Python vs. gini vs. imageio vs. scikit-image Comparison Chart

Replace hard-coded spreadsheets with automated data feeds from your portfolio companies. Use anti-fraud algorithms to identify red flags. Instantly use public and private comps for DCF analysis. Build up-to-date cash flow forecasts in minutes. Get a standardized financial report every month. Automatically update data in your spreadsheets. Identify issues and ask the right questions early. If you’re an investor and you don’t have a financial fraud in your portfolio, it’s probably because you haven’t found it yet. Automate your data collection process to get accurate, real-time data on your portfolio companies. Granular real-time financial data on all your current, and future investments. Forget hard-coded Excel spreadsheets and reminder emails to your portfolio companies. Streamline your data collection process with live data sent directly into your own models and spreadsheets, updated every day.

scikit-image is a collection of algorithms for image processing. It is available free of charge and free of restriction. We pride ourselves on high-quality, peer-reviewed code, written by an active community of volunteers. scikit-image provides a versatile set of image processing routines in Python. This library is developed by its community, and contributions are most welcome! scikit-image aims to be the reference library for scientific image analysis in Python. We accomplish this by being easy to use and install. We are careful in taking on new dependencies, and sometimes cull existing ones, or make them optional. All functions in our API have thorough docstrings clarifying expected inputs and outputs. Conceptually identical arguments have the same name and position in a function signature. Test coverage is close to 100% and code is reviewed by at least two core developers before being included in the library.