#!/usr/bin/env python # -*- coding: utf-8 -*- ''' Iterates over a bunch of .jpg or .cr2 files and matches DateTimeOriginal from Exif tags to DateTime in a csv log of a GeigerMuellerCounter and writes its value to Exif/ITPC/XMP tags in µS/h ''' import csv import argparse import pytz import gpxpy from functions import Radiation, Photo, Match, Exif, Output # SIFACTOR for GQ Geiger counters # 300 series: 0.0065 µSv/h / CPM # 320 series: 0.0065 µSv/h / CPM # 500 series: 0.0065 µSv/h / CPM # 500+ series: 0.0065 µSv/h / CPM for the first tube # 600 series: 0.0065 µSv/h / CPM # 600+ series: 0.002637 µSv/h / CPM # Configure argument parser for cli options parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter, description='''A unix-tyle tool that extracts GPS and/or radiation data from GPX/CSV files and writes them into the Exif/ITPC/XMP tags of given photos.''') parser.add_argument('-si', '--sifactor', type=float, default=0.0065, help='Factor to multiply recorded CPM with.') parser.add_argument('-tz', '--timezone', type=str, metavar='Timezone', default='utc', help='''Manually set timezone of CSV / and Photo timestamp, defaults to UTC if omitted. This is useful, if the GPS-Logger saves the time incl. timezone''') parser.add_argument('-d', '--dry', action='store_true', help='Dry-run, do not actually write anything.') parser.add_argument('csv', metavar='CSV', type=str, help='Geiger counter history file in CSV format.') parser.add_argument('-g', '--gpx', metavar='GPX', type=str, help='GPS track in GPX format') parser.add_argument('photos', metavar='Photo', type=str, nargs='+', help='One or multiple photo image files to process.') parser.add_argument('-o', '--outdir', type=str, default='.', help='Directory to output processed photos.') args = parser.parse_args() # Create timezone datetime object local_timezone = pytz.timezone(args.timezone) # Initialize two empty lists for all radiation / gps values radiation_list = [] position_list = [] # Import GeigerCounter log with open(args.csv, "r") as f: csv = csv.reader(filter(lambda row: row[0] != '#', f), delimiter=',', skipinitialspace=True) # Import only relevant values, that's timestamp and CP/M for _, csv_raw_time, csv_raw_cpm, _ in csv: radiation = Radiation(csv_raw_time, csv_raw_cpm, local_timezone, args.sifactor) radiation_list.append(radiation) # close CSV file f.close() # Import GPX track(s)print if args.gpx: gpx_file = open(args.gpx, 'r') gpx_reader = gpxpy.parse(gpx_file) for track in gpx_reader.tracks: for segment in track.segments: for point in segment.points: point_aware_time = point.time.astimezone(local_timezone) position = (point_aware_time, point.latitude, point.longitude, point.elevation) position_list.append(position) # Inform the user about what is going to happen if args.dry: print('Not modifying anything. Just print what would happen without --dry') else: if args.outdir == ".": print('Modifying photos in place (overwrite)') else: print('Modifying photos in', str(args.outdir), '(copy)') # Print table header print('{:<15} {:<25} {:<22}'.format('filename', 'date / time', 'Matched Data')) for src_photo in args.photos: # Instantiate photo, copy it to destdir if needed and receive filename to work on photo = Photo(src_photo, local_timezone, args.outdir, args.dry) # Here the matching magic takes place match = Match(photo.get_date, radiation_list, position_list) # Formatted output: data = Output(match.radiation_value, match.position_latitude, match.position_longitude, match.position_altitude) print('{:<15} {:<25} {:<22}'.format(photo.get_photo_basename, str(photo.get_date), str(data))) # Write exif data Exif(photo.get_photo_filename, args.dry, match.radiation_value, match.position_latitude, match.position_longitude, match.position_altitude)