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 io
import 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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