Ignore multispectral band groups that are missing images

opendm/osfm.py

@@ -64,7 +64,6 @@ def reconstruct(self, rolling_shutter_correct=False, merge_partial=False, rerun=
                             "Check that the images have enough overlap, "
                             "that there are enough recognizable features "
                             "and that the images are in focus. "
-                            "You could also try to increase the --min-num-features parameter."
                             "The program will now exit.")
 
         if rolling_shutter_correct:

opendm/types.py

@@ -13,6 +13,7 @@
 from opendm import io
 from opendm import system
 from opendm import context
+from opendm import multispectral
 
 from opendm.progress import progressbc
 from opendm.photo import ODM_Photo
@@ -45,19 +46,51 @@ def detect_multi_camera(self):
             band_photos[p.band_name].append(p)
 
         bands_count = len(band_photos)
-        if bands_count >= 2 and bands_count <= 8:
+
+        # Band name with the minimum number of photos
+        max_band_name = None
+        max_photos = -1
+        for band_name in band_photos:
+            if len(band_photos[band_name]) > max_photos:
+                max_band_name = band_name
+                max_photos = len(band_photos[band_name])
+
+        if bands_count >= 2 and bands_count <= 10:
             # Validate that all bands have the same number of images,
             # otherwise this is not a multi-camera setup
-            img_per_band = len(band_photos[p.band_name])
-            for band in band_photos:
-                if len(band_photos[band]) != img_per_band:
-                    log.ODM_ERROR("Multi-camera setup detected, but band \"%s\" (identified from \"%s\") has only %s images (instead of %s), perhaps images are missing or are corrupted. Please include all necessary files to process all bands and try again." % (band, band_photos[band][0].filename, len(band_photos[band]), img_per_band))
-                    raise RuntimeError("Invalid multi-camera images")
+            img_per_band = len(band_photos[max_band_name])
 
             mc = []
             for band_name in band_indexes:
                 mc.append({'name': band_name, 'photos': band_photos[band_name]})
 
+            filter_missing = False
+            for band in band_photos:
+                if len(band_photos[band]) < img_per_band:
+                    log.ODM_WARNING("Multi-camera setup detected, but band \"%s\" (identified from \"%s\") has only %s images (instead of %s), perhaps images are missing or are corrupted." % (band, band_photos[band][0].filename, len(band_photos[band]), len(band_photos[max_band_name])))
+                    filter_missing = True
+
+            if filter_missing:
+                # Calculate files to ignore
+                _, p2s = multispectral.compute_band_maps(mc, max_band_name)
+
+                max_files_per_band = 0
+
+                for filename in p2s:
+                    max_files_per_band = max(max_files_per_band, len(p2s[filename]))
+
+                for filename in p2s:
+                    if len(p2s[filename]) < max_files_per_band:
+                        photos_to_remove = p2s[filename] + [p for p in self.photos if p.filename == filename]
+                        for photo in photos_to_remove:
+                            log.ODM_WARNING("Excluding %s" % photo.filename)
+
+                            self.photos = [p for p in self.photos if p != photo]
+                            for i in range(len(mc)):
+                                mc[i]['photos'] = [p for p in mc[i]['photos'] if p != photo]
+
+                log.ODM_INFO("New image count: %s" % len(self.photos))
+
             # We enforce a normalized band order for all bands that we can identify
             # and rely on the manufacturer's band_indexes as a fallback for all others
             normalized_band_order = {
@@ -94,7 +127,7 @@ def detect_multi_camera(self):
 
             for c, d in enumerate(mc):
                 log.ODM_INFO(f"Band {c + 1}: {d['name']}")
-
+            
             return mc
 
         return None