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quantitative-big-imaging-2025

https://github.com/imaginglectures/quantitative-big-imaging-2025

Science Score: 26.0%

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    Scientific vocabulary similarity
    Low similarity (5.3%) to scientific vocabulary
Last synced: 9 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: ImagingLectures
  • License: apache-2.0
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 220 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 2
  • Open Issues: 0
  • Releases: 0
Created over 1 year ago · Last pushed 12 months ago
Metadata Files
Readme License Citation Zenodo

README.md

Quantitative Big Imaging Course 2025

The course web page is here.

Install the pixi environment manager

Windows

Get the installer for the latest release at https://github.com/prefix-dev/pixi/releases/ and run it. This is the better way than the powershell script recommended on the pixi.ch home page.

MacOS

Install the pixi enviroment curl -fsSL https://pixi.sh/install.sh | sh

Install the lecture environment

Install the dependencies pixi install pixi run jupyter-contrib-nbextension install --user

Install Tensorflow

Tensorflow requires GPU support. This differs between MacOS (uses Metal) and Windows/Linux (Uses Cuda).

For MacOS

pixi run pip install tensorflow-macos tensorflow-metal tensorflow-datasets ```

Run a jupyter notebook

To run jupyter notebook you need to start a terminal and type pixi run jupyter-notebook

Owner

  • Name: ImagingLectures
  • Login: ImagingLectures
  • Kind: organization

GitHub Events

Total
  • Watch event: 2
  • Delete event: 18
  • Member event: 2
  • Push event: 70
  • Fork event: 4
Last Year
  • Watch event: 2
  • Delete event: 18
  • Member event: 2
  • Push event: 70
  • Fork event: 4

