semvec/pypi-packages huggingface dataset:
odooghost 0.16.0
Odoo developpement made easy
License: MIT
Requires Python: <4.0,>=3.9

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# OdooGhost
*Making Odoo development a breeze.*  

OdooGhost is a powerful tool tailored for streamlining the development and deployment of Odoo instances. It offers an integrated solution that harnesses the power of Docker for orchestrating and managing these instances. With both a Command Line Interface (CLI) and an upcoming web interface, managing Odoo stacks has never been simpler.

## Features

- **Fine-grained Configuration**: Customize each Odoo instance with configuration files, tailoring settings to fit your specific needs.
- **Holistic Instance Management**: With just a few commands, you can create, update, start, stop, and even delete Odoo instances straight from the CLI.

## Installation
To kickstart your OdooGhost journey:
`pipx install odooghost`.

## Usage

### Initial Setup
Before diving deep into OdooGhost, ensure you set it up properly. Use the `setup` command and specify your working directory:
```
odooghost setup /you/working/dir
```
### Crafting a Stack
To bring your Odoo instance to life, you first need to define its blueprint - the stack configuration file. Samples to guide your creation can be found [here](https://github.com/remyz17/odooghost/tree/main/exemples).
```
odooghost stack create you-stack-config.yaml
```

## Contribute
Have ideas or enhancements for OdooGhost? We'd love to see them! Create a Pull Request to join in the journey of making Odoo development smoother for everyone.

## License
Licensed under the [MIT License](LICENSE).
ct_image_to_pic_list 0.0.5
convert a 3d CT/MRI image (numpy) into pillow image list.
License: MIT
Requires Python: >=3.10

# ct_image_to_pic_list
convert a 3d CT/MRI image (numpy) into pillow image list.

## Installation
```bash
pip install ct_image_to_pic_list
```

## Usage

reading 3d CT image.

```python
import numpy as np
from ct_image_to_pic_list import convert_ct_3darray_to_grey_image_list

# construct you 3d CT image (HU value)
arr3d = np.array([ ... ])

# get a list of PIL.Image.Image
img_list = convert_ct_3darray_to_grey_image_list(arr3d)

# save it if you want
for index, img in enumerate(img_list):
    img.save(f"{index:05d}.png")
```

reading 3d MRI image.

```python
import numpy as np
from ct_image_to_pic_list import convert_mri_3darray_to_grey_image_list

# construct you 3d MRI image (HU value)
arr3d = np.array([ ... ])

# get a list of PIL.Image.Image
img_list = convert_mri_3darray_to_grey_image_list(arr3d)

# save it if you want
for index, img in enumerate(img_list):
    img.save(f"{index:05d}.png")
```