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Dataset assetOpen Source CommunityVisual AestheticsImage Evaluation

EVA

The EVA dataset is an explainable visual aesthetics dataset comprising five CSV files and resized images from the AVA dataset, intended for experimental demonstration. It is used to evaluate visual aesthetics and includes detailed information on image classification, user ratings, and attribute assessments.

Source
github
Created
Aug 15, 2020
Updated
Apr 16, 2024
Signals
132 views
Availability
Linked source ready
Overview

Dataset description and usage context

Dataset Overview

Dataset Components

  • File Types: Includes 5 CSV files and 7 archive files.
  • Images: Resized images from the AVA dataset stored in 7 archives named EVA_together.zip.00X, total size approximately 600‑700 MB.
  • CSV Files:
    • image_content_category.csv: Contains image IDs and content categories; each image belongs to a single category.
    • users.csv: Records user information, including ID, age, region, photography skill level, gender, and visual acuity.
    • votes.csv: Records user votes and difficulty assessments for images, as well as visual, composition, quality, and semantic attributes.
    • votes_filtered.csv: Contains filtered user votes and attribute assessments.
    • region_index.csv: Provides a list of regions and their codes.

Dataset Usage

  • Citation: When using this dataset, cite the paper "EVA: An Explainable Visual Aesthetics Dataset".
  • Image Extraction: After merging the 7 archive files, extract the images.
  • Image Classification: Can use provided classifications or define custom ones.

User Information

  • User CSV: Includes user ID, age, region, photography skill level, gender, and visual acuity.
  • Trusted Users: Lists 13 trusted user IDs.

Voting Information

  • Votes CSV: Records image ID, user ID, rating, difficulty, and image attributes.
  • Filtered Votes: Provides filtered ratings and attribute data.

Region Information

  • Region CSV: Supplies region codes and names.
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