Showing 4 open source projects for "command line dynamic"

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    gowitness

    gowitness

    Golang, web screenshot utility using Chrome Headless

    A golang, web screenshot utility using Chrome Headless. gowitness is a website screenshot utility written in Golang, that uses Chrome Headless to generate screenshots of web interfaces using the command line, with a handy report viewer to process results. Both Linux and macOS is supported, with Windows support mostly working. Inspiration for gowitness comes from Eyewitness. If you are looking for something with lots of extra features, be sure to check it out along with these other projects. For installation information and other documentation, please refer to the wiki. ...
    Downloads: 1 This Week
    Last Update:
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  • 2
    ascii-image-converter

    ascii-image-converter

    A cross-platform command-line tool to convert images into ascii art

    ascii-image-converter is a command-line tool that converts images into ASCII art and prints them out onto the console. Available on Windows, Linux, and macOS.
    Downloads: 3 This Week
    Last Update:
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  • 3
    Pixelizer

    Pixelizer

    An efficient image pixelizer written in go

    Pixelizer is a command-line tool written in Go that transforms images into pixelated versions. Designed for simplicity and efficiency, it allows users to apply pixelation effects with customizable parameters directly from the terminal. Pixelizer supports various output options, including animated GIFs and ANSI-rendered previews, making it a versatile tool for developers and artists working with pixel art.
    Downloads: 0 This Week
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  • 4
    Primitive Pictures

    Primitive Pictures

    Reproducing images with geometric primitives

    Primitive Pictures is an image processing command-line tool written in Go that reproduces images using geometric primitives (triangles, rectangles, ellipses, polygons, etc.). The core algorithm is iterative and “hill-climbing”: given a target image, it repeatedly finds the best single shape to add that will reduce the error between the current approximation and the target image, then draws that shape.
    Downloads: 0 This Week
    Last Update:
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