PerceptNet / README.md
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metadata
license: afl-3.0
tags:
  - tensorflow
  - feature_extraction
  - image
  - perceptual_metric
datasets:
  - tid2008
  - tid2013
metrics:
  - pearsonr
model_index:
  - name: PerceptNet
  - task:
      type: feature_extraction
      name: Perceptual Distance
    dataset:
      type: image
      name: tid2013
    metrics:
      - type: pearsonr
        value: 0.93
        name: TID2013

PerceptNet

PercepNet model trained on TID2008 and validated on TID2013, obtaining 0.97 and 0.93 Pearson Correlation respectively.

Link to the run: https://wandb.ai/jorgvt/PerceptNet/runs/28m2cnzj?workspace=user-jorgvt

Usage

As of now to use the model you have to install the PerceptNet repo to get access to the PerceptNet class where you will load the weights available here like this:

from perceptnet.networks import PerceptNet

weights_path = get_file(fname='perceptnet_rgb.h5',
                        origin='https://huggingface.co/Jorgvt/PerceptNet/blob/main/final_model_rgb.h5')
model = PerceptNet(kernel_initializer='ones', gdn_kernel_size=1, learnable_undersampling=False)
model.build(input_shape=(None, 384, 512, 3))
model.load_weights(weights_path)