Metadata-Version: 2.1
Name: optical_profilometry_feature_detection
Version: 0.1.1
Summary: A suite of feature detection tools for optical profilometry data
Home-page: https://engineering.case.edu/centers/sdle/
Author: Kai Zheng, Priyan Rajamohan, Addison Klinke, Bereket Tadesse, Mirra Rasmussen, Mahamad Salah Mahmoud, Laura Bruckman
Author-email: zheng@case.edu, priyan@case.edu, agk38@case.edu, bereket.tadesse@case.edu, mirra.rasmussen@case.edu, mohamed.mahmoud2@case.edu, laura.bruckman@case.edu
License: BSD License (BSD-3)
Project-URL: Documentation, https://cwrusdle.bitbucket.io/sphinx/docs/build/html/index.html
Platform: UNKNOWN
Description-Content-Type: text/markdown

# Optical Profilometry Feature Detection
A suite of feature detection tools for optical profilometry data


# Features
 -   Crack Detection and Aalysis
 
#  Setup
1. Installation
```bash
$ pip install optical_profilometry_feature_detection
```
2.	Import it in python
```python
from optical_profilometry_feature_detection import *
``` 
#  A quick example
```python
# separate the individual lines from the raw sample2
lines = g_separate_lines("", "sample2.txt")

# analyze line 1 of sample2, excluding first 2% and last 2% of data, using a span of 0.02 
# in the loewss surface profile model
g_model_cracking("", lines[0], "sample2.txt", 1, first_surf= 0.02, last_surf= 0.98, span = 0.02)

# analyze the first 5 lines in sample1
batch_cracking("", "", "sample1.txt", 5)
``` 
***Output will be series of png and csv files***


