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https://github.com/abailoni/cell-cme


https://github.com/abailoni/cell-cme

Last synced: 24 days ago
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README

        

### Installation
- Clone the repository: `git clone https://github.com/abailoni/cell-CME.git`
- Move to the package directory: `cd cell-CME`
- To install the dependencies, you will need [miniconda](https://docs.conda.io/en/latest/miniconda.html) or [conda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/)
- Once you have installed conda, run the command `conda env create --name=cellCME --file=environment.yml`
- Before to run any of the scripts, activate your new environment with `conda activate cellCME`
- Install package with `python setup.py install`

### Usage
- Data should be organized as follows:

```
ROOT_DATA_DIR:
input_images:
Place here the images with .czi or .dv formats (They can also be organized in subdirectories)
converted_to_tif:
Converted tif images used by ilastik will be placed here
converted_to_jpg:
Converted jpg images will be placed here
resulting_segmentations:
Final segmentation images will be placed here
```

- To convert images to tif format (accepted by ilastik):
- Run `python scripts/convert_input_images.py --ROOT_DATA_DIR=`
- Images will be found in the `converted_to_tif` and `converted_to_jpg` subfolders
- To train ilastik classifier, see [Wiki page](https://github.com/abailoni/cell-CME/wiki/Training-ilastik-classifier)
- To plot the final segmentations:
- Run `python scripts/plot_output_segmentation.py --ROOT_DATA_DIR=`
- Images will be found in the `resulting_segmentations` subfolder
- To be continued...