Real-ESRGAN ncnn Vulkan is an optimized, cross-platform implementation of Real-ESRGAN using the ncnn neural network inference engine and Vulkan for hardware acceleration. Unlike the standard PyTorch-based Real-ESRGAN code, this variant is written in C/C++ and designed to run efficiently on many platforms (including Windows, Linux, and possibly Android) without requiring heavy frameworks like CUDA or Python. It provides command-line tools for upscaling images with selected models, allowing users to specify input/output paths, scaling factors, tile sizes, and model names from a compressed model set, which is particularly helpful for larger images or automated workflows. The Vulkan backend enables fast execution on GPUs from different vendors (Intel/AMD/Nvidia) with broad support, making it suitable for non-Python environments, production systems, or performance-constrained setups.
Features
- High-performance, Vulkan-accelerated implementation of Real-ESRGAN
- Uses ncnn inference engine — no Python or TensorFlow/PyTorch support needed
- Cross-platform C/C++ tool executable for common OSes
- Command-line control of scaling, model selection, and tiling options
- Supports anime and general image models
- Ideal for integration into apps, services, or pipelines requiring fast runtime