-
Notifications
You must be signed in to change notification settings - Fork 613
New issue
Have a question about this project? # for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “#”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? # to your account
dense_image_warp with other interpolation schemes #2733
Comments
To avoid duplications as we had also a request related to elastic image warping in Keras-cv can you try to open a ticket there? |
You mean replying to the existing issue or raise a new issue? |
As you like |
TensorFlow Addons is transitioning to a minimal maintenance and release mode. New features will not be added to this repository. For more information, please see our public messaging on this decision: Please consider sending feature requests / contributions to other repositories in the TF community with a similar charters to TFA: |
Currently,
dense_image_warp
uses only bilinear interpolation. It would be beneficial to use other interpolation schemes for better quality or different tradeoffs.Other interpolation schemes are already available in other operations such as resize (Lanczos interpolation 3x3 or 5x5).
tf.image.resize(in, new_size, method = tf.image.ResizeMethod.LANCZOS5)
Relevant information
https://github.com/Luvideria/tensorflow-dense-warp-catmull-rom
Which API type would this fall under (layer, metric, optimizer, etc.)
image
Who will benefit with this feature?
Anyone using
dense_image_warp
and looking for more quality rather than speed.The text was updated successfully, but these errors were encountered: