pebbie

import numpy as np
from scipy import ndimage as ndi

# lookup tables for bwmorph_thin

G123_LUT = np.array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1,
       0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
       0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0,
       0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 0, 1, 0, 0, 0,
       1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0,

pebbie

"""
author: Peb Ruswono Aryan

Binarization Algorithm by Su et al.

@inproceedings{Su:2010:BHD:1815330.1815351,
 author = {Su, Bolan and Lu, Shijian and Tan, Chew Lim},
 title = {Binarization of Historical Document Images Using the Local Maximum and Minimum},
 booktitle = {Proceedings of the 9th IAPR International Workshop on Document Analysis Systems},
 series = {DAS '10},

pebbie

"""
author : Peb Ruswono Aryan
Automatic selection of ROI rectangle based on single point (assumed target center) selection on the image 
Automatic scale selection performed by selecting scale which maximizes laplacian of gaussian in the selected point across scales
intended use : simplifying object tracking target selection, output rectangle can be used as initial target
"""
import os
import sys
import cv2
import numpy as np

pebbie

"""
TBMR : Tree-based morse region

Xu et al, 2013, Tree-Based Morse Regions: A Topological Approach to Local Feature Detection
"""
import sys
import numpy as np 
import timeit

def compute_tree(img, isMaxTree=True):

pebbie

import sys

class Rule:
    def __init__(self, lhs, rhs):
        self.lhs = lhs
        self.rhs = rhs

    def __repr__(self):
        return "{0} ::== {1}".format(self.lhs, self.rhs)

pebbie

"""
rastore - virtual RDF data store for rasters

a graph interface from a numpy array into RDF Data Cube

- shape (dimensions)
- element datatype

- elements as rdf list?
- slices? as structured naming of bnode or a slice object?

pebbie

from rdflib.store import Store
from rdflib import Graph, RDF, URIRef, Namespace
import urllib.parse as urlparse

def add_params(origUrl, paramsDict):
    url_parts = list(urlparse.urlparse(origUrl))
    query = dict(urlparse.parse_qsl(url_parts[4]))
    query.update(dict([i for i in iter(paramsDict.items()) if i[1] is not None]))
    url_parts[4] = urlparse.urlencode(query)
    return urlparse.urlunparse(url_parts)

pebbie

import sys
from rdflib import Graph, Namespace
from rdflib.namespace import RDF, RDFS
import requests

HYDRA = Namespace("http://www.w3.org/ns/hydra/core#")

class HydraOperation:
    def __init__(self, subj, graph):
        self.type = graph.value(subj, RDF.type)

pebbie

import sys, rdflib; print rdflib.Graph().parse(sys.argv[1], format=sys.argv[2] if len(sys.argv)>2 else "json-ld").serialize(format=sys.argv[3] if len(sys.argv)>3 else "n3") if len(sys.argv)>1 else "%s <input-file> [<input-format> <output-format>]" % sys.argv[0]

pebbie

"""
call : dump_ckan.py <ckan_website>

ckan_website : e.g. http://data.ukp.go.id

author : Peb Ruswono Aryan
"""
from __future__ import print_function
import json
import os