semvec/pypi-packages huggingface dataset:
image-processing-testing 0.0.1
Passo a passo passado por Karina Kato.
Requires Python: >=3.8

# image-processing

Description. 
The package package_name is used to:
	Processing:
		- Histogram matching
		- Structural similarity
		- Resize image

	Utils:
		- Read image
		- Save image
		- Plot image
		- Plot result
		- Plot histogram

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install package_name

```bash
pip install package_name
```

## Author
Gabriel Monteiro

## License
[MIT](https://choosealicense.com/licenses/mit/)
idendrogram 0.2.0
Interactive dendrograms compatible with scipy, scikit-learn and hdbscan
Requires Python: >=3.8
Keywords: dendrogram,hierarchical clustering,clustering

# idendrogram

idendrogram helps you create nicer, interactive visualizations of hierarchical clustering trees (a.k.a. dendrograms) from clustering outputs generated by your preferred hierarchical clustering library (SciPy, Scikit-learn or HDBSCAN) in your preferred python visualization library (Altair, Plotly or Matplotlib)

It also supports bi-directional Streamlit integration via a custom D3-powered component.

<img src='docs/gallery/custom-radii.png' width=500>
<img src='docs/gallery/streamlit-integration.gif' width=500>

## Installation

To use the main package:

```pip install idendrogram```

To use the bi-directional Streamlit component:

```pip install idendrogram idendrogram-streamlit-component``` 

## Basic usage 

```python
import idendrogram
import scipy.cluster.hierarchy as sch
from idendrogram.targets.altair import to_altair

#cluster the data
linkage_matrix = sch.linkage(
    data['data'], method='single', metric='euclidean'
)
threshold = 0.8
flat_clusters = sch.fcluster(
    linkage_matrix, t=threshold, criterion='distance'
)

#wrap clustering outputs / parameters into a container
cl_data = idendrogram.ClusteringData(
    linkage_matrix = linkage_matrix, 
    cluster_assignments = flat_clusters
)

#pass to idendrogram and visualize
idd = idendrogram.idendrogram()
idd.set_cluster_info(cl_data)
dendrogram = idd.create_dendrogram(truncate_mode='level', p=10)
to_altair(dendrogram=dendrogram, height=200, width=629)
```

For more, see docs at https://kamicollo.github.io/idendrogram/