First baby steps towards GPX handling - mainly foolish test output.

CHANGELOG.md

@@ -5,7 +5,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
 ## [Unreleased]
-
+- Added GPX parser
 
 ## [0.2] - 2020-02-05
 ### Added

Readme.md

@@ -11,9 +11,10 @@ It then creates a `UserComment` Exif tag with the actual measured radiation at t
 ## Dependencies
 Right now it depends on the following non-core Python 3 libraries:
 
-  * [py3exiv2](https://pypi.org/project/py3exiv2/) A Python 3 binding to the library exiv2.
+  * [py3exiv2](https://pypi.org/project/py3exiv2/) A Python 3 binding for (lib)exiv2.
   * [boost.python3](http://www.boost.org/libs/python/doc/index.html) Welcome to Boost.Python, a C++ library which enables seamless interoperability between C++ and the Python programming language.
   * [exiv2](http://www.exiv2.org/) Exiv2 is a Cross-platform C++ library and a command line utility to manage image metadata.
+  * [gpxpy](https://github.com/tkrajina/gpxpy) gpx-py is a python GPX parser. GPX (GPS eXchange Format) is an XML based file format for GPS tracks. 
 
 ## Requirements
   * GeigerCounter log file in csv format as it is being exported by the software GeigerLog. 

exif_rad.py

@@ -12,6 +12,7 @@ import shutil
 import csv
 import argparse
 import pyexiv2
+import gpxpy
 
 # SIFACTOR for GQ Geiger counters
 
@@ -24,17 +25,19 @@ import pyexiv2
 
 # Configure argument parser for cli options
 parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter, 
-                                 description='''A tool that writes 
-    radiation levels (and optionally geocoordinates) to image files 
-    and extracts the infos from external sources.''')
+                                 description='''A unix-tyle tool that 
+    extracts GPS and/or radiation data from GPX/CSV files and writes
+    them into the Exif tags of given photos.''')
 parser.add_argument('-si', '--sifactor', type=float, default=0.0065, 
                     help='Factor to multiply recorded CPM with.')
 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')
+                    help='Directory to output processed photos.')
 
 args = parser.parse_args()
 
@@ -72,7 +75,6 @@ for srcphoto in args.photos:
         csvreader = csv.reader(filter(lambda row: row[0] != '#', f), 
                                delimiter=',', skipinitialspace=True)
 
-        print('Processing file:', photo_basename, end='\r')
         for _, csvrawtime, csvrawcpm, _ in csvreader:
             csvtime = datetime.fromisoformat(csvrawtime)
             # Process image if its timestamp is found in CSV log (compares 2 datetime objects)
@@ -93,3 +95,23 @@ for srcphoto in args.photos:
             print('{:<15} {:<20} {:<22}'.format(photo_basename, str(pictime), 'NOT FOUND!'))
     # close CSV file
     f.close()
+
+    # Import GPX track(s)
+    if hasattr(args, 'gpx'):
+        gpx_file = open(args.gpx, 'r')
+        gpxreader = gpxpy.parse(gpx_file)
+
+        for waypoint in gpxreader.waypoints:
+            for track in gpxreader.tracks:
+                for segment in track.segments:
+                    for point in segment.points:
+                        #if pictime == point.time:
+                            print(type(point.time))
+                            print(type(pictime))
+                            print(pictime, 'vs.', point.time)
+#                        print('Point at ({0},{1}) -> {2}'.format(point.latitude, point.longitude, point.time))
+
+'''<class 'datetime.datetime'>
+    2018-08-04 17:50:16 vs. 2018-08-04 17:50:03.535000+00:00
+    <class 'datetime.datetime'>
+    2018-08-04 17:50:16 vs. 2018-08-04 17:50:23.327000+00:00'''