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-0.0.2.7.tar.gz (30.8 kB view details)

Uploaded Source

Built Distribution

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

vislearnlabpy-0.0.2.7-py3-none-any.whl (35.8 kB view details)

Uploaded Python 3

File details

Details for the file vislearnlabpy-0.0.2.7.tar.gz.

File metadata

  • Download URL: vislearnlabpy-0.0.2.7.tar.gz
  • Upload date:
  • Size: 30.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.11

File hashes

Hashes for vislearnlabpy-0.0.2.7.tar.gz
Algorithm Hash digest
SHA256 651ae1160b0732256a869bb548eac864ba54a8adc7063c1e0049730acfe637ea
MD5 1e7b791e2da458e58f01ab061dddd99e
BLAKE2b-256 621c40f225023b14596d3f140add12307a86ce10c747fce21f7a8e77253c093f

See more details on using hashes here.

File details

Details for the file vislearnlabpy-0.0.2.7-py3-none-any.whl.

File metadata

File hashes

Hashes for vislearnlabpy-0.0.2.7-py3-none-any.whl
Algorithm Hash digest
SHA256 ce2b49995e221bfbe3596572cea950f2ce33c1757b2c9bbcf41c30bda3e5617b
MD5 5df7e1e9e41bad1aada7801d92e89b03
BLAKE2b-256 384b3ae4aceeab1dff2845ddb5e4af6039bf34bb54a133dc12e7e162ef0fe8df

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