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Weird image output from trained model #27

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hsinpa opened this issue May 10, 2020 · 2 comments
Open

Weird image output from trained model #27

hsinpa opened this issue May 10, 2020 · 2 comments

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@hsinpa
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hsinpa commented May 10, 2020

Hi Diana
After loading mobilenet-nnconv5-skipadd-pruned
The last layer "decode_conv6" output numbers between 1 to 5, whether I normalized my input image or not.

Its clearly not a normalized image and too bright for image between [0-255].
Not sure where I do wrong, or the output is not means for gray image?

@dwofk
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dwofk commented Jul 30, 2020

Hi @hsinpa

The output from the model contains values that should correspond to depth measurements in meters -- in this case, numbers between 1 and 5 should correspond to estimated depth of 1 to 5 meters. To properly visualize this output, depth values need to be shifted to zero (by subtracting minimum depth) and then normalized by the depth range. A colormap can then be applied, as in https://github.com/dwofk/fast-depth/blob/master/deploy/data/visualize.py#L9.

The input RGB image fed into the model should indeed be divided by 255 so that input values are in the [0-1] range.

@sunmengnan
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could you share the training script? Thx

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