From bec1d5b9790e3ae9827540a125153832cf23ea7a Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Fri, 22 Dec 2023 15:22:01 -0600
Subject: [PATCH 01/18] Moved processing to `utils/utils.py`

Crashes when another face is introduced
---
 wyzely_detect/__main__.py       | 138 +++++----------------------
 wyzely_detect/utils/cli_args.py |   1 +
 wyzely_detect/utils/utils.py    | 159 +++++++++++++++++++++++++++++++-
 3 files changed, 181 insertions(+), 117 deletions(-)

diff --git a/wyzely_detect/__main__.py b/wyzely_detect/__main__.py
index 7f6f1bd..d17be86 100644
--- a/wyzely_detect/__main__.py
+++ b/wyzely_detect/__main__.py
@@ -7,17 +7,12 @@ import cv2
 import torch
 from ultralytics import YOLO
 
-from .utils import notify, utils
+from .utils import utils
 from .utils.cli_args import argparser
 
 DATETIME_FORMAT = "%Y-%m-%d %H:%M:%S"
 args = None
 
-objects_and_peoples = {
-    "objects": {},
-    "peoples": {},
-}
-
 
 def main():
     global objects_and_peoples
@@ -70,121 +65,32 @@ def main():
     while True:
         # Grab a single frame of video
         ret, frame = video_capture.read()
-        # 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)
 
-        results = model(run_frame, verbose=False)
+        frame_to_show = utils.process_footage(
+            frame = frame,
+            run_scale = args.run_scale,
+            view_scale = args.view_scale,
 
-        path_to_faces = Path(args.faces_directory)
-        path_to_faces_exists = path_to_faces.is_dir()
+            faces_directory=Path(args.faces_directory),
+            face_confidence_threshold=args.face_confidence_threshold,
+            no_remove_representations=args.no_remove_representations,
 
-        for i, r in enumerate(results):
-            # list of dicts with each dict containing a label, x1, y1, x2, y2
-            plot_boxes = []
+            detection_window=args.detection_window,
+            detection_duration=args.detection_duration,
+            notification_window=args.notification_window,
 
-            # The following is stuff for people
-            # This is still in the for loop as each result, no matter if anything is detected, will be present.
-            # Thus, there will always be one result (r)
+            ntfy_url=args.ntfy_url,
 
-            # Only run if path_to_faces exists
-            # 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,
-                    min_confidence=args.face_confidence_threshold,
-                    no_remove_representations=args.no_remove_representations,
-                ):
-                    plot_boxes.append(face_details)
-                    objects_and_peoples = notify.thing_detected(
-                        thing_name=face_details["label"],
-                        objects_and_peoples=objects_and_peoples,
-                        detection_type="peoples",
-                        detection_window=args.detection_window,
-                        detection_duration=args.detection_duration,
-                        notification_window=args.notification_window,
-                        ntfy_url=args.ntfy_url,
-                    )
-
-            # The following is stuff for objects
-            # Setup dictionary of object names
-            if (
-                objects_and_peoples["objects"] == {}
-                or objects_and_peoples["objects"] is None
-            ):
-                for name in r.names.values():
-                    objects_and_peoples["objects"][name] = {
-                        "last_detection_time": None,
-                        "detection_duration": None,
-                        # "first_detection_time": None,
-                        "last_notification_time": None,
-                    }
-                # Also, make sure that the objects to detect are in the list of objects_and_peoples
-                # If it isn't, print a warning
-                for obj in args.detect_object:
-                    if obj not in objects_and_peoples:
-                        print(
-                            f"Warning: {obj} is not in the list of objects the model can detect!"
-                        )
-
-            for box in r.boxes:
-                # Get the name of the object
-                class_id = r.names[box.cls[0].item()]
-                # Get the coordinates of the object
-                cords = box.xyxy[0].tolist()
-                cords = [round(x) for x in cords]
-                # Get the confidence
-                conf = round(box.conf[0].item(), 2)
-                # Print it out, adding a spacer between each object
-                # print("Object type:", class_id)
-                # print("Coordinates:", cords)
-                # print("Probability:", conf)
-                # print("---")
-
-                # Now do stuff (if conf > 0.5)
-                if conf < args.object_confidence_threshold or (
-                    class_id not in args.detect_object and args.detect_object != []
-                ):
-                    # If the confidence is too low
-                    # or if the object is not in the list of objects to detect and the list of objects to detect is not empty
-                    # then skip this iteration
-                    continue
-
-                # Add the object to the list of objects to plot
-                plot_boxes.append(
-                    {
-                        "label": class_id,
-                        "x1": cords[0],
-                        "y1": cords[1],
-                        "x2": cords[2],
-                        "y2": cords[3],
-                    }
-                )
-
-                objects_and_peoples = notify.thing_detected(
-                    thing_name=class_id,
-                    objects_and_peoples=objects_and_peoples,
-                    detection_type="objects",
-                    detection_window=args.detection_window,
-                    detection_duration=args.detection_duration,
-                    notification_window=args.notification_window,
-                    ntfy_url=args.ntfy_url,
-                )
-
-            # To debug plotting, use r.plot() to cross reference the bounding boxes drawn by the plot_label() and r.plot()
-            frame_to_show = utils.plot_label(
-                boxes=plot_boxes,
-                full_frame=frame,
-                # full_frame=r.plot(),
-                run_scale=args.run_scale,
-                view_scale=args.view_scale,
-            )
-
-            # Display the resulting frame
-            # cv2.imshow("", r)
-            if not args.no_display:
-                cv2.imshow(f"Video{i}", frame_to_show)
+            model=model,
+            detect_object=args.detect_object,
+            object_confidence_threshold=args.object_confidence_threshold,
+        )
+        # Display the resulting frame
+        # TODO: When multi-camera support is added, this needs to be changed to allow all feeds
+        if not args.no_display:
+            # When a face isn't recognized: "cv2.error: OpenCV(4.8.1) D:\a\opencv-python\opencv-python\opencv\modules\highgui\src\window.cpp:971: error: (-215:Assertion failed) size.width>0 && size.height>0 in function 'cv::imshow'"
+            # Seems to be because frame_to_show is null
+            cv2.imshow("Video", frame_to_show)
 
