fromepicbot_imagesimportmemes# for a discord bot@bot.command()asyncdefdrake(ctx, first, second):
awaitctx.reply(file=discord.File(awaitmemes.drake(first, second)))
# it's so easy to use
Effects:
fromepicbot_imagesimporteffects@bot.command()asyncdefblur(ctx, user: discord.User):
awaitctx.reply(file=discord.File(awaiteffects.blur(awaituser.avatar.read())))
# 1 line go brr
I won't be making docs for these, refer to the source code or ask in the support server if you have any questions
Fast Image Retrieval is an open source image retrieval framework release by Center of Image and Signal Processing Lab (CISiP Lab), Universiti Malaya. This framework implements most of the major binary hashing methods, together with both popular backbone networks and public datasets.
Fast Image Retrieval (FIRe) is an open source image retrieval project release by Center of Image and Signal Processing Lab (CISiP Lab), Universiti Malaya. This project implements most of the major binary hashing methods to date, together with different popular backbone networks and public datasets.
clesperanto is a graphical user interface for a multi-platform multi-language framework for GPU-accelerated image processing. It is based on napari and the pyclesperanto-prototype.
This implementation works on pixelized images that were created with a linear box filter. In this article I cover background information on pixelization and similar research.
This is a very small prject which helps in enhancing the images by taking a Input images. This project has many features like detcting the faces and enhaning the faces itself and also a feature which
Fast Image Retrieval is an open source image retrieval framework release by Center of Image and Signal Processing Lab (CISiP Lab), Universiti Malaya. This framework implements most of the major binar