REPID: Rendering Evaluation of Photographic Image Dataset REPID (officially introduced as the Rendering Evaluation of Photographic Image Dataset) is a large-scale benchmark designed for Image Rendering Quality Assessment (IRQA). Unlike traditional Image Quality Assessment (IQA) which focuses on technical degradations like noise or blur, REPID aims to model subjective human aesthetic preferences for different rendering styles of the same scene. Dataset Overview… See the full description on the dataset page: https://huggingface.co/datasets/vsevolodpl/REPID.
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Pull with QuantumShield
quantumshield pull vsevolodpl/REPID Verify integrity
quantumshield verify vsevolodpl/REPID pip install
pip install quantumshield && quantumshield pull vsevolodpl/REPID Unverified Model
This model has not been PQC-verified. File integrity cannot be guaranteed against quantum threats.
README.md
REPID
REPID: Rendering Evaluation of Photographic Image Dataset REPID (officially introduced as the Rendering Evaluation of Photographic Image Dataset) is a large-scale benchmark designed for Image Rendering Quality Assessment (IRQA). Unlike traditional Image Quality Assessment (IQA) which focuses on technical degradations like noise or blur, REPID aims to model subjective human aesthetic preferences for different rendering styles of the same scene. Dataset Overview… See the full description on the dataset page: https://huggingface.co/datasets/vsevolodpl/REPID.
Intended Uses
This model is registered on the QuantaMrkt quantum-safe registry. This model has not yet been PQC-verified.
Quick Start
# Install the CLI pip install quantumshield # Pull the model quantumshield pull vsevolodpl/REPID # Verify file integrity quantumshield verify vsevolodpl/REPID
About
REPID: Rendering Evaluation of Photographic Image Dataset REPID (officially introduced as the Rendering Evaluation of Photographic Image Dataset) is a large-scale benchmark designed for Image Rendering Quality Assessment (IRQA). Unlike traditional Image Quality Assessment (IQA) which focuses on technical degradations like noise or blur, REPID aims to model subjective human aesthetic preferences for different rendering styles of the same scene. Dataset Overview… See the full description on the dataset page: https://huggingface.co/datasets/vsevolodpl/REPID.
Get this model
Pull with QuantumShield
quantumshield pull vsevolodpl/REPID Verify signatures
quantumshield verify vsevolodpl/REPID