         # Hit 'q' on the keyboard to quit!
         if cv2.waitKey(1) & 0xFF == ord("q"):
diff --git a/wyzely_detect/utils/cli_args.py b/wyzely_detect/utils/cli_args.py
index b18d20f..0b6eaf0 100644
--- a/wyzely_detect/utils/cli_args.py
+++ b/wyzely_detect/utils/cli_args.py
@@ -92,6 +92,7 @@ def set_argparse():
         help="The URL to send notifications to",
     )
 
+    # Various timers
     timers = argparser.add_argument_group("Timers")
     timers.add_argument(
         "--detection-duration",
diff --git a/wyzely_detect/utils/utils.py b/wyzely_detect/utils/utils.py
index 19ea7ea..bc6a3b0 100644
--- a/wyzely_detect/utils/utils.py
+++ b/wyzely_detect/utils/utils.py
@@ -2,9 +2,165 @@ import cv2
 import numpy as np
 from pathlib import Path
 from deepface import DeepFace
+from . import notify
 
 first_face_try = True
 
+# TODO: When multi-camera support is added, this will need to be changed so that each camera has its own dict
+objects_and_peoples = {
+    "objects": {},
+    "peoples": {},
+}
+
+
+def process_footage(
+    # Frame
+    frame: np.ndarray = None,
+
+    # scale
+    run_scale: float = None,
+    view_scale: float = None,
+
+    # Face stuff
+    faces_directory: str = None,
+    face_confidence_threshold: float = None,
+    no_remove_representations: bool = False,
+
+    # Timer stuff
+    detection_window: int = None,
+    detection_duration: int = None,
+    notification_window: int = None,
+
+    ntfy_url: str = None,
+
+    # Object stuff
+    # YOLO object
+    model = None,
+    detect_object: list = None,
+    object_confidence_threshold = None
+) -> np.ndarray:
+    """
+    Takes in a frame and processes it
+    """ 
+
+    global objects_and_peoples
+
+    
+    # Resize frame of video to a smaller size for faster recognition processing
+    run_frame = cv2.resize(frame, (0, 0), fx=run_scale, fy=run_scale)
+    # view_frame = cv2.resize(frame, (0, 0), fx=args.view_scale, fy=args.view_scale)
+
+    results = model(run_frame, verbose=False)
+
+    path_to_faces = Path(faces_directory)
+    path_to_faces_exists = path_to_faces.is_dir()
+
+    for i, r in enumerate(results):
+        # list of dicts with each dict containing a label, x1, y1, x2, y2
+        plot_boxes = []
+
+        # The following is stuff for people
+        # This is still in the for loop as each result, no matter if anything is detected, will be present.
+        # Thus, there will always be one result (r)
+
+        # Only run if path_to_faces exists
+        # May be better to check every iteration, but this also works
+        if path_to_faces_exists:
+            if face_details := recognize_face(
+                path_to_directory=path_to_faces,
+                run_frame=run_frame,
+                # Perhaps make these names match?
+                min_confidence=face_confidence_threshold,
+                no_remove_representations=no_remove_representations,
+            ):
+                plot_boxes.append(face_details)
+                objects_and_peoples = notify.thing_detected(
+                    thing_name=face_details["label"],
+                    objects_and_peoples=objects_and_peoples,
+                    detection_type="peoples",
+                    detection_window=detection_window,
+                    detection_duration=detection_duration,
+                    notification_window=notification_window,
+                    ntfy_url=ntfy_url,
+                )
+
+        # The following is stuff for objects
+        # Setup dictionary of object names
+        if (
+            objects_and_peoples["objects"] == {}
+            or objects_and_peoples["objects"] is None
+        ):
+            for name in r.names.values():
+                objects_and_peoples["objects"][name] = {
+                    "last_detection_time": None,
+                    "detection_duration": None,
+                    # "first_detection_time": None,
+                    "last_notification_time": None,
+                }
+            # Also, make sure that the objects to detect are in the list of objects_and_peoples
+            # If it isn't, print a warning
+            for obj in detect_object:
+                if obj not in objects_and_peoples:
+                    print(
+                        f"Warning: {obj} is not in the list of objects the model can detect!"
+                    )
+
+        for box in r.boxes:
+            # Get the name of the object
+            class_id = r.names[box.cls[0].item()]
+            # Get the coordinates of the object
+            cords = box.xyxy[0].tolist()
+            cords = [round(x) for x in cords]
+            # Get the confidence
+            conf = round(box.conf[0].item(), 2)
+            # Print it out, adding a spacer between each object
+            # print("Object type:", class_id)
+            # print("Coordinates:", cords)
+            # print("Probability:", conf)
+            # print("---")
+
+            # Now do stuff (if conf > 0.5)
+            if conf < object_confidence_threshold or (
+                class_id not in detect_object and detect_object != []
+            ):
+                # If the confidence is too low
+                # or if the object is not in the list of objects to detect and the list of objects to detect is not empty
+                # then skip this iteration
+                continue
+
+            # Add the object to the list of objects to plot
+            plot_boxes.append(
+                {
+                    "label": class_id,
+                    "x1": cords[0],
+                    "y1": cords[1],
+                    "x2": cords[2],
+                    "y2": cords[3],
+                }
+            )
+
+            objects_and_peoples = notify.thing_detected(
+                thing_name=class_id,
+                objects_and_peoples=objects_and_peoples,
+                detection_type="objects",
+                detection_window=detection_window,
+                detection_duration=detection_duration,
+                notification_window=notification_window,
+                ntfy_url=ntfy_url,
+            )
+            
+
+            # To debug plotting, use r.plot() to cross reference the bounding boxes drawn by the plot_label() and r.plot()
+            frame_to_show = plot_label(
+                boxes=plot_boxes,
+                full_frame=frame,
+                # full_frame=r.plot(),
+                run_scale=run_scale,
+                view_scale=view_scale,
+            )
+            # Unsure if this should also return the objects_and_peoples dict
+            return frame_to_show
+
 
