Skip to main content

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. This package uses python>=3.11.

It is recommended you create a conda environment to start using this package but this step is optional. To do so, run the commands below:

conda create -n vislearnlabpy python=3.12
conda activate vislearnlabpy

Then, activate the environment and simply install vislearnlabpy and CLIP by running the commands below in your terminal.

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

You may also have to install PyTorch manually, ensuring that you have the right version but the right version may also be installed by default with CLIP. To install the right version of 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 a CSV file with embeddings from a list of images in a directory. You can also use this to generate npy files and doc files by changing the output type in the command below, and generate the embeddings from a CSV file instead by using input_file instead of input_dir

python embedding_generator.py --input_dir examples/input --output_path examples/output --output_type csv --overwrite

For more detailed examples, please look at the demo in the Jupyter notebooks within the examples folder.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

vislearnlabpy-0.0.3.0.tar.gz (31.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

vislearnlabpy-0.0.3.0-py3-none-any.whl (35.9 kB view details)

Uploaded Python 3

File details

Details for the file vislearnlabpy-0.0.3.0.tar.gz.

File metadata

  • Download URL: vislearnlabpy-0.0.3.0.tar.gz
  • Upload date:
  • Size: 31.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.11.14

File hashes

Hashes for vislearnlabpy-0.0.3.0.tar.gz
Algorithm Hash digest
SHA256 5814b67655bece3b12f7640f5e8f1cbd2e482ecab664095acce426586607f97d
MD5 e6969a1b0cfe3817d60c7cd7f06f1276
BLAKE2b-256 903c5532af770cc2b1253077e4a07a2737ec21c319b5c9b769bc7c221001e8b2

See more details on using hashes here.

File details

Details for the file vislearnlabpy-0.0.3.0-py3-none-any.whl.

File metadata

File hashes

Hashes for vislearnlabpy-0.0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 5144b2861515c001af5f84e3bfb6106352a651ac455d8d44d8a9004e402de442
MD5 a1a1551d254d0af15566b6fcd587ed4a
BLAKE2b-256 0f499081a45dc1a377608263aacb24d33b1a10299c7d668fe660f274539326b7

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page