https://pypi.org/project/pyskylumos/ Recent updates to the Python Package Index for pyskylumos en https://pypi.org/project/pyskylumos/0.0.6/ A Python package for simulating skylight polarization sensor recordings using advanced polarization models (including Pan, Berry, and Rayleigh). Designed for researchers and engineers, this tool enables the generation of synthetic datasets for biomimetic navigation, machine learning, computer vision, and atmospheric optics. Ideal for developing and testing bio-inspired sensors, building training data for AI models, and exploring applications in robotics, remote sensing, and environmental monitoring. sgtcioch@liverpool.ac.uk, sgdjohnc@liverpool.ac.uk, isandall@liverpool.ac.uk, jfralph@liverpool.ac.uk Mon, 02 Feb 2026 16:00:10 GMT https://pypi.org/project/pyskylumos/0.0.5/ A Python package for simulating skylight polarization sensor recordings using advanced polarization models (including Pan, Berry, and Rayleigh). Designed for researchers and engineers, this tool enables the generation of synthetic datasets for biomimetic navigation, machine learning, computer vision, and atmospheric optics. Ideal for developing and testing bio-inspired sensors, building training data for AI models, and exploring applications in robotics, remote sensing, and environmental monitoring. sgtcioch@liverpool.ac.uk, sgdjohnc@liverpool.ac.uk, isandall@liverpool.ac.uk, jfralph@liverpool.ac.uk Tue, 15 Jul 2025 16:59:45 GMT https://pypi.org/project/pyskylumos/0.0.4/ A Python package for simulating skylight polarization sensor recordings using advanced polarization models (including Pan, Berry, and Rayleigh). Designed for researchers and engineers, this tool enables the generation of synthetic datasets for biomimetic navigation, machine learning, computer vision, and atmospheric optics. Ideal for developing and testing bio-inspired sensors, building training data for AI models, and exploring applications in robotics, remote sensing, and environmental monitoring. sgtcioch@liverpool.ac.uk, sgdjohnc@liverpool.ac.uk, isandall@liverpool.ac.uk, jfralph@liverpool.ac.uk Mon, 07 Jul 2025 16:59:39 GMT https://pypi.org/project/pyskylumos/0.0.3/ A Python package for simulating skylight polarization sensor recordings using advanced polarization models (including Pan, Berry, and Rayleigh). Designed for researchers and engineers, this tool enables the generation of synthetic datasets for biomimetic navigation, machine learning, computer vision, and atmospheric optics. Ideal for developing and testing bio-inspired sensors, building training data for AI models, and exploring applications in robotics, remote sensing, and environmental monitoring. sgtcioch@liverpool.ac.uk, sgdjohnc@liverpool.ac.uk, isandall@liverpool.ac.uk, jfralph@liverpool.ac.uk Mon, 07 Jul 2025 16:26:36 GMT https://pypi.org/project/pyskylumos/0.0.2/ A Python package for simulating skylight polarization sensor recordings using advanced polarization models (including Pan, Berry, and Rayleigh). Designed for researchers and engineers, this tool enables the generation of synthetic datasets for biomimetic navigation, machine learning, computer vision, and atmospheric optics. Ideal for developing and testing bio-inspired sensors, building training data for AI models, and exploring applications in robotics, remote sensing, and environmental monitoring. sgtcioch@liverpool.ac.uk, sgdjohnc@liverpool.ac.uk, isandall@liverpool.ac.uk, jfralph@liverpool.ac.uk Mon, 07 Jul 2025 16:02:45 GMT https://pypi.org/project/pyskylumos/0.0.1/ A Python package for simulating skylight polarization sensor recordings using advanced polarization models (including Pan, Berry, and Rayleigh). Designed for researchers and engineers, this tool enables the generation of synthetic datasets for biomimetic navigation, machine learning, computer vision, and atmospheric optics. Ideal for developing and testing bio-inspired sensors, building training data for AI models, and exploring applications in robotics, remote sensing, and environmental monitoring. sgtcioch@liverpool.ac.uk, sgdjohnc@liverpool.ac.uk, isandall@liverpool.ac.uk, jfralph@liverpool.ac.uk Mon, 07 Jul 2025 15:30:39 GMT