https://github.com/kamangir/mayo-clinic-strip-ai

hacking at Image Classification of Stroke Blood Clot Origin kaggle competition.
https://github.com/kamangir/mayo-clinic-strip-ai

deep-learning kaggle machine-vision medical-imaging

Last synced: 13 days ago
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hacking at Image Classification of Stroke Blood Clot Origin kaggle competition.

• Host: GitHub
• URL: https://github.com/kamangir/mayo-clinic-strip-ai
• Owner: kamangir
• Created: 2022-07-12T15:11:33.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-07-12T23:38:45.000Z (over 2 years ago)
• Last Synced: 2024-11-21T01:12:13.020Z (3 months ago)
• Topics: deep-learning, kaggle, machine-vision, medical-imaging
• Language: Jupyter Notebook
• Homepage: https://www.kaggle.com/competitions/mayo-clinic-strip-ai/overview
• Size: 2.63 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Mayo Clinic - STRIP AI (mcsai)

`mcsai` is a bash cli for the [Image Classification of Stroke Blood Clot Origin kaggle competition](https://www.kaggle.com/competitions/mayo-clinic-strip-ai/overview) based on [abcli](https://github.com/kamangir/awesome-bash-cli) - to see list of `mcsai` commands type in:

```

mcsai help

```

```

mcsai dataset download metadata/object_1

 . download object_1/metadata from mcsai dataset.

mcsai dataset list [count=10]

 . list [first 10 files in] mcsai dataset.

mcsai install

 . install mcsai.

mcsai notebook open

 . open mcsai notebook.

mcsai validate

 . validate mcsai.

```

## example 1

purpose: download a few files from the dataset and access them in [OpenSlide](https://openslide.org/api/python/) - based on [this notebook](https://www.kaggle.com/code/naotous/openslide-how-to-open-whole-slide-images?scriptVersionId=100210828).

first install and validate `mcsai`:

```

mcsai install

mcsai validate

```

you should see `openslide-1.2.0` or higher.

now review the names of the first 10 files in the dataset:

```

mcsai dataset list count=10

```

then download a few of them:

```

abcli select

mcsai dataset download metadata

mcsai dataset download other/04414e_0.tif

mcsai notebook open

```

![image](abcli/assets/example1.png)

[openslide.ipynb](openslide.ipynb) should be up and running. 🚀

/END