image and showing image, Thanks, Yuanyuan

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GLCM and angles
by Igor Karlovits 09 Dec '16

09 Dec '16

Hello everybody I would have a question regarding the results of graycoprops which is giving me the same results for all attributes (energy, ASM etc...) in angles of rotation of 135 and 90. Angles 0, 45 and 90 are ok (with an offset of 1) but the angle 135 is giving the same results as 90? Any explanation of this? Thanks

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Re: [scikit-image] how to correctly save an numpy array with float32 type into an image
by Juan Nunez-Iglesias 08 Dec '16

08 Dec '16

Hi Yuanyuan, This warning is raised when the value range of a float image is less than 1/256, because in those cases, most image viewers will show the image as having a single shade of grey. For example, if you have an image of physical measurements in the range [0, 1e-5], and you save that as float, in many viewers it will appear as all black. It is not something to worry about if you just want to save the data for later. We implemented it to help you figure out what is happening when the image doesn’t “look right” in a viewer. =) Juan. On 8 Dec. 2016, 10:51 AM +1100, wine lover <winecoding(a)gmail.com>, wrote: > Hi Juan, Hi Imanol, > > Thank you so much for your replies, which are very helpful. > > During saving the image, I got some warning messages such as follows. What does it indicate? > /development/lib/python3.4/site-packages/scikit_image-0.12.3-py3.4-linux-x86_64.egg/skimage/io/_io.py:132: UserWarning: /data/train/image_sampled.tif is a low contrast image > warn('%s is a low contrast image' % fname) > > Thanks, > Yuanyuan > > > On Wed, Dec 7, 2016 at 4:54 AM, Imanol Luengo <imanol.luengo(a)nottingham.ac.uk> wrote: > > > Hello, > > > I would say there are two differences between 'Saving the data' and 'Displaying the data'. An image is discretized to `uint8` or `uint16` prior to being saved as standard formates (`.png` or `.jpg`). You could do something like > > > ``` > > > import numpy as np > > > from skimage import io, util > > > > > > A = np.random.rand(100,100) > > > io.imsave('tmp.png', A) > > > B = util.img_as_float(io.imread('tmp.png') > > > > > > assert np.allclose(A, B) # ERROR > > > ``` > > > But you will find some discretization errors, which makes `B != A`. Having said that, if you want to preserve the data in `B`, I think the best option is to export the data using another format, e.g. numpy arrays: > > > ``` > > > import numpy as np > > > > > > A = np.random.rand(100,100) > > > np.save('tmp.npy', A) > > > B = np.load('tmp.npy') > > > > > > assert np.allclose(A, B) # True > > > ``` > > > Or alternatively, if you really want to save the data in a visualizable format, exporting the image as `.tif` format, which preserves data information, should also work: > > > ``` > > > A = np.random.rand(100,100) > > > io.imsave('tmp.tif', A) > > > B = io.imread('tmp.tif') > > > > > > assert np.allclose(A, B) # True > > > ``` > > > However, I would personally store my data in non-visualizable formats such as `.npy, .h5` (the later if you work with tons of data) as they usually offer another advantages (e.g. Datasets in HDF5). > > > Hope it helps, > > > Imanol > > > > > > On 07/12/16 04:41, wine lover wrote: > > > > Dear All, > > > > > > > > In a program, I generate an numpy array, with shape (128,128), which is supposed to represent an image. > > > > For instance, I have an array temp_mask, which is of type float32 and shape (128,128), the maximum value is 1.0 and the minimum value is 0.0. I saved it using io.imsave(‘mask_image’,temp_mask) However, after I re-opened this image using img_mask = io.imread(‘mask_image’). The read image turns out to have type unit16, the max value becomes 65535 and the min value is 0 . It seems to me that io.imsave automatically transform the float32 array into an unit16 array. > > > > Is it possible to save the image while keeping the original type? If not, what’s the correct way to save an image represented as an array, with type float32 and the range of value [0.0,1.0]? > > > > > > > > Thank you very much! > > > > > > > > > > > > > > > > _______________________________________________ > > > > scikit-image mailing list > > > > scikit-image(a)python.org > > > > https://mail.python.org/mailman/listinfo/scikit-image > > > > > > > > > > > > > This message and any attachment are intended solely for the addressee > > > and may contain confidential information. If you have received this > > > message in error, please send it back to me, and immediately delete it. > > > > > > Please do not use, copy or disclose the information contained in this > > > message or in any attachment. Any views or opinions expressed by the > > > author of this email do not necessarily reflect the views of the > > > University of Nottingham. > > > > > > This message has been checked for viruses but the contents of an > > > attachment may still contain software viruses which could damage your > > > computer system, you are advised to perform your own checks. Email > > > communications with the University of Nottingham may be monitored as > > > permitted by UK legislation. > > > > > > _______________________________________________ > > > scikit-image mailing list > > > scikit-image(a)python.org > > > https://mail.python.org/mailman/listinfo/scikit-image > > > > > _______________________________________________ > scikit-image mailing list > scikit-image(a)python.org > https://mail.python.org/mailman/listinfo/scikit-image

