feat: images are in sequential order if randomizeOrder is false or none

Author: Gigaszi

mapswipe_workers/mapswipe_workers/utils/process_mapillary.py

@@ -262,8 +262,7 @@ def get_image_metadata(
     ):
         raise ValueError("No Mapillary Features in the AoI match the filter criteria.")
 
-    if sampling_threshold is not None:
-        downloaded_metadata = spatial_sampling(downloaded_metadata, sampling_threshold)
+    downloaded_metadata = spatial_sampling(downloaded_metadata, sampling_threshold)
 
     if randomize_order is True:
         downloaded_metadata = downloaded_metadata.sample(frac=1).reset_index(drop=True)

mapswipe_workers/mapswipe_workers/utils/spatial_sampling.py

@@ -141,10 +141,9 @@ def spatial_sampling(df, interval_length):
     for sequence in sorted_df["sequence_id"].unique():
         sequence_df = sorted_df[sorted_df["sequence_id"] == sequence]
 
-        filtered_sorted_sub_df = filter_points(sequence_df, interval_length)
-        sampled_sequence_df = pd.concat(
-            [sampled_sequence_df, filtered_sorted_sub_df], axis=0
-        )
+        if interval_length:
+            sequence_df = filter_points(sequence_df, interval_length)
+        sampled_sequence_df = pd.concat([sampled_sequence_df, sequence_df], axis=0)
 
     # reverse order such that sequence are in direction of travel
     sampled_sequence_df = sampled_sequence_df.iloc[::-1]

mapswipe_workers/tests/unittests/test_process_mapillary.py

@@ -343,7 +343,11 @@ def test_get_image_metadata_empty_response(self, mock_coordinate_download):
     def test_get_image_metadata_size_restriction(
         self, mock_coordinate_download, mock_filter_results
     ):
-        mock_filter_results.return_value = pd.DataFrame({"ID": range(1, 100002)})
+        mock_df = pd.DataFrame({"ID": range(1, 100002)})
+        mock_df["geometry"] = self.test_polygon
+        mock_df["captured_at"] = range(1, 100002)
+        mock_df["sequence_id"] = 1
+        mock_filter_results.return_value = mock_df
         mock_coordinate_download.return_value = self.fixture_df
 
         with self.assertRaises(ValueError):