Converting this 16-bit grayscale image to 'L' mode destroys it

[ExplodingCabbage]

Here is a 16-bit grayscale image:

It clearly contains a gradient of grays.

If I open it with Pillow, convert it to 8-bit grayscale, and save it, like so...

>>> from PIL import Image
>>> test_img = Image.open('test.png')
>>> test_img.mode
'I'
>>> test_img.convert('L').save('out.png')

... then I get this, which is mostly completely white:

This conversion should work; according to http://pillow.readthedocs.io/en/4.2.x/handbook/tutorial.html#converting-between-modes

The library supports transformations between each supported mode and the “L” and “RGB” modes.

and according to http://pillow.readthedocs.io/en/latest/handbook/concepts.html#modes, I is a supported mode.

Notably, I don't see this same problem if I start by loading an 8-bit RGB image from a JPG and then do .convert('I').convert('L'), so it's not simply the case that I->L conversion is broken in general. I'm not what specifically leads to the breakage in this case.

[wiredfool]

There's a longstanding behavioral issue with Pillow where conversions don't intelligently use the range of the target mode.

So, in this case, you're taking an image with values from 0-65k and converting it to 0-255, with clipping. Most of the values are > 255, so they're all white. When you start with an 8 bit image, you convert 0-255 to 0-65k, but since there's no promotion, it's still just a 0-255 image. Converting back is then not a problem.

[radarhere]

This looks related to #3159

[radarhere]

I've created PR #3838 to resolve this.

[radarhere]

Resolved by #3838