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generate_readme.py
executable file
·158 lines (122 loc) · 4.71 KB
/
generate_readme.py
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#!/usr/bin/env python
import datetime
import glob
import math
import os.path as osp
import subprocess
import sys
import cv2
import tabulate
import jsk_recognition_utils
here = osp.dirname(osp.realpath(__file__))
PACKAGES = [
'jsk_recognition_msgs',
'jsk_perception',
'jsk_pcl_ros',
'jsk_pcl_ros_utils',
'resized_image_transport',
'jsk_recognition_utils',
'checkerboard_detector',
'imagesift',
]
def get_gallery():
content = []
for pkg in PACKAGES:
# TODO(wkentaro): Scrape pacakge.xml only once by creating a class.
from bs4 import BeautifulSoup
with open(osp.join(pkg, 'package.xml')) as f:
soup = BeautifulSoup(f.read(), 'lxml')
website_url = soup.find('url', type='website')
imgs = []
for ext in ['*.png', '*.jpg']:
pattern = osp.join(here, 'doc', pkg, 'nodes/images', ext)
for fname in glob.glob(pattern):
img = cv2.imread(fname)
scale = math.sqrt(1. * 200 * 200 / img.shape[0] / img.shape[1])
img = cv2.resize(img, None, None, fx=scale, fy=scale)
imgs.append(img)
if len(imgs) >= 15:
break
if not imgs:
continue
cols = 5
rows = max(len(imgs) // cols, 1)
tiled = jsk_recognition_utils.get_tile_image(
imgs, tile_shape=(cols, rows), margin_color=[255, 255, 255])
fname = osp.join(here, '.readme/gallery_%s.jpg' % pkg)
cv2.imwrite(fname, tiled)
content.append('### [%s](%s)' % (pkg, website_url.text))
content.append('')
content.append('[](%s)' % (osp.relpath(fname, here),
website_url.text))
content.append('')
return '\n'.join(content)
def get_package_table():
headers = ['Package', 'Description', 'Documentation', 'Code']
rows = []
for pkg in PACKAGES:
# TODO(wkentaro): Scrape pacakge.xml only once by creating a class.
from bs4 import BeautifulSoup
with open(osp.join(pkg, 'package.xml')) as f:
soup = BeautifulSoup(f.read(), 'lxml')
website_url = soup.find('url', type='website')
if website_url:
doc_url = '[](%s)' % website_url.text
else:
doc_url = ''
repo_url = soup.find('url', type='repository')
if repo_url:
code_url = '[](%s)' % \
osp.join(repo_url.text, 'tree/master', pkg)
else:
code_url = ''
desc = filter(None, soup.find('description').text.splitlines())[0].strip()
desc = desc[:50]
if not desc.endswith('.'):
desc += '...'
row = [pkg, desc, doc_url, code_url]
rows.append(row)
return tabulate.tabulate(rows, headers=headers, tablefmt='pipe')
def get_deb_status_table():
cmd = 'rosrun jsk_tools generate_deb_status_table.py jsk_recognition'
return subprocess.check_output(cmd, shell=True).strip()
template = '''\
<!--
DO NOT EDIT THIS FILE BY HAND.
This file is automatically generated by {SCRIPT} at {TIMESTAMP}.
-->
jsk\_recognition
===============
[](https://badge.fury.io/gh/jsk-ros-pkg%2Fjsk_recognition)
[](https://travis-ci.org/jsk-ros-pkg/jsk_recognition)
[](https://jsk-docs.readthedocs.io/projects/jsk_recognition/en/latest/)
jsk_recognition is a stack for the perception packages which are used in JSK lab.
ROS packages
------------
{PACKAGES_TABLE}
Gallery
-------
{GALLERY}
Deb build status
----------------
{DEB_STATUS_TABLE}
Deprecated packages
-------------------
* [cr\_calibration](https://github.com/jsk-ros-pkg/jsk_recognition/tree/master/cr_calibration)
* [cr\_capture](https://github.com/jsk-ros-pkg/jsk_recognition/tree/master/cr_capture)
* [orbit\_pantilt](https://github.com/jsk-ros-pkg/jsk_recognition/tree/master/orbit_pantilt)
* [posedetectiondb](https://github.com/jsk-ros-pkg/jsk_recognition/tree/master/posedetectiondb)
* [jsk\_libfreenect2](https://github.com/jsk-ros-pkg/jsk_recognition/tree/master/jsk_libfreenect2)
'''
def main():
sys.stdout.write(
template.format(
SCRIPT=osp.realpath(__file__),
TIMESTAMP=datetime.datetime.now().isoformat(),
DEB_STATUS_TABLE=get_deb_status_table(),
GALLERY=get_gallery(),
PACKAGES_TABLE=get_package_table(),
)
)
if __name__ == '__main__':
main()