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[python]
python_binary = ".venv/bin/python"

[custom.uv-version]
description = "The currently installed version of uv"
shell = "bash"
detect_files = [
  ".python-version",
  "Pipfile",
  "__init__.py",

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[python]
python_binary = ".venv/bin/python"

[custom.uv-version]
description = "The currently installed version of uv"
shell = "bash"
detect_files = [
  ".python-version",
  "Pipfile",
  "__init__.py",

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# /// script
# requires-python = ">=3.12"
# dependencies = [
#     "einops",
#     "loguru",
#     "numpy",
#     "pillow",
#     "procex",
#     "torch",
#     "transformers",

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#!/bin/bash

PYTHON_VERSION="3.13"

tmp_dir=$(mktemp -d)

uv init \
    --bare \
    --quiet \
    --python $PYTHON_VERSION \

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"""
Convert the input of day 12 of Advent of Code 2022 to an STL file.

To install requirements, run:
pip install scikit-image numpy-stl

Usage:
python input_to_mesh.py input.txt output.stl

Example content of input.txt:

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import torch
import torchio as tio
from einops import rearrange

rows = 16
cols = 28

dataset = tio.datasets.OrganMNIST3D('train')
batch_size = rows * cols
loader = torch.utils.data.DataLoader(dataset, batch_size=batch_size, shuffle=True)

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import torch
import torchio as tio

image4d = tio.Resample()(tio.datasets.FPG().dmri)
collater = torch.utils.data.DataLoader([image4d])
batch = next(iter(collater))
tensor = batch[tio.DATA].float()
dropped = torch.nn.Dropout3d()(tensor)
for i, channel in enumerate(dropped[0]):

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