{"library":"pyiqa","type":"library","category":null,"description":"pyiqa is a comprehensive PyTorch-based toolbox for Image Quality Assessment (IQA), offering reimplementations of numerous mainstream full-reference (FR) and no-reference (NR) metrics. It aims for GPU acceleration, often outperforming MATLAB counterparts, and provides calibrated results against official scripts where available. The library is actively maintained with frequent releases, adding new metrics, features, and bug fixes.","language":"python","status":"active","version":"0.1.15.post2","tags":["image-quality-assessment","pytorch","deep-learning","computer-vision","full-reference","no-reference","iqa"],"install":[{"cmd":"pip install pyiqa","imports":["from pyiqa import create_metric","from pyiqa import list_models","from pyiqa import imread2tensor"]},{"cmd":"pip install uv\nuv pip install pyiqa","imports":[]},{"cmd":"pip install git+https://github.com/chaofengc/IQA-PyTorch.git","imports":[]}],"homepage":null,"github":"https://github.com/chaofengc/IQA-PyTorch","docs":null,"changelog":null,"pypi":"https://pypi.org/project/pyiqa/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":10,"avg_install_s":110.5,"avg_import_s":null,"wheel_type":"sdist"},"url":"https://checklist.day/v1/registry/pyiqa/compatibility"},"provenance":{"verified_status":"passing","verified_at":"Sun Jun 28","last_verified":"Sun Jun 28","next_check":"Tue Jul 28","install_tag":null}}