diff --git a/BUGs b/BUGs
index 7e80a47..37e3e8d 100644
--- a/BUGs
+++ b/BUGs
@@ -27,3 +27,8 @@ BUG-89: refimg face_locn also got transformed -- some sequence of adding/removin
 BUG-90: I added photo of mich as kid (ice-cream in paris) and then somehow it matches that photo to Cam's face, not the same img -- is this a bug in my code, or some weird quirk of face_recognition library???
 	- either lib. is weird; OR
 	- I should get a lower score for mich in that image, and somehow my order/face matching is not doing the right thing
+
+BUG-91: uploading reference images from a phone, does soemthing to the format (they are uploaded as some sort of TIFF inside jpeg?: 
+	"JPEG image data, Exif standard: [TIFF image data, little-endian, direntries=12, height=3024, manufacturer=samsung, model=SM-G980F, orientation=upper-right, xresolution=210, yresolution=218, resolutionunit=2, software=G980FXXUEFVDB, datetime=2022:07:03 14:04:43, width=4032], baseline, precision 8, 4032x3024, components 3"
+
+	and then face_recognition.load_image cant find a face in it -- but, if I uplaod via a browser, its a more normal jpeg that I can find a face in... ODD)
diff --git a/person.py b/person.py
index d22b5c2..acc4eb8 100644
--- a/person.py
+++ b/person.py
@@ -101,10 +101,13 @@ def AddRefimgToPerson( filename, person ):
         settings = Settings.query.first()
         model=AIModel.query.get(settings.default_refimg_model)
         refimg.face, face_locn = GenFace( filename, model=model.name )
+        os.remove(filename)
+        if not face_locn:
+            raise Exception("Could not find face in uploaded reference image" )
+            return
         refimg.face_locn = json.dumps(face_locn)
         refimg.model_used = settings.default_refimg_model
         refimg.created_on = time.time()
-        os.remove(filename)
         person.refimg.append(refimg)
         db.session.add(person)
         db.session.add(refimg)
diff --git a/shared.py b/shared.py
index 4baafcf..aa67238 100644
--- a/shared.py
+++ b/shared.py
@@ -141,7 +141,7 @@ def GenFace(fname, model):
     img = face_recognition.load_image_file(fname)
     location = face_recognition.face_locations(img, model=model)
     encodings = face_recognition.face_encodings(img, known_face_locations=location)
-    if len(encodings):
+    if len(encodings) and len(location):
         return encodings[0].tobytes(), location[0]
     else:
         return None, None