Python vs. QShield vs. jsObf vs. scikit-image Comparison Chart

Obfuscate your highly valuable source code and protect your sensitive assets thanks to QShield compiler-obfuscator. Protect your applications against static and dynamic analysis. Software running on untrusted environments is at risk of reverse-engineering, an application running on a device that is available to an attacker is vulnerable to a wide range of techniques used to try and extract secrets, and intellectual property. To prevent unauthorized parties from gaining insight, tampering with or even recovering the source code from the binary, software protection mechanisms must be implemented to preserve revenues and intellectual property. 30+ obfuscation schemes are available. Granular control of the protection profile thanks to a file-based policy or comments throughout the code. Build diversification, each compiled application is different with a user-controlled randomness seed. Integrity checks and detection of debuggers, emulators, and hooking frameworks.

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.