 def plot_label(
     # list of dicts with each dict containing a label, x1, y1, x2, y2
@@ -18,7 +174,7 @@ def plot_label(
     # So the coordinates will be scaled appropriately when coming from run_frame
     view_scale: float = None,
     font: int = cv2.FONT_HERSHEY_SIMPLEX,
-):
+) -> np.ndarray:
     # x1 and y1 are the top left corner of the box
     # x2 and y2 are the bottom right corner of the box
     # Example scaling: full_frame: 1 run_frame: 0.5 view_frame: 0.25
@@ -176,6 +332,7 @@ def recognize_face(
             f"Cosine similarity: {cosine_similarity}, filname: {path_to_image.name}, to_return: {to_return}"
         )
         return to_return
+    return None
 
     """
     Example dataframe, for reference

From e7b63126d24f1558fbf77d2758ec4d9474e587c6 Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Fri, 22 Dec 2023 16:44:21 -0600
Subject: [PATCH 02/18] Fixed (?) prior error causing null `frame_to_show`

---
 wyzely_detect/__main__.py    |  2 --
 wyzely_detect/utils/utils.py | 20 ++++++++++----------
 2 files changed, 10 insertions(+), 12 deletions(-)

diff --git a/wyzely_detect/__main__.py b/wyzely_detect/__main__.py
index d17be86..7d8e16c 100644
--- a/wyzely_detect/__main__.py
+++ b/wyzely_detect/__main__.py
@@ -88,8 +88,6 @@ def main():
         # Display the resulting frame
         # TODO: When multi-camera support is added, this needs to be changed to allow all feeds
         if not args.no_display:
-            # When a face isn't recognized: "cv2.error: OpenCV(4.8.1) D:\a\opencv-python\opencv-python\opencv\modules\highgui\src\window.cpp:971: error: (-215:Assertion failed) size.width>0 && size.height>0 in function 'cv::imshow'"
-            # Seems to be because frame_to_show is null
             cv2.imshow("Video", frame_to_show)
 
         # Hit 'q' on the keyboard to quit!
diff --git a/wyzely_detect/utils/utils.py b/wyzely_detect/utils/utils.py
index bc6a3b0..b5fcd6d 100644
--- a/wyzely_detect/utils/utils.py
+++ b/wyzely_detect/utils/utils.py
@@ -150,16 +150,16 @@ def process_footage(
             )
             
