A lightweight provider whitelisting/blacklisting helper for Golem that filters offers via environment variables.
a package that facilitates whitelisting or blacklisting on golem from the command line
a gui to see providers on the Golem network
Generates images in bulk from image inputs.
Golem Image Sharpening is a tool that leverages the Golem Network to process and sharpen digital images. It addresses the inherent blur introduced during the image capture process—from lens optics to sensor interpolation—enhancing contrast and legibility to draw viewer attention and clarify important details. ## Key Features - **Camera Blur Correction** — Compensates for blur introduced by lens elements, sensor processing, and color channel interpolation in RAW files. - **Selective Attention Guidance** — Uses sharpening to direct viewer focus to specific areas of an image through increased contrast. - **Detail Legibility Enhancement** — Makes text, fine details (like individual leaves), and faces in crowds more distinct and easier to discern. ## Philosophy Golem Image Sharpening operates on the principle that human vision is drawn to contrast, and by restoring sharpness lost in digital capture, it can improve both aesthetic impact and functional clarity in photographs.
This project provides a dockerized workflow for compiling the VIM editor on the Golem Network, a decentralized computing platform. It enables users to leverage distributed resources to build VIM binaries, which can then be executed locally on their native machines. ## Key Features - **Decentralized Compilation** — Compiles VIM using Golem Network nodes instead of local hardware. - **Dockerized Environment** — Uses a Docker image to ensure consistent build environments across distributed nodes. - **Golem VM Integration** — Converts Docker images into Golem VM images for execution on the network. - **Python API Automation** — Utilizes yapapi (Golem's Python high-level API) to orchestrate tasks on the Golem Network. - **Local Binary Execution** — Downloads and runs the compiled VIM binary on the user's native machine after network processing. ## Philosophy The project embraces decentralized computing to offload resource-intensive compilation tasks, promoting open-source collaboration and reducing local hardware requirements.
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.