location_finder.py

from owslib.wms import WebMapService
from owslib import crs
from pyspark import SparkContext
from image_processing import *
import csv


c = crs.Crs('EPSG:3857')
wms = WebMapService('http://www.ign.es/wms-inspire/pnoa-ma', version='1.3.0')

def parallel_processing(xy,box,picsize):
    img = wms.getmap(
        layers=['OI.OrthoimageCoverage'],
        styles=[],
        srs='EPSG:3857',
        bbox=(xy[0] - box, xy[1] - box, xy[0] + box, xy[1] + box),
        size=(picsize,picsize), #W,H px
        format='image/png',
        transparent=False
    )
    with open('Images/image{0}{1}.png'.format(xy[0],xy[1]),'wb') as out:
        out.write(img.read())
    
    green_detection(xy)
    c=contour_detection(xy)
    locations=location_convertor(c,xy,box,picsize)
    return locations

def getmap():
    sc = SparkContext()
    box = 1000 # m?
    x=241314#m?
    y=5066180 #m?
    picsize = 512
    xylist=[]
    d=[]

    xydict={}
    location_list=[]
    for i in range(-12,12):
        for j in range(-12,12):
            xylist.append([x+(i*(box-100)),y+(j*(box-100))])
    
    xylist = sc.parallelize(xylist)\
        .map(lambda x: [x,parallel_processing(x,box,picsize)])\
        .collect()
    sc.stop()
    
    # remove localization exact duplicates
    [d.append(item) for item in xylist if item not in d]

    with open('locations.csv',"w") as f:
        for element in d:
            if (element[1] != []):
                for i in range(len(element[1])):
                    csv_row=[]
                    csv_row.append(str(element[0][0])+str(element[0][1]))
                    csv_row.append(element[1][i][0])
                    csv_row.append(element[1][i][1])
                    xydict[str(element[0][0])+str(element[0][1])]=element[1]
                    writer = csv.writer(f, lineterminator='\n')
                    writer.writerow(csv_row)
    f.close()
    
    return xydict




if __name__ == "__main__":
    xydict=getmap()
    for element in xydict.items():
        print(element)