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
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