fbcnn

February 21, 2022 · View on GitHub

Use Case and High-Level Description

The fbcnn model is a flexible blind convolutional neural network to remove JPEG artifacts. Model based on "Towards Flexible Blind JPEG Artifacts Removal" paper. It was implemented in PyTorch* framework. Model works with color jpeg images. For details about this model and other jpeg artifacts removal models (for grayscale images and double jpeg restoration), check out the "Towards Flexible Blind JPEG Artifacts Removal (FBCNN, ICCV 2021)".

Specification

MetricValue
TypeImage Processing
GFLOPs1420.78235
MParams71.922
Source frameworkPyTorch*

Accuracy

Model was tested on LIVE_1 dataset.

MetricOriginal modelConverted model
PSNR34.34Db34.34Db
SSIM0.990.99

Input

Original model

Image, name - image_lq, shape - 1, 3, 512, 512, format is B, C, H, W, where:

  • B - batch size
  • C - channel
  • H - height
  • W - width

Channel order is RGB. Scale value - 255.

Converted model

Image, name - image_lq, shape - 1, 3, 512, 512, format is B, C, H, W, where:

  • B - batch size
  • C - channel
  • H - height
  • W - width

Channel order is BGR

Output

Original Model

Restored image, name - image_result, shape - 1, 3, 512, 512, output data format is B, C, H, W, where:

  • B - batch size
  • C - channel
  • H - height
  • W - width

Channel order is RGB.

Converted Model

Restored image, name - image_result, shape - 1, 3, 512, 512, output data format is B, C, H, W, where:

  • B - batch size
  • C - channel
  • H - height
  • W - width

Channel order is BGR.

Download a Model and Convert it into OpenVINO™ IR Format

You can download models and if necessary convert them into OpenVINO™ IR format using the Model Downloader and other automation tools as shown in the examples below.

An example of using the Model Downloader:

omz_downloader --name <model_name>

An example of using the Model Converter:

omz_converter --name <model_name>

Demo usage

The model can be used in the following demos provided by the Open Model Zoo to show its capabilities:

The original model is distributed under the following license.