OpenSEP: An Open Source Subjective Experiment Platform

摘要

Subjective experiments driven by human visual perception for images aid in the development of related technologies such as analysis, compression, and transmission, which garners substantial attention and research interest. However, the general subjective experiment platform is relatively lacking, and verifying the reliability of annotation data is often difficult. In response to these challenges, an open source subjective experiment platform, namely OpenSEP, is proposed in this paper. Specifically, OpenSEP mainly includes a contrast mode sub-platform that displays dual stimuli, allowing for the simultaneous display of both source stimulus and distorted stimulus for subjective testing. Moreover, a scoring mode sub-platform that displays single stimulus is also provided in OpenSEP. In this mode, subjects can only score the distorted stimulus individually after sequentially viewing the source stimulus and all the distorted stimuli. Besides, OpenSEP constructs a cross-validation sub-platform integrated mainstream Just Noticeable Distortion (JND) algorithms. Within this sub-platform, the reliability of subjective annotation data can be verified based on existing JND algorithms, and the effectiveness of newly proposed modeling algorithms can also be validated. The open source library for OpenSEP is available at https://openi.pcl.ac.cn/OpenDatasets/OpenSEP