ocrd-fork-pylsd


Nameocrd-fork-pylsd JSON
Version 0.0.8 PyPI version JSON
download
home_pagehttps://github.com/OCR-D/pylsd
Summarypylsd is the python bindings for LSD - Line Segment Detector
upload_time2023-06-23 16:15:08
maintainerkba
docs_urlNone
authorGefu Tang
requires_python
licenseAGPL
keywords lsd line segmentation
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            pylsd
=============

[![Build Wheels](https://github.com/kba/pylsd/actions/workflows/wheels.yml/badge.svg?branch=pypi-fork)](https://github.com/kba/pylsd/actions/workflows/wheels.yml)
[![PyPI Release](https://img.shields.io/pypi/v/ocrd-fork-pylsd.svg)](https://pypi.org/project/ocrd-fork-pylsd/)

### 1. Introduction

pylsd is the python bindings for [LSD - Line Segment Detector](http://www.ipol.im/pub/art/2012/gjmr-lsd/).

### 2. Install

This package uses distutils, which is the default way of installing python modules. To install in your home directory, securely run the following:
```
git clone https://github.com/primetang/pylsd.git
cd pylsd
python setup.py install
```

Or directly through `pip` to install it:
```
pip install pylsd
```

### 3. Usage

We can use the package by using `from pylsd.lsd import lsd`, and `lines = lsd(src)` is the call format for the `lsd` function, where `src` is a Grayscale Image (`H * W` numpy.array), and the return value `lines` is the Detected Line Segment, `lines` is an `N * 5` numpy.array, each row represents a straight line, the 5-dimensional vector is:

`[point1.x, point1.y, point2.x, point2.y, width]`


According to these presentations, we can use it just like the following code ([here is the link](https://github.com/primetang/pylsd/tree/master/example)):

* by using cv2 module

```python
import cv2
import numpy as np
import os
from pylsd.lsd import lsd
fullName = 'car.jpg'
folder, imgName = os.path.split(fullName)
src = cv2.imread(fullName, cv2.IMREAD_COLOR)
gray = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY)
lines = lsd(gray)
for i in xrange(lines.shape[0]):
    pt1 = (int(lines[i, 0]), int(lines[i, 1]))
    pt2 = (int(lines[i, 2]), int(lines[i, 3]))
    width = lines[i, 4]
    cv2.line(src, pt1, pt2, (0, 0, 255), int(np.ceil(width / 2)))
cv2.imwrite(os.path.join(folder, 'cv2_' + imgName.split('.')[0] + '.jpg'), src)
```

* by using PIL(Image) module

```python
from PIL import Image, ImageDraw
import numpy as np
import os
from pylsd.lsd import lsd
fullName = 'house.png'
folder, imgName = os.path.split(fullName)
img = Image.open(fullName)
gray = np.asarray(img.convert('L'))
lines = lsd(gray)
draw = ImageDraw.Draw(img)
for i in xrange(lines.shape[0]):
    pt1 = (int(lines[i, 0]), int(lines[i, 1]))
    pt2 = (int(lines[i, 2]), int(lines[i, 3]))
    width = lines[i, 4]
    draw.line((pt1, pt2), fill=(0, 0, 255), width=int(np.ceil(width / 2)))
img.save(os.path.join(folder, 'PIL_' + imgName.split('.')[0] + '.jpg'))
```

The following is the result:

* car.jpg by using cv2 module

![](https://github.com/primetang/pylsd/blob/master/example/car.jpg)

![](https://github.com/primetang/pylsd/blob/master/example/cv2_car.jpg)

* house.png by using PIL(Image) module

![](https://github.com/primetang/pylsd/blob/master/example/house.png)

![](https://github.com/primetang/pylsd/blob/master/example/PIL_house.jpg)

            

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