.vscode/launch.json

@@ -22,16 +22,6 @@
             "module": "wyzely_detect",
             // "justMyCode": true
             "justMyCode": false
-        },
+        }
-        {
-            "name": "Debug --help",
-            "type": "python",
-            "request": "launch",
-            "module": "wyzely_detect",
-            "args": [
-                "--help"
-            ],
-            "justMyCode": false
-        },
     ]
 }

wyzely_detect/__main__.py

@@ -1,6 +1,6 @@
 # import face_recognition
 from pathlib import Path
-import os
+
 import cv2
 
 # import hjson as json
@@ -30,22 +30,12 @@ def main():
     # https://github.com/ultralytics/ultralytics/issues/3084#issuecomment-1732433168
     # Currently, I have been unable to set up Poetry to use GPU for Torch
     for i in range(torch.cuda.device_count()):
-        print(f'Using {torch.cuda.get_device_properties(i).name} for pytorch')
+        print(torch.cuda.get_device_properties(i).name)
     if torch.cuda.is_available():
         torch.cuda.set_device(0)
         print("Set CUDA device")
     else:
         print("No CUDA device available, using CPU")
-    # Seems automatically, deepface (tensorflow) tried to use my GPU on Pop!_OS (I did not set up cudnn or anything)
-    # Not sure the best way, in Poetry, to manage GPU libraries so for now, just use CPU
-    if args.force_disable_tensorflow_gpu:
-        print("Forcing tensorflow to use CPU")
-        import tensorflow as tf
-        tf.config.set_visible_devices([], 'GPU')
-        if tf.config.experimental.list_logical_devices('GPU'):
-            print('GPU disabled unsuccessfully')
-        else:
-            print("GPU disabled successfully")
 
     model = YOLO("yolov8n.pt")
 
@@ -70,6 +60,7 @@ def main():
     while True:
         # Grab a single frame of video
         ret, frame = video_capture.read()
+        # Only process every other frame of video to save time
         # Resize frame of video to a smaller size for faster recognition processing
         run_frame = cv2.resize(frame, (0, 0), fx=args.run_scale, fy=args.run_scale)
         # view_frame = cv2.resize(frame, (0, 0), fx=args.view_scale, fy=args.view_scale)

wyzely_detect/utils/cli_args.py

@@ -72,15 +72,7 @@ def set_argparse():
         action="store_true",
         help="Don't display the video feed",
     )
-    video_options.add_argument(
+
-        '-c',
-        '--force-disable-tensorflow-gpu',
-        default=os.environ["FORCE_DISABLE_TENSORFLOW_GPU"]
-        if "FORCE_DISABLE_TENSORFLOW_GPU" in os.environ and os.environ["FORCE_DISABLE_TENSORFLOW_GPU"] != ""
-        else False,
-        action="store_true",
-        help="Force disable tensorflow GPU through env since sometimes it's not worth it to install cudnn and whatnot",
-    )
 
     notifcation_services = argparser.add_argument_group("Notification Services")
     notifcation_services.add_argument(

wyzely_detect/utils/utils.py

@@ -124,21 +124,13 @@ def recognize_face(
             model_name="ArcFace",
             detector_backend="opencv",
         )
-    
+    except ValueError as e:
-    except (ValueError) as e:
         if (
             str(e)
             == "Face could not be detected. Please confirm that the picture is a face photo or consider to set enforce_detection param to False."  # noqa: E501
         ):
             # print("No faces recognized") # For debugging
             return None
-        elif (
-            # Check if the error message contains "Validate .jpg or .png files exist in this path."
-            "Validate .jpg or .png files exist in this path." in str(e)
-        ):
-            # If a verbose/silent flag is added, this should be changed to print only if verbose is true
-            # print("No faces found in database")
-            return None 
         else:
             raise e
     # Iteate over the dataframes