 
-            # To debug plotting, use r.plot() to cross reference the bounding boxes drawn by the plot_label() and r.plot()
-            frame_to_show = plot_label(
-                boxes=plot_boxes,
-                full_frame=frame,
-                # full_frame=r.plot(),
-                run_scale=run_scale,
-                view_scale=view_scale,
-            )
-            # Unsure if this should also return the objects_and_peoples dict
-            return frame_to_show
+        # To debug plotting, use r.plot() to cross reference the bounding boxes drawn by the plot_label() and r.plot()
+        frame_to_show = plot_label(
+            boxes=plot_boxes,
+            full_frame=frame,
+            # full_frame=r.plot(),
+            run_scale=run_scale,
+            view_scale=view_scale,
+        )
+        # Unsure if this should also return the objects_and_peoples dict
+        return frame_to_show
 
 
 def plot_label(

From 06bd1ccbd753ebaa08314aa88d14c2d1e535f50d Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Sun, 24 Dec 2023 15:28:47 -0600
Subject: [PATCH 03/18] Fixed incorrect warning when using `--detect-object`

---
 wyzely_detect/__main__.py    | 3 +--
 wyzely_detect/utils/utils.py | 2 +-
 2 files changed, 2 insertions(+), 3 deletions(-)

diff --git a/wyzely_detect/__main__.py b/wyzely_detect/__main__.py
index 7d8e16c..5db34e5 100644
--- a/wyzely_detect/__main__.py
+++ b/wyzely_detect/__main__.py
@@ -1,6 +1,5 @@
 # import face_recognition
 from pathlib import Path
-import os
 import cv2
 
 # import hjson as json
@@ -16,7 +15,7 @@ args = None
 
 def main():
     global objects_and_peoples
-    global args
+    global args 
     # RUN_BY_COMPOSE = os.getenv("RUN_BY_COMPOSE") # Replace this with code to check for gpu
 
     args = argparser.parse_args()
diff --git a/wyzely_detect/utils/utils.py b/wyzely_detect/utils/utils.py
index b5fcd6d..0a12de2 100644
--- a/wyzely_detect/utils/utils.py
+++ b/wyzely_detect/utils/utils.py
@@ -100,7 +100,7 @@ def process_footage(
             # Also, make sure that the objects to detect are in the list of objects_and_peoples
             # If it isn't, print a warning
             for obj in detect_object:
-                if obj not in objects_and_peoples:
+                if obj not in objects_and_peoples["objects"].keys():
                     print(
                         f"Warning: {obj} is not in the list of objects the model can detect!"
                     )

From 82abe8b6d5f1109d803dbf5ada03aabb0075e36b Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Sun, 24 Dec 2023 16:07:53 -0600
Subject: [PATCH 04/18] Fixed `--detect-object` when specifying multiple
 objects

---
 .vscode/launch.json             | 10 ++++++++++
 wyzely_detect/utils/cli_args.py |  2 +-
 2 files changed, 11 insertions(+), 1 deletion(-)

diff --git a/.vscode/launch.json b/.vscode/launch.json
index f7701bf..5990161 100644
--- a/.vscode/launch.json
+++ b/.vscode/launch.json
@@ -14,6 +14,16 @@
             ],
             "justMyCode": true
         },
+        // {
+        //     "name": "Quick, Specific Debug",
+        //     "type": "python",
+        //     "request": "launch",
+        //     "module": "wyzely_detect",
+        //     "args": [
+        //         "--run-scale", "0.25", "--view-scale", "0.5", "--no-remove-representations", "--detect-object", "person", "--detect-object", "cell phone"
+        //     ],
+        //     "justMyCode": true
+        // },
         {
             // "name": "Python: Module",
             "name": "Full Debug",
diff --git a/wyzely_detect/utils/cli_args.py b/wyzely_detect/utils/cli_args.py
index 0b6eaf0..0f9e1ef 100644
--- a/wyzely_detect/utils/cli_args.py
+++ b/wyzely_detect/utils/cli_args.py
@@ -154,7 +154,7 @@ def set_argparse():
     object_detection = argparser.add_argument_group("Object Detection options")
     object_detection.add_argument(
         "--detect-object",
-        nargs="*",
+        action="append",
         default=[],
         type=str,
         help="The object(s) to detect. Must be something the model is trained to detect",

From 5cc5e04642cb406142031d23fc05a2918764f2ef Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Sun, 31 Dec 2023 16:37:13 -0600
Subject: [PATCH 05/18] Works on MacOS?