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Re: [scikit-image] how to correctly save an numpy array with float32 type into an image
by Imanol Luengo 07 Dec '16

07 Dec '16

Hello, I would say there are two differences between 'Saving the data' and 'Displaying the data'. An image is discretized to `uint8` or `uint16` prior to being saved as standard formates (`.png` or `.jpg`). You could do something like ``` import numpy as np from skimage import io, util A = np.random.rand(100,100) io.imsave('tmp.png', A) B = util.img_as_float(io.imread('tmp.png') assert np.allclose(A, B) # ERROR ``` But you will find some discretization errors, which makes `B != A`. Having said that, if you want to preserve the data in `B`, I think the best option is to export the data using another format, e.g. numpy arrays: ``` import numpy as np A = np.random.rand(100,100) np.save('tmp.npy', A) B = np.load('tmp.npy') assert np.allclose(A, B) # True ``` Or alternatively, if you really want to save the data in a visualizable format, exporting the image as `.tif` format, which preserves data information, should also work: ``` A = np.random.rand(100,100) io.imsave('tmp.tif', A) B = io.imread('tmp.tif') assert np.allclose(A, B) # True ``` However, I would personally store my data in non-visualizable formats such as `.npy, .h5` (the later if you work with tons of data) as they usually offer another advantages (e.g. Datasets in HDF5). Hope it helps, Imanol On 07/12/16 04:41, wine lover wrote: > > Dear All, > > > In a program, I generate an numpy array, with shape (128,128), which > is supposed to represent an image. > > For instance, I havean array |temp_mask|, which is of type|float32 and > shape (128,128)|, the maximum value is|1.0|and the minimum value > is|0.0. |I saved it using|io.imsave(‘mask_image’,temp_mask)|However, > after I re-opened this image using|img_mask = > io.imread(‘mask_image’)|. The read image turns out to have > type|unit16|, the max value becomes|6553|5 and the min value is|0| . > It seems to me that io.imsave automatically transform the float32 > array into an unit16 array. > > Is it possible to save the image while keeping the original type? If > not, what’s the correct way to save an image represented as an array, > with type|float32|and the range of value |[0.0,1.0]|? > > > Thank you very much! > > > > _______________________________________________ > scikit-image mailing list > scikit-image(a)python.org > https://mail.python.org/mailman/listinfo/scikit-image This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please send it back to me, and immediately delete it. Please do not use, copy or disclose the information contained in this message or in any attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. This message has been checked for viruses but the contents of an attachment may still contain software viruses which could damage your computer system, you are advised to perform your own checks. Email communications with the University of Nottingham may be monitored as permitted by UK legislation.

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how to correctly save an numpy array with float32 type into an image
by wine lover 07 Dec '16

07 Dec '16

Dear All, In a program, I generate an numpy array, with shape (128,128), which is supposed to represent an image. For instance, I have an array temp_mask, which is of type float32 and shape (128,128), the maximum value is 1.0 and the minimum value is 0.0. I saved it using io.imsave(‘mask_image’,temp_mask) However, after I re-opened this image using img_mask = io.imread(‘mask_image’). The read image turns out to have type unit16, the max value becomes 65535 and the min value is 0 . It seems to me that io.imsave automatically transform the float32 array into an unit16 array. Is it possible to save the image while keeping the original type? If not, what’s the correct way to save an image represented as an array, with type float32 and the range of value [0.0,1.0]? Thank you very much!

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