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# Changelog
All notable changes to this project will be documented in this file.

The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

## [1.16.3] - 2024-12-16

170 changes: 170 additions & 0 deletions solutions/DL4MicEverywhere/cellpose-2d-zerocostdl4mic/solution.py
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###album catalog: cellcanvas

# Based on https://github.com/HenriquesLab/DL4MicEverywhere/blob/main/notebooks/ZeroCostDL4Mic_notebooks/Cellpose_2D_DL4Mic/configuration.yaml
# and https://github.com/betaseg/solutions/blob/main/solutions/io.github.betaseg/cellsketch-plot/solution.py

from album.runner.api import setup
import subprocess

try:
subprocess.check_output('nvidia-smi')
gpu_access = True
except Exception:
gpu_access = False

def install():
from album.runner.api import get_app_path
from git import Repo
import subprocess
import requests
import shutil
import os

# Clone the DL4MicEverywhere repository
clone_url = "https://github.com/HenriquesLab/DL4MicEverywhere"
repository_path = get_app_path().joinpath("DL4MicEverywhere")
Repo.clone_from(clone_url, repository_path)
assert (repository_path.exists())

# URL of the notebook you want to download
notebook_url = "https://raw.githubusercontent.com/HenriquesLab/ZeroCostDL4Mic/master/Colab_notebooks/Cellpose_2D_ZeroCostDL4Mic.ipynb"

notebook_path = get_app_path().joinpath("Cellpose_2D_ZeroCostDL4Mic.ipynb")
notebook_path.parent.mkdir(parents=True, exist_ok=True)

response = requests.get(notebook_url)
response.raise_for_status()

with open(notebook_path, 'wb') as notebook_file:
notebook_file.write(response.content)

assert notebook_path.exists(), "Notebook download failed"

# Convert the notebook to its colabless form
section_to_remove = "1.1. 1.2. 2. 6.3."
section_to_remove = section_to_remove.split(' ')

python_command = ["python", ".tools/notebook_autoconversion/transform.py", "-p", f"{get_app_path()}", "-n", "Cellpose_2D_ZeroCostDL4Mic.ipynb", "-s"]
python_command += section_to_remove

subprocess.run(python_command, cwd=repository_path)
subprocess.run(["mv", get_app_path().joinpath("colabless_Cellpose_2D_ZeroCostDL4Mic.ipynb"), get_app_path().joinpath("Cellpose_2D_ZeroCostDL4Mic.ipynb")])

# Remove the cloned DL4MicEverywhere repository
if os.name == 'nt':
os.system(f'rmdir /s /q "{to}"')
else:
# rmtree has no permission to do this on Windows
shutil.rmtree(repository_path)

def run():
from album.runner.api import get_args, get_app_path
import subprocess
import os

# Fetch arguments and paths
args = get_args()
app_path = get_app_path()

# Path to the downloaded notebook
notebook_path = app_path.joinpath("Cellpose_2D_ZeroCostDL4Mic.ipynb")

# Ensure the notebook exists
assert notebook_path.exists(), "Notebook does not exist"

# Output path for running the notebook
output_path = args.path
os.makedirs(output_path, exist_ok=True)
print(f"Saving output to {output_path}")

# Set the LD_LIBRARY_PATH to allow TensorFlow to find the CUDA libraries
global gpu_access
if gpu_access:
os.environ["LD_LIBRARY_PATH"] = f"{os.environ['LD_LIBRARY_PATH']}:{os.environ['CONDA_PREFIX']}/lib"

