Metadata-Version: 2.4
Name: superccm
Version: 0.2.0
Summary: An Open-Source Python Toolkit for Automated Quantification of Corneal Nerve Fibers in Confocal Microscopy Images
Home-page: https://https://github.com/SummerColdWind
Author: Qincheng Qiao
Author-email: jugking6688@gmail.com
Classifier: Development Status :: 1 - Planning
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: aiccm
Requires-Dist: gradio==5.35.0
Requires-Dist: matplotlib==3.7.0
Requires-Dist: numpy<2.0.0
Requires-Dist: scikit-learn==1.7.0
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

---
title: SuperCCM Web Application
emoji: 🚀
colorFrom: indigo
colorTo: blue
sdk: gradio
sdk_version: "5.35.0"
app_file: app.py
pinned: false
---

<div align="center">
  <img src="docs/assets/superccm.png" alt="description" />

<hr>

English | [简体中文](./README_cn.md)
</div>

## 🚀 Introduction

✨️SuperCCM is an open-source Python framework for processing and analyzing corneal nerve images from corneal confocal microscopy (CCM).
By inputting a CCM corneal nerve image, SuperCCM can automatically process the image and output various commonly used morphological parameters in clinical practice.

## 🌟 Using online

> https://huggingface.co/spaces/jugking6688/SuperCCM

## ❇️ Environmental Preparation

```shell
conda create -n superccm python=3.10 -y
conda activate superccm
pip install -r requirements.txt
```

## ⚡ Quickly Start

```python
from superccm import SuperCCM  # Import the superccm object from the SuperCCM package
import cv2

image = cv2.imread('path/to/your/image.png')  # Read the test image
# Of course, you can also obtain a picture object in any way you like
# Make sure the image is an np.ndarray object of shape (384, 384, 3) and type uint8
ccm = SuperCCM()  # Instantiate the SuperCCM object
metrics = ccm(image)  # Process and analyze the image, and return a dictionary storing various morphological parameters
print(metrics)  # Print parameters
```

## 📖 Document Tutorial

We offer a wealth of documentation and tutorials for users to delve deeply into SuperCCM.
Click the link below to quickly jump to the corresponding section of the document.

 - ✨️ [Auto Analysis](docs/doc_auto_analysis.md)
 - ✨️ [Visualization](docs/doc_vis.md)
 - ✨️ [Bulk Analysis](docs/doc_bulk_analysis.md)
 - ✨️ [Web Application](docs/doc_web.md)


## 📄 License

This project follows the [GPL v3](LICENSE) open source license.

## 🎓 Academic Citation

> coming soon ...
