Use embeddings to intelligently sift through a maze of unlabeled imagery.
WIP Coming soon ⏳
Use the following steps to install imagescry
from its github repository.
-
Install
uv
if you haven't already:curl -LsSf https://astral.sh/uv/install.sh | sh
-
Create a virtual environment:
uv venv <my_env_name>
-
Activate your virtual environment:
source <my_env_name>/bin/activate
uv pip install git+https://github.com/libertininick/imagescry.git
Verify the installation by running:
uv pip show imagescry
This repository uses a Makefile for managing useful commands used for development.
Available commands:
Available commands
=============================================================================================================
- check : Runs all checks:
- formatting
- docstring checks
- tests and coverage reports
- type checking
- dependency vulnerability checks
- docstring-check : Run docstring checks
- format : Lint and format code with ruff
- init : Initialize workspace for development:
- install & update uv
- sync workspace environment
- install pre-commit hooks
- install-uv : Download and install uv
- sync : Sync workspace environment and prune uv cache
- test : Run all tests using workspace Python version
- test-cov : Run all tests and generate coverage report using workspace Python version
- test-all-python-versions : Run all tests over supported Python versions
- type-check : Run type checking with mypy
- update : Update uv, all dependencies, and pre-commit hooks in workspace
- vulnerability-check : Run dependency vulnerability checks
-
Clone the repository:
git clone git@github.com:libertininick/imagescry.git cd imagescry
-
Install
make
if you haven't alreadysudo apt update && sudo apt install make
-
Initialize the workspace environment
make init
-
Restart your terminal and run all workspace checks:
make check