search your image collections with natural language
Project description
memery
Search over large image datasets with natural language and computer vision!
Install
The necessary CLIP and torch packages will be installed by pip. You might want to make sure you have a sane CUDA environment before and after this step if you're trying to use GPU. If you don't have a GPU, memery
should still work on your CPU.
If you have any trouble please open an issue on Github! I want to make this package useful for as many people as possible. Help me know what's going wrong :)
pip install memery
How to use
Use GUI
The browser GUI is a Voilá app, which basically runs a Jupyter notebook without showing any of the code cells. To use this way, navigate to your memery
folder in a terminal and run:
voila serve app.ipynb
If you're in a Jupyter environment, you can summon the GUI directly into an output cell like this:
from memery.gui import appPage
app = appPage()
display(app)
<memery.gui.appPage at 0x7f6c0e7c80d0>
Use CLI
From the command line, you can use memery
on any folder and it will search for images recursively, returning a list object to stdout.
Pass the --n flag to control how many images are returned (default 10).
memery PATH/TO/IMAGE/FOLDER 'query' --n 20
Use as a library
Simply use queryFlow
to search over a folder recursively! The folder will be indexed, if an index doesn't already exist. Then any new images will be CLIP-encoded, an Annoy treemap built, and a list of ranked filenames returned.
from memery.core import queryFlow
from memery.gui import get_grid
ranked = queryFlow('./images', 'dad joke')
print(ranked[:5])
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