About
IQA-Server offers a suite of tools for evaluating image quality using models from the `pyiqa` library. It provides metrics such as Mean Opinion Score (MOS), sharpness, brightness, colorfulness, and contrast, along with in-depth analysis of bitrate, compression algorithms, spatial information, entropy, dynamic range, blurriness, blockiness, color balance, saturation, noise level, exposure level, vibrance, and color variance. This comprehensive assessment allows users to gain a detailed understanding of image characteristics and quality without needing reference images.
Key Features
- Calculates Mean Opinion Score (MOS) using `pyiqa` models.
- Measures sharpness using edge detection or gradient-based methods.
- Provides image dimensions, brightness, and colorfulness metrics.
- Analyzes compression artifacts like blockiness and blurriness.
- Evaluates color balance, saturation, and noise levels.
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Use Cases
- Automated image quality control in content creation workflows.
- Image optimization for storage or transmission based on quality metrics.
- Quality assurance for image datasets used in machine learning models.