# Optionally, launch the Jupyter notebook to show the results
subprocess.run(["jupyter", "lab", str(notebook_path)], cwd=str(output_path))

if gpu_access:
channels = """
- conda-forge
- nvidia
- anaconda
- defaults
"""
dependencies = """
- python=3.10
- cudatoolkit=11.8.0
- cudnn=8.9.2
- pip
- pkg-config
"""
else:
channels = """
- conda-forge
- defaults
"""
dependencies = f"""
- python=3.10
- pip
- pkg-config
"""

env_file = f"""
channels:
{channels}
dependencies:
{dependencies}
- pip:
- GitPython==3.1.43
- astropy==5.3.2
- cellpose==2.2.3
- folium==0.2.1
- fpdf2==2.7.5
- google==2.0.3
- h5py==3.10.0
- imgaug==0.2.5
- ipywidgets==8.1.0
- matplotlib==3.7.1
- memory-profiler==0.61.0
- numba==0.56.4
- numpy==1.23.5
- opencv-python-headless==3.4.18.65
- opencv-python==4.8.0.76
- pandas==1.5.3
- pathlib==1.0.1
- pip==23.1.2
- scikit-image==0.19.3
- scikit-learn==1.2.2
- scipy==1.10.1
- tabulate==0.9.0
- tensorflow==2.12.0
- tifffile==2023.8.12
- tqdm==4.66.1
- wget==3.2
- nbformat==5.9.2
- jupyterlab==3.4.0
"""

setup(
group="DL4MicEverywhere",
name="cellpose-2d-zerocostdl4mic",
version="1.16.3",
solution_creators=["DL4MicEverywhere team", "album team"],
title="cellpose-2d-zerocostdl4mic implementation.",
description="Instance segmentation of 2D and 3D images. Cellpose is a generalist algorithm for cellular segmentation.",
documentation="https://raw.githubusercontent.com/HenriquesLab/ZeroCostDL4Mic/master/BioimageModelZoo/README.md",
tags=['AMD64', 'colab', 'notebook', 'Cellpose', 'Segmentation', 'ZeroCostDL4Mic', 'dl4miceverywhere'],
args=[{
"name": "path",
"type": "string",
"default": ".",
"description": "What is your working path?"
}],
cite=[{'doi': 'https://doi.org/10.1038/s41467-021-22518-0', 'text': 'von Chamier, L., Laine, R.F., Jukkala, J. et al. Democratising deep learning for microscopy with ZeroCostDL4Mic. Nat Commun 12, 2276 (2021). https://doi.org/10.1038/s41467-021-22518-0'}, {'doi': 'https://doi.org/10.1038/s41592-020-01018-x', 'text': 'Stringer, C., Wang, T., Michaelos, M. et al. Cellpose: a generalist algorithm for cellular segmentation. Nat Methods 18, 100–106 (2021). https://doi.org/10.1038/s41592-020-01018-x'}],
album_api_version="0.5.1",
covers=[],
run=run,
install=install,
dependencies={"environment_file": env_file},
)
34 changes: 34 additions & 0 deletions solutions/DL4MicEverywhere/cellpose-2d-zerocostdl4mic/solution.yml
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album_api_version: 0.5.1
args:
- default: .
description: What is your working path?
name: path
type: string
changelog: null
cite:
- doi: https://doi.org/10.1038/s41467-021-22518-0
text: von Chamier, L., Laine, R.F., Jukkala, J. et al. Democratising deep learning
for microscopy with ZeroCostDL4Mic. Nat Commun 12, 2276 (2021). https://doi.org/10.1038/s41467-021-22518-0
- doi: https://doi.org/10.1038/s41592-020-01018-x
text: "Stringer, C., Wang, T., Michaelos, M. et al. Cellpose: a generalist algorithm\
\ for cellular segmentation. Nat Methods 18, 100\u2013106 (2021). https://doi.org/10.1038/s41592-020-01018-x"
covers: []
description: Instance segmentation of 2D and 3D images. Cellpose is a generalist algorithm
for cellular segmentation.
documentation: https://raw.githubusercontent.com/HenriquesLab/ZeroCostDL4Mic/master/BioimageModelZoo/README.md
group: DL4MicEverywhere
name: cellpose-2d-zerocostdl4mic
solution_creators:
- DL4MicEverywhere team
- album team
tags:
- AMD64
- colab
- notebook
- Cellpose
- Segmentation
- ZeroCostDL4Mic
- dl4miceverywhere
timestamp: '2024-12-16T21:22:04.952484'
title: cellpose-2d-zerocostdl4mic implementation.
version: 1.16.3

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