Dependencies

Exercises/01-Images/pyproject.toml pypi
  • ipykernel >=6.29.5
  • ipython >=8.32.0
  • matplotlib >=3.10.0
  • numpy >=2.2.2
  • pytest >=8.3.4
  • scikit-image >=0.25.1
  • scipy >=1.15.1
Exercises/01-Images/uv.lock pypi
  • appnope 0.1.4
  • asttokens 3.0.0
  • cffi 1.17.1
  • colorama 0.4.6
  • comm 0.2.2
  • contourpy 1.3.1
  • cycler 0.12.1
  • debugpy 1.8.12
  • decorator 5.1.1
  • executing 2.2.0
  • fonttools 4.56.0
  • imageio 2.37.0
  • iniconfig 2.0.0
  • ipykernel 6.29.5
  • ipython 8.32.0
  • jedi 0.19.2
  • jupyter-client 8.6.3
  • jupyter-core 5.7.2
  • kiwisolver 1.4.8
  • lazy-loader 0.4
  • matplotlib 3.10.0
  • matplotlib-inline 0.1.7
  • nest-asyncio 1.6.0
  • networkx 3.4.2
  • numpy 2.2.2
  • packaging 24.2
  • parso 0.8.4
  • pexpect 4.9.0
  • pillow 11.1.0
  • platformdirs 4.3.6
  • pluggy 1.5.0
  • prompt-toolkit 3.0.50
  • psutil 6.1.1
  • ptyprocess 0.7.0
  • pure-eval 0.2.3
  • pycparser 2.22
  • pygments 2.19.1
  • pyparsing 3.2.1
  • pytest 8.3.4
  • python-dateutil 2.9.0.post0
  • pywin32 308
  • pyzmq 26.2.1
  • quantitative-big-imaging-2025-remake 0.1.0
  • scikit-image 0.25.1
  • scipy 1.15.1
  • six 1.17.0
  • stack-data 0.6.3
  • tifffile 2025.1.10
  • tornado 6.4.2
  • traitlets 5.14.3
  • typing-extensions 4.12.2
  • wcwidth 0.2.13
Exercises/02-Augmentation/pyproject.toml pypi
  • albumentations >=2.0.4
  • ipykernel >=6.29.5
  • ipython >=8.32.0
  • matplotlib >=3.10.0
  • numpy >=2.2.2
  • pandas >=2.2.3
  • pytest >=8.3.4
  • scikit-image >=0.25.1
  • scikit-learn >=1.6.1
  • scipy >=1.15.1
  • seaborn >=0.13.2
Exercises/02-Augmentation/uv.lock pypi
  • albucore 0.0.23
  • albumentations 2.0.4
  • annotated-types 0.7.0
  • appnope 0.1.4
  • asttokens 3.0.0
  • cffi 1.17.1
  • colorama 0.4.6
  • comm 0.2.2
  • contourpy 1.3.1
  • cycler 0.12.1
  • debugpy 1.8.12
  • decorator 5.1.1
  • executing 2.2.0
  • fonttools 4.56.0
  • imageio 2.37.0
  • iniconfig 2.0.0
  • ipykernel 6.29.5
  • ipython 8.32.0
  • jedi 0.19.2
  • joblib 1.4.2
  • jupyter-client 8.6.3
  • jupyter-core 5.7.2
  • kiwisolver 1.4.8
  • lazy-loader 0.4
  • matplotlib 3.10.0
  • matplotlib-inline 0.1.7
  • nest-asyncio 1.6.0
  • networkx 3.4.2
  • numpy 2.2.2
  • opencv-python-headless 4.11.0.86
  • packaging 24.2
  • pandas 2.2.3
  • parso 0.8.4
  • pexpect 4.9.0
  • pillow 11.1.0
  • platformdirs 4.3.6
  • pluggy 1.5.0
  • prompt-toolkit 3.0.50
  • psutil 6.1.1
  • ptyprocess 0.7.0
  • pure-eval 0.2.3
  • pycparser 2.22
  • pydantic 2.10.6
  • pydantic-core 2.27.2
  • pygments 2.19.1
  • pyparsing 3.2.1
  • pytest 8.3.4
  • python-dateutil 2.9.0.post0
  • pytz 2025.1
  • pywin32 308
  • pyyaml 6.0.2
  • pyzmq 26.2.1
  • quantitative-big-imaging-2025-remake 0.1.0
  • scikit-image 0.25.1
  • scikit-learn 1.6.1
  • scipy 1.15.1
  • seaborn 0.13.2
  • simsimd 6.2.1
  • six 1.17.0
  • stack-data 0.6.3
  • stringzilla 3.12.1
  • threadpoolctl 3.5.0
  • tifffile 2025.1.10
  • tornado 6.4.2
  • traitlets 5.14.3
  • typing-extensions 4.12.2
  • tzdata 2025.1
  • wcwidth 0.2.13
Exercises/03-ImageEnhancement/pyproject.toml pypi
  • albumentations >=2.0.4
  • ipykernel >=6.29.5
  • ipython >=8.32.0
  • ipywidgets >=8.1.5
  • matplotlib >=3.10.0
  • numpy >=2.2.2
  • pandas >=2.2.3
  • pytest >=8.3.4
  • scikit-image >=0.25.1