---
 README.md   |   3 +
 poetry.lock | 600 ++++++++++++++++++++++++++--------------------------
 2 files changed, 307 insertions(+), 296 deletions(-)

diff --git a/README.md b/README.md
index 902316d..b858d52 100644
--- a/README.md
+++ b/README.md
@@ -16,6 +16,9 @@ Recognize faces/objects in a video stream (from a webcam or a security camera) a
     - All RTSP feeds _should_ work, however.  
 - Python 3.10 or 3.11  
 - Poetry (optional)  
+- Windows or Linux  
+    - I've tested this on MacOS - it works on my 2014 MacBook Air but not a 2011 MacBook Pro  
+    - Both were upgraded with OpenCore, with the MacBook Air running Monterey and the MacBook Pro running a newer version of MacOS, which may have been the problem  
 
 ### Docker  
 - A Wyze Cam  
diff --git a/poetry.lock b/poetry.lock
index 2425330..e35998d 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -13,19 +13,20 @@ files = [
 
 [[package]]
 name = "anyio"
-version = "4.1.0"
+version = "4.2.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "anyio-4.1.0-py3-none-any.whl", hash = "sha256:56a415fbc462291813a94528a779597226619c8e78af7de0507333f700011e5f"},
-    {file = "anyio-4.1.0.tar.gz", hash = "sha256:5a0bec7085176715be77df87fc66d6c9d70626bd752fcc85f57cdbee5b3760da"},
+    {file = "anyio-4.2.0-py3-none-any.whl", hash = "sha256:745843b39e829e108e518c489b31dc757de7d2131d53fac32bd8df268227bfee"},
+    {file = "anyio-4.2.0.tar.gz", hash = "sha256:e1875bb4b4e2de1669f4bc7869b6d3f54231cdced71605e6e64c9be77e3be50f"},
 ]
 
 [package.dependencies]
 exceptiongroup = {version = ">=1.0.2", markers = "python_version < \"3.11\""}
 idna = ">=2.8"
 sniffio = ">=1.1"
+typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
 doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
@@ -78,21 +79,22 @@ wheel = ">=0.23.0,<1.0"
 
 [[package]]
 name = "attrs"
-version = "23.1.0"
+version = "23.2.0"
 description = "Classes Without Boilerplate"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "attrs-23.1.0-py3-none-any.whl", hash = "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04"},
-    {file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"},
+    {file = "attrs-23.2.0-py3-none-any.whl", hash = "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1"},
+    {file = "attrs-23.2.0.tar.gz", hash = "sha256:935dc3b529c262f6cf76e50877d35a4bd3c1de194fd41f47a2b7ae8f19971f30"},
 ]
 
 [package.extras]
 cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
-dev = ["attrs[docs,tests]", "pre-commit"]
+dev = ["attrs[tests]", "pre-commit"]
 docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
 tests = ["attrs[tests-no-zope]", "zope-interface"]
-tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+tests-mypy = ["mypy (>=1.6)", "pytest-mypy-plugins"]
+tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
 
 [[package]]
 name = "beautifulsoup4"
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 [package.dependencies]
@@ -150,7 +156,7 @@ typing-extensions = {version = ">=4.0.1", markers = "python_version < \"3.11\""}
 
 [package.extras]
 colorama = ["colorama (>=0.4.3)"]
-d = ["aiohttp (>=3.7.4)"]
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 jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
 uvloop = ["uvloop (>=0.15.2)"]
 
@@ -593,13 +599,13 @@ tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipyth
 
 [[package]]
 name = "fastjsonschema"
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 python-versions = "*"
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 ]
 
 [package.extras]
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+all = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "fs (>=2.2.0,<3)", "lxml (>=4.0,<5)", "lz4 (>=1.7.4.2)", "matplotlib", "munkres", "pycairo", "scipy", "skia-pathops (>=0.5.0)", "sympy", "uharfbuzz (>=0.23.0)", "unicodedata2 (>=15.1.0)", "xattr", "zopfli (>=0.1.4)"]
 graphite = ["lz4 (>=1.7.4.2)"]
-interpolatable = ["munkres", "scipy"]
+interpolatable = ["munkres", "pycairo", "scipy"]
 lxml = ["lxml (>=4.0,<5)"]
 pathops = ["skia-pathops (>=0.5.0)"]
 plot = ["matplotlib"]
@@ -735,13 +741,13 @@ woff = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "zopfli (>=0.1.4)"]
 
 [[package]]
 name = "fsspec"
-version = "2023.12.1"
+version = "2023.12.2"
 description = "File-system specification"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -1056,13 +1062,13 @@ files = [
 
 [[package]]
 name = "ipykernel"
-version = "6.27.1"
+version = "6.28.0"
 description = "IPython Kernel for Jupyter"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -1076,7 +1082,7 @@ matplotlib-inline = ">=0.1"
 nest-asyncio = "*"
 packaging = "*"
 psutil = "*"
-pyzmq = ">=20"
+pyzmq = ">=24"
 tornado = ">=6.1"
 traitlets = ">=5.4.0"
 
@@ -1089,13 +1095,13 @@ test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio"
 
 [[package]]
 name = "ipython"
-version = "8.18.1"
+version = "8.19.0"
 description = "IPython: Productive Interactive Computing"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 files = [
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 ]
 
