Add `--face-confidence-threshold`

wyzely_detect/__main__.py

@@ -83,7 +83,7 @@ def main():
             # May be better to check every iteration, but this also works
             if path_to_faces_exists:
                 if face_details := utils.recognize_face(
-                    path_to_directory=path_to_faces, run_frame=run_frame
+                    path_to_directory=path_to_faces, run_frame=run_frame, min_confidence=args.face_confidence_threshold
                 ):
                     plot_boxes.append(face_details)
                     objects_and_peoples = notify.thing_detected(
@@ -132,7 +132,7 @@ def main():
                 # print("---")
 
                 # Now do stuff (if conf > 0.5)
-                if conf < args.confidence_threshold or (
+                if conf < args.object_confidence_threshold or (
                     class_id not in args.detect_object and args.detect_object != []
                 ):
                     # If the confidence is too low

wyzely_detect/utils/cli_args.py

@@ -20,8 +20,10 @@ def set_argparse():
         epilog=":)",
     )
 
-    # required='RUN_SCALE' not in os.environ,
 
+    # One important thing to consider is that most function parameters are optional and have a default value
+    # However, with argparse, those are never used since a argparse always passes something, even if it's None
+    
     argparser.add_argument(
         "--run-scale",
         # Set it to the env RUN_SCALE if it isn't blank, otherwise set it to 0.25
@@ -53,7 +55,7 @@ def set_argparse():
     )
 
     argparser.add_argument(
-        "--confidence-threshold",
+        "--object-confidence-threshold",
         default=os.environ["CONFIDENCE_THRESHOLD"]
         if "CONFIDENCE_THRESHOLD" in os.environ
         and os.environ["CONFIDENCE_THRESHOLD"] != ""
@@ -61,7 +63,15 @@ def set_argparse():
         type=float,
         help="The confidence threshold to use",
     )
-
+    argparser.add_argument(
+        "--face-confidence-threshold",
+        default=os.environ["FACE_CONFIDENCE_THRESHOLD"]
+        if "FACE_CONFIDENCE_THRESHOLD" in os.environ
+        and os.environ["FACE_CONFIDENCE_THRESHOLD"] != ""
+        else 0.3,
+        type=float,
+        help="The confidence (currently cosine similarity) threshold to use for face recognition",
+    )
     argparser.add_argument(
         "--faces-directory",
         default=os.environ["FACES_DIRECTORY"]

wyzely_detect/utils/utils.py

@@ -68,6 +68,7 @@ def recognize_face(
     path_to_directory: Path = Path("faces"),
     # opencv image
     run_frame: np.ndarray = None,
+    min_confidence: float = 0.3,
 ) -> np.ndarray:
     """
     Accepts a path to a directory of images of faces to be used as a refference
@@ -149,15 +150,13 @@ def recognize_face(
             "y2": df.iloc[-1]["source_y"] + df.iloc[-1]["source_h"],
         }
         # After some brief testing, it seems positive matches are > 0.3
-        distance = df.iloc[-1]["ArcFace_cosine"]
+        cosine_similarity = df.iloc[-1]["ArcFace_cosine"]
-        # TODO: Make this a CLI argument
+        if cosine_similarity < min_confidence:
-        if distance < 0.3:
             return None
-        # if 0.5 < distance < 0.7:
         # label = "Unknown"
         to_return = dict(label=label, **coordinates)
         print(
-            f"Confindence: {distance}, filname: {path_to_image.name}, to_return: {to_return}"
+            f"Cosine similarity: {cosine_similarity}, filname: {path_to_image.name}, to_return: {to_return}"
         )
         return to_return