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Visual Learning Lab utility files and pipelines

Project description

vllpy

This is a package with common utility functions, files and pipelines for the Visual Learning Lab. Creating a conda environment is recommended but optional. This package uses python=3.12.

conda create -n vislearnlabpy python=3.12
conda activate vislearnlabpy

Then, activate the environment and simply install vislearnlabpy via running the following pip command in your terminal. You will also have to install PyTorch and CLIP manually.

pip install git+https://github.com/openai/CLIP.git
pip install --upgrade vislearnlabpy

To install PyTorch on the Tversky server, run:

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

Here is as an example of how to generate npy embedding files from a list of images whose relative paths are defined in a CSV file

python embedding_generator.py --input_csv examples/input/inputs.csv --output_path examples/output --output_type npy --input_dir [working_directory] --overwrite

If the full paths are defined in the CSV file, you can similarly use

python embedding_generator.py --input_csv [input_path] --output_path [output_path] --output_type npy

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