 [package.dependencies]
@@ -1111,17 +1117,17 @@ stack-data = "*"
 traitlets = ">=5"
 
 [package.extras]
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+all = ["black", "curio", "docrepr", "exceptiongroup", "ipykernel", "ipyparallel", "ipywidgets", "matplotlib", "matplotlib (!=3.2.0)", "nbconvert", "nbformat", "notebook", "numpy (>=1.23)", "pandas", "pickleshare", "pytest", "pytest-asyncio (<0.22)", "qtconsole", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "trio", "typing-extensions"]
 black = ["black"]
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+doc = ["docrepr", "exceptiongroup", "ipykernel", "matplotlib", "pickleshare", "pytest", "pytest-asyncio (<0.22)", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "typing-extensions"]
 kernel = ["ipykernel"]
 nbconvert = ["nbconvert"]
 nbformat = ["nbformat"]
 notebook = ["ipywidgets", "notebook"]
 parallel = ["ipyparallel"]
 qtconsole = ["qtconsole"]
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-test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.22)", "pandas", "pickleshare", "pytest (<7.1)", "pytest-asyncio (<0.22)", "testpath", "trio"]
+test = ["pickleshare", "pytest", "pytest-asyncio (<0.22)", "testpath"]
+test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.23)", "pandas", "pickleshare", "pytest", "pytest-asyncio (<0.22)", "testpath", "trio"]
 
 [[package]]
 name = "itsdangerous"
@@ -1193,13 +1199,13 @@ format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-
 
 [[package]]
 name = "jsonschema-specifications"
-version = "2023.11.2"
+version = "2023.12.1"
 description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -1229,13 +1235,13 @@ test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pyt
 
 [[package]]
 name = "jupyter-core"
-version = "5.5.0"
+version = "5.5.1"
 description = "Jupyter core package. A base package on which Jupyter projects rely."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -1661,13 +1667,13 @@ test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=
 
 [[package]]
 name = "nbconvert"
-version = "7.12.0"
+version = "7.13.1"
 description = "Converting Jupyter Notebooks"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -1693,7 +1699,7 @@ docs = ["ipykernel", "ipython", "myst-parser", "nbsphinx (>=0.2.12)", "pydata-sp
 qtpdf = ["nbconvert[qtpng]"]
 qtpng = ["pyqtwebengine (>=5.15)"]
 serve = ["tornado (>=6.1)"]
-test = ["flaky", "ipykernel", "ipywidgets (>=7)", "pytest"]
+test = ["flaky", "ipykernel", "ipywidgets (>=7.5)", "pytest"]
 webpdf = ["playwright"]
 
 [[package]]
@@ -2064,25 +2070,25 @@ signedtoken = ["cryptography (>=3.0.0)", "pyjwt (>=2.0.0,<3)"]
 
 [[package]]
 name = "opencv-python"
-version = "4.8.1.78"
+version = "4.9.0.80"
 description = "Wrapper package for OpenCV python bindings."
 optional = false
 python-versions = ">=3.6"
 files = [
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 [package.dependencies]
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     {version = ">=1.21.2", markers = "platform_system != \"Darwin\" and python_version >= \"3.10\" and python_version < \"3.11\""},
+    {version = ">=1.23.5", markers = "python_version >= \"3.11\""},
 ]
 
 [[package]]
@@ -2150,8 +2156,8 @@ files = [
 
 [package.dependencies]
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     {version = ">=1.22.4,<2", markers = "python_version < \"3.11\""},
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 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
@@ -2209,13 +2215,13 @@ testing = ["docopt", "pytest (<6.0.0)"]
 
 [[package]]
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 [[package]]
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 [package.extras]
@@ -2790,110 +2796,110 @@ tensorflow = ">=1.9.0"
 
 [[package]]
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 python-versions = ">=3.8"
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 [[package]]
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 [[package]]
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 pandas = ">=1.2"
 
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 python-versions = ">=3.8"
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 ]
 
 [package.dependencies]
 numpy = "*"
 pillow = ">=5.3.0,<8.3.dev0 || >=8.4.dev0"
 requests = "*"
-torch = "2.1.1"
+torch = "2.1.2"
 
 [package.extras]
 scipy = ["scipy"]
@@ -3475,35 +3481,35 @@ tutorials = ["matplotlib", "pandas", "tabulate"]
 
 [[package]]
 name = "typing-extensions"
-version = "4.8.0"
+version = "4.9.0"
 description = "Backported and Experimental Type Hints for Python 3.8+"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
 name = "tzdata"
-version = "2023.3"
+version = "2023.4"
 description = "Provider of IANA time zone data"
 optional = false
 python-versions = ">=2"
 files = [
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 ]
 
 [[package]]
 name = "ultralytics"
-version = "8.0.225"
+version = "8.0.231"
 description = "Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -3524,8 +3530,10 @@ torchvision = ">=0.9.0"
 tqdm = ">=4.64.0"
 