  • scikit-learn >=1.6.1
  • scipy >=1.15.1
  • seaborn >=0.13.2
  • tqdm >=4.67.1
Exercises/03-ImageEnhancement/uv.lock pypi
  • albucore 0.0.23
  • albumentations 2.0.4
  • annotated-types 0.7.0
  • appnope 0.1.4
  • asttokens 3.0.0
  • cffi 1.17.1
  • colorama 0.4.6
  • comm 0.2.2
  • contourpy 1.3.1
  • cycler 0.12.1
  • debugpy 1.8.12
  • decorator 5.1.1
  • executing 2.2.0
  • fonttools 4.56.0
  • imageio 2.37.0
  • iniconfig 2.0.0
  • ipykernel 6.29.5
  • ipython 8.32.0
  • ipywidgets 8.1.5
  • jedi 0.19.2
  • joblib 1.4.2
  • jupyter-client 8.6.3
  • jupyter-core 5.7.2
  • jupyterlab-widgets 3.0.13
  • kiwisolver 1.4.8
  • lazy-loader 0.4
  • matplotlib 3.10.0
  • matplotlib-inline 0.1.7
  • nest-asyncio 1.6.0
  • networkx 3.4.2
  • numpy 2.2.2
  • opencv-python-headless 4.11.0.86
  • packaging 24.2
  • pandas 2.2.3
  • parso 0.8.4
  • pexpect 4.9.0
  • pillow 11.1.0
  • platformdirs 4.3.6
  • pluggy 1.5.0
  • prompt-toolkit 3.0.50
  • psutil 6.1.1
  • ptyprocess 0.7.0
  • pure-eval 0.2.3
  • pycparser 2.22
  • pydantic 2.10.6
  • pydantic-core 2.27.2
  • pygments 2.19.1
  • pyparsing 3.2.1
  • pytest 8.3.4
  • python-dateutil 2.9.0.post0
  • pytz 2025.1
  • pywin32 308
  • pyyaml 6.0.2
  • pyzmq 26.2.1
  • quantitative-big-imaging-2025-remake 0.1.0
  • scikit-image 0.25.1
  • scikit-learn 1.6.1
  • scipy 1.15.1
  • seaborn 0.13.2
  • simsimd 6.2.1
  • six 1.17.0
  • stack-data 0.6.3
  • stringzilla 3.12.1
  • threadpoolctl 3.5.0
  • tifffile 2025.1.10
  • tornado 6.4.2
  • tqdm 4.67.1
  • traitlets 5.14.3
  • typing-extensions 4.12.2
  • tzdata 2025.1
  • wcwidth 0.2.13
  • widgetsnbextension 4.0.13
Exercises/04-Segmentation/pyproject.toml pypi
  • albumentations >=2.0.4
  • ipykernel >=6.29.5
  • ipython >=8.32.0
  • ipython-genutils >=0.2.0
  • ipyvolume >=0.6.3
  • ipywidgets >=8.1.5
  • matplotlib >=3.10.0
  • notebook >=7.3.2
  • numpy >=2.2.2
  • pandas >=2.2.3
  • pytest >=8.3.4
  • pywavelets >=1.8.0
  • scikit-image >=0.25.1
  • scikit-learn >=1.6.1
  • scipy >=1.15.1
  • seaborn >=0.13.2
  • tqdm >=4.67.1
Exercises/04-Segmentation/uv.lock pypi
  • 143 dependencies
Exercises/05-AdvancedSegmentation/pyproject.toml pypi
  • albumentations >=2.0.4
  • ipykernel >=6.29.5
  • ipython >=8.32.0
  • ipython-genutils >=0.2.0
  • ipyvolume >=0.6.3
  • ipywidgets >=8.1.5
  • lightning >=2.5.1
  • matplotlib >=3.10.0
  • notebook >=7.3.2
  • numpy >=2.2.2
  • pandas >=2.2.3
  • pytest >=8.3.4
  • pywavelets >=1.8.0
  • scikit-image >=0.25.1
  • scikit-learn >=1.6.1
  • scipy >=1.15.1
  • seaborn >=0.13.2
  • segmentation-models-pytorch *
  • tqdm >=4.67.1
Exercises/06-Shapes/pyproject.toml pypi
  • albumentations >=2.0.4
  • ipykernel >=6.29.5
  • ipython >=8.32.0
  • ipyvolume >=0.6.3
  • matplotlib >=3.10.0
  • numpy >=2.2.2
  • pandas >=2.2.3
  • pytest >=8.3.4
  • scikit-image >=0.25.1
  • scikit-learn >=1.6.1
  • scipy >=1.15.1
  • seaborn >=0.13.2
Exercises/07-ComplexObjects/pyproject.toml pypi
  • ipykernel >=6.29.5
  • ipython >=8.32.0
  • ipyvolume >=0.6.3
  • matplotlib >=3.10.0
  • numpy >=2.2.2
  • pandas >=2.2.3
  • pytest >=8.3.4
  • scikit-image >=0.25.1
  • scikit-learn >=1.6.1
  • scipy >=1.15.1
  • seaborn >=0.13.2
Exercises/08-Statistics/pyproject.toml pypi
  • plotnine >=0.14.5
Exercises/09-DynamicExperiments/pyproject.toml pypi