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FGRestore Dataset README

This directory contains the FGRestore data and annotations for two tasks:

  • Image quality score prediction (Regression)
  • Pairwise preference prediction (Rank)

Directory Layout

  • annotations/IR_train.json: training set (contains both score and preference annotations)
  • annotations/test_single/: test split for score prediction
  • annotations/test_pairs/: test split for pairwise preference prediction
  • images/: distorted or restored images
  • ref/: reference images

Annotation Formats

1) Training: annotations/IR_train.json

Each sample is a pairwise record with both preference and score labels. Typical fields:

  • ref_image: reference image path relative to FGRestore (for example, ref/000000.png)
  • image_nameA: candidate image A path (for example, images/000000.png)
  • image_nameB: candidate image B path (for example, images/000001.png)
  • human_preference_for_A: human preference label
    • 1: A is preferred over B
    • 0: B is preferred over A
    • 0.5: tie between A and B
  • score_normA: normalized score of image A
  • score_normB: normalized score of image B
  • task: restoration task name (for example, Denoising)
  • scene_id: scene identifier

2) Score Test Split: annotations/test_single/

Used to evaluate score prediction performance. Each record is a single-image sample. Typical fields:

  • ref_image
  • image_name
  • score_norm
  • task
  • scene_id

3) Preference Test Split: annotations/test_pairs/

Used to evaluate pairwise preference performance. Each record is a pairwise sample. Typical fields:

  • ref_image
  • image_nameA
  • image_nameB
  • human_preference_for_A (can be 0, 0.5, or 1)
  • score_normA
  • score_normB
  • task
  • scene_id

Official Train/Test Usage

  • Training: use FGRestore/annotations/IR_train.json
  • Score evaluation: use FGRestore/annotations/test_single
  • Preference evaluation: use FGRestore/annotations/test_pairs

Important Note for Scene IDs 3 and 4

For samples with scene_id equal to 3 or 4, a true pristine reference image does not exist.

In these cases, ref_image corresponds to the pre-restoration image, not a distortion-free ground-truth reference.

Suggested Metrics

  • Score prediction (test_single): SRCC / PLCC
  • Preference prediction (test_pairs): Accuracy

Data Loading Notes

  • All path fields are relative paths; use FGRestore as the data root when resolving files.
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