We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Hi, I would like to use your Rain Rendering research for my PhD research in domain adaptation on a custom dataset.
I extracted the depth maps from Midas v3.1, which are 3 channels scaled between 0 and 1 and dtype = float32.
You wrote : # Depth images (16 bits, with depth_in_meter = depth/256.)
So am I supposed to do something like :
depth = depth.mean(0) # [3, H, W] to [H, W] focal_length, baseline = 2262, 0.22 depth = (baseline * focal_length) / (depth*2048) depth_enc = np.minimum(depth * 256., 2 ** 16 - 1).astype(np.uint16)
And just use the final depth_enc as depth labels or just feed the model the original depth maps ?
Thanks !
The text was updated successfully, but these errors were encountered:
No branches or pull requests
Hi, I would like to use your Rain Rendering research for my PhD research in domain adaptation on a custom dataset.
I extracted the depth maps from Midas v3.1, which are 3 channels scaled between 0 and 1 and dtype = float32.
You wrote : # Depth images (16 bits, with depth_in_meter = depth/256.)
So am I supposed to do something like :
And just use the final depth_enc as depth labels or just feed the model the original depth maps ?
Thanks !
The text was updated successfully, but these errors were encountered: