modified paths for query phots and maps

src/build_map.py

@@ -1,4 +1,4 @@
-"""Module used for writing csv files"""
+"""Module used for automatically building satellite maps with Google Maps API"""
 import csv
 import math
 import shutil

src/extract_image_meta_exif.py

@@ -1,9 +1,9 @@
+"""Script that reads the EXIF data from the drone images and extracts the GNSS coordinates to a csv file"""
 import subprocess
 import re
 import os
 
 ############################################################################################################
-# Script that reads the EXIF data from the drone images and extracts the GNSS coordinates to a csv file
 # Requires exiftool to be installed: https://exiftool.org/
 # You might have to modify the scripts to match the EXIF metadata of your drone photos 
 # Use https://www.metadata2go.com/ to easily check the metadata of your images

src/plot_data.py

@@ -1,3 +1,4 @@
+"""Plots data output from wildnav"""
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd

src/superglue_utils.py

@@ -17,7 +17,7 @@ def match_image():
     Wrapper function for matching two images, provides an interface to superglue model
     """
     center = None
-    input = '../assets/map/'
+    input = '../assets/maps/map_1/'
     output_dir = "../results"
     image_glob = ['*.png', '*.jpg', '*.jpeg', '*.JPG']
     skip = 1

src/wildnav.py

@@ -1,15 +1,16 @@
-import cv2
+"""Core module. Contains the main functions for the project."""
 import csv
-import superglue_utils
-
+import cv2
 import haversine as hs
 from haversine import Unit
+import superglue_utils
 
 ############################################################################################################
 # Important variables
 ############################################################################################################
 
-map_filename = "../assets/map/map.csv" #  csv file with the sattelite geo tagged images
+map_path = "../assets/maps/map_1/"
+map_filename = "../assets/maps/map_1/map.csv" #  csv file with the sattelite geo tagged images
 drone_photos_filename = "../assets/query/photo_metadata.csv" # csv file with the geo tagged drone images;
                                                              # the geo coordinates are only used to compare
                                                              # the calculated coordinates with the real ones
@@ -177,7 +178,7 @@ def calculate_geo_pose(geo_photo, center, features_mean,  shape):
     for rot in rotations:
 
         # Write the query photo to the map folder
-        cv2.imwrite("../assets/map/1_query_image.png", photo)
+        cv2.imwrite(map_path + "1_query_image.png", photo)
 
         #Call superglue wrapper function to match the query image to the map
         satellite_map_index_new, center_new, located_image_new, features_mean_new, query_image_new, feature_number = superglue_utils.match_image()