Hi Imanol, It works fine now, thanks for your suggestions. Regarding the second part of my question. If I read the image using matlibplot instead of skimage, i.e., output=plt.imread(os.path.join(image_path,raw_image_name)) I found that the pixel values of output were all changed, and they becomes either 255. or 0. which causes the image shown as all black. What are the possible reasons for plt.imread. Thanks. Yuanyuan On Sun, Dec 11, 2016 at 4:54 AM, Imanol Luengo < imanol.luengo@nottingham.ac.uk> wrote:

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.

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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