 [package.extras]
-dev = ["check-manifest", "coverage", "ipython", "mkdocs-material", "mkdocs-redirects", "mkdocs-ultralytics-plugin (>=0.0.34)", "mkdocstrings[python]", "pre-commit", "pytest", "pytest-cov"]
-export = ["coremltools (>=7.0)", "openvino-dev (>=2023.0)", "tensorflow (<=2.13.1)", "tensorflowjs"]
+dev = ["check-manifest", "coverage[toml]", "ipython", "mkdocs-material", "mkdocs-redirects", "mkdocs-ultralytics-plugin (>=0.0.34)", "mkdocstrings[python]", "pre-commit", "pytest", "pytest-cov"]
+export = ["coremltools (>=7.0)", "jax (<=0.4.21)", "jaxlib (<=0.4.21)", "onnx (>=1.12.0)", "openvino-dev (>=2023.0)", "tensorflow (<=2.13.1)", "tensorflowjs (>=3.9.0)"]
+extra = ["albumentations (>=1.0.3)", "ipython", "pycocotools (>=2.0.6)"]
+logging = ["comet", "dvclive (>=2.12.0)", "tensorboard (>=2.13.0)"]
 
 [[package]]
 name = "urllib3"

From d3c157df4d2337512dfc33992187f22ace710fea Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Sat, 10 Feb 2024 21:16:11 -0600
Subject: [PATCH 06/18] (untested) - Added args for multiple sources

Could not test due to dependency problems on Windows
---
 wyzely_detect/__main__.py       | 18 +++++++++++++-----
 wyzely_detect/utils/cli_args.py | 15 +++++++++------
 2 files changed, 22 insertions(+), 11 deletions(-)

diff --git a/wyzely_detect/__main__.py b/wyzely_detect/__main__.py
index 5db34e5..19ecf3b 100644
--- a/wyzely_detect/__main__.py
+++ b/wyzely_detect/__main__.py
@@ -2,6 +2,8 @@
 from pathlib import Path
 import cv2
 
+from PrettyTable import PrettyTable
+
 # import hjson as json
 import torch
 from ultralytics import YOLO
@@ -45,21 +47,27 @@ def main():
 
     # Depending on if the user wants to use a stream or a capture device,
     # Set the video capture to the appropriate source
-    if args.rtsp_url is not None:
-        video_capture = cv2.VideoCapture(args.rtsp_url)
+    if not args.rtsp_url and not args.capture_device:
+        print("No stream or capture device set, defaulting to capture device 0")
+        args.capture_device = [0]
     else:
-        video_capture = cv2.VideoCapture(args.capture_device)
+        video_sources = {
+            "streams": [cv2.VideoCapture(url) for url in args.rtsp_url],
+            "devices": [cv2.VideoCapture(device) for device in args.capture_device],
+        }
 
     # Eliminate lag by setting the buffer size to 1
     # This makes it so that the video capture will only grab the most recent frame
     # However, this means that the video may be choppy
-    video_capture.set(cv2.CAP_PROP_BUFFERSIZE, 1)
+    # Only do this for streams
+    for stream in video_sources["streams"]:
+        stream.set(cv2.CAP_PROP_BUFFERSIZE, 1)
 
     # Print the resolution of the video
     print(
         f"Video resolution: {video_capture.get(cv2.CAP_PROP_FRAME_WIDTH)}x{video_capture.get(cv2.CAP_PROP_FRAME_HEIGHT)}"  # noqa: E501
     )
-
+    print
     print("Beginning video capture...")
     while True:
         # Grab a single frame of video
diff --git a/wyzely_detect/utils/cli_args.py b/wyzely_detect/utils/cli_args.py
index 0f9e1ef..6337c76 100644
--- a/wyzely_detect/utils/cli_args.py
+++ b/wyzely_detect/utils/cli_args.py
@@ -29,17 +29,19 @@ def set_argparse():
     stream_source = video_options.add_mutually_exclusive_group()
     stream_source.add_argument(
         "--rtsp-url",
-        default=os.environ["RTSP_URL"]
-        if "RTSP_URL" in os.environ and os.environ["RTSP_URL"] != ""
-        else None,  # noqa: E501
+        action="append",
+        # If RTSP_URL is in the environment, use it, otherwise just use a blank list
+        # This may cause problems down the road, but if it does, env for this can be removed
+        default=[os.environ["RTSP_URL"]] if "RTSP_URL" in os.environ and os.environ["RTSP_URL"] != "" else [],
         type=str,
         help="RTSP camera URL",
     )
     stream_source.add_argument(
         "--capture-device",
-        default=os.environ["CAPTURE_DEVICE"]
-        if "CAPTURE_DEVICE" in os.environ and os.environ["CAPTURE_DEVICE"] != ""
-        else 0,  # noqa: E501
+        action="append",
+        # If CAPTURE_DEVICE is in the environment, use it, otherwise just use a blank list
+        # If __main__.py detects that no capture device or remote stream is set, it will default to 0
+        default=[int(os.environ["CAPTURE_DEVICE"])] if "CAPTURE_DEVICE" in os.environ and os.environ["CAPTURE_DEVICE"] != "" else [],
         type=int,
         help="Capture device number",
     )
@@ -155,6 +157,7 @@ def set_argparse():
     object_detection.add_argument(
         "--detect-object",
         action="append",
+        # Stuff is appended to default, as far as I can tell
         default=[],
         type=str,
         help="The object(s) to detect. Must be something the model is trained to detect",

