Skip to main content

Deep Guided Filtering Layer for PyTorch

Project description

[Project] [Paper] [arXiv] [Demo] [Home]

Official implementation of Fast End-to-End Trainable Guided Filter.
Faster, Better and Lighter for pixel-wise image prediction.


Fast End-to-End Trainable Guided Filter
Huikai Wu, Shuai Zheng, Junge Zhang, Kaiqi Huang
CVPR 2018


pip install guided-filter-pytorch


from guided_filter_pytorch.guided_filter import FastGuidedFilter

hr_y = FastGuidedFilter(r, eps)(lr_x, lr_y, hr_x)
from guided_filter_pytorch.guided_filter import GuidedFilter

hr_y = GuidedFilter(r, eps)(hr_x, init_hr_y)
from guided_filter_pytorch.guided_filter import ConvGuidedFilter

hr_y = ConvGuidedFilter(r, norm)(lr_x, lr_y, hr_x)


  title     = {Fast End-to-End Trainable Guided Filter},
  author    = {Wu, Huikai and Zheng, Shuai and Zhang, Junge and Huang, Kaiqi},
  booktitle = {CVPR},
  year = {2018}

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

guided_filter_pytorch-3.7.5.tar.gz (3.8 kB view hashes)

Uploaded source

Built Distribution

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page