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SubjectiveIQE
gongnq/SubjectiveIQE
SubjectiveIQE is a machine learning model from gongnq. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
A deep learning model for subjective image quality assessment based on the Q-SiT architecture.
Access
Public
Updated Nov 26, 2025
Repo size
16.2 GB
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At a glance
- Library
- transformers
- License
- apache-2.0
- Access
- Public
- Created
- Nov 26, 2025
- Updated
- Nov 26, 2025
- SHA
- 9fec4c53
Model card
From the Hugging Face model README
Q-SiT: Subjective Image Quality Assessment
A deep learning model for subjective image quality assessment based on the Q-SiT architecture.
Quick Start
1. Clone the repository
git clone https://huggingface.co/gongnq/SubjectiveIQE
cd SubjectiveIQE
2. Install dependencies
pip install -r requirements.txt
3. Usage
Web Interface
Run the web application for interactive image quality assessment:
python UI.py
Batch Testing
Test multiple images at once:
python test_images.py
Model
The model files are included in this repository and will be automatically downloaded when you clone from Hugging Face.
Dataset
Download Full Datasets
- Koniq/SPAQ/Q-Instruct: https://huggingface.co/datasets/q-future/Q-Instruct-DB/blob/main/q-instruct-images.tar
- LLaVA-150K: https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K
Requirements
- Python 3.8+
- PyTorch
- Transformers
- Other dependencies listed in
requirements.txt
- Library
- transformers
- License
- apache-2.0
- Languages
- en
- Created
- Nov 26, 2025
- Updated
- Nov 26, 2025