From 3ac460a060420c5de97146fb336946715afc9caa Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Sat, 10 Feb 2024 21:38:22 -0600
Subject: [PATCH 07/18] Made PyTorch GPU functionality optional

---
 .python-version |   2 +-
 poetry.lock     | 232 ++++++++++++------------------------------------
 pyproject.toml  |  25 +++++-
 3 files changed, 78 insertions(+), 181 deletions(-)

diff --git a/.python-version b/.python-version
index c84ccce..9ac3804 100644
--- a/.python-version
+++ b/.python-version
@@ -1 +1 @@
-3.10.5
+3.11.5
diff --git a/poetry.lock b/poetry.lock
index e35998d..4877303 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
 
 [[package]]
 name = "absl-py"
@@ -1808,17 +1808,6 @@ files = [
     {file = "nvidia_cublas_cu11-11.11.3.6-py3-none-win_amd64.whl", hash = "sha256:6ab12b1302bef8ac1ff4414edd1c059e57f4833abef9151683fb8f4de25900be"},
 ]
 
-[[package]]
-name = "nvidia-cublas-cu12"
-version = "12.1.3.1"
-description = "CUBLAS native runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl", hash = "sha256:ee53ccca76a6fc08fb9701aa95b6ceb242cdaab118c3bb152af4e579af792728"},
-    {file = "nvidia_cublas_cu12-12.1.3.1-py3-none-win_amd64.whl", hash = "sha256:2b964d60e8cf11b5e1073d179d85fa340c120e99b3067558f3cf98dd69d02906"},
-]
-
 [[package]]
 name = "nvidia-cuda-cupti-cu11"
 version = "11.8.87"
@@ -1830,17 +1819,6 @@ files = [
     {file = "nvidia_cuda_cupti_cu11-11.8.87-py3-none-win_amd64.whl", hash = "sha256:4332d8550ad5f5b673f98d08e4e4f82030cb604c66d8d5ee919399ea01312e58"},
 ]
 
-[[package]]
-name = "nvidia-cuda-cupti-cu12"
-version = "12.1.105"
-description = "CUDA profiling tools runtime libs."
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:e54fde3983165c624cb79254ae9818a456eb6e87a7fd4d56a2352c24ee542d7e"},
-    {file = "nvidia_cuda_cupti_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:bea8236d13a0ac7190bd2919c3e8e6ce1e402104276e6f9694479e48bb0eb2a4"},
-]
-
 [[package]]
 name = "nvidia-cuda-nvcc-cu11"
 version = "11.8.89"
@@ -1852,17 +1830,6 @@ files = [
     {file = "nvidia_cuda_nvcc_cu11-11.8.89-py3-none-win_amd64.whl", hash = "sha256:bcfb622d2449982812eb0fa43b3de0593e877edd33790f423a228ed1be62378c"},
 ]
 
-[[package]]
-name = "nvidia-cuda-nvrtc-cu12"
-version = "12.1.105"
-description = "NVRTC native runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:339b385f50c309763ca65456ec75e17bbefcbbf2893f462cb8b90584cd27a1c2"},
-    {file = "nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:0a98a522d9ff138b96c010a65e145dc1b4850e9ecb75a0172371793752fd46ed"},
-]
-
 [[package]]
 name = "nvidia-cuda-runtime-cu11"
 version = "11.8.89"
@@ -1874,17 +1841,6 @@ files = [
     {file = "nvidia_cuda_runtime_cu11-11.8.89-py3-none-win_amd64.whl", hash = "sha256:f60c9fdaed8065b38de8097867240efc5556a8a710007146daeb9082334a6e63"},
 ]
 
-[[package]]
-name = "nvidia-cuda-runtime-cu12"
-version = "12.1.105"
-description = "CUDA Runtime native Libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:6e258468ddf5796e25f1dc591a31029fa317d97a0a94ed93468fc86301d61e40"},
-    {file = "nvidia_cuda_runtime_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:dfb46ef84d73fababab44cf03e3b83f80700d27ca300e537f85f636fac474344"},
-]
-
 [[package]]
 name = "nvidia-cudnn-cu11"
 version = "8.7.0.84"
@@ -1898,19 +1854,6 @@ files = [
 [package.dependencies]
 nvidia-cublas-cu11 = "*"
 
-[[package]]
-name = "nvidia-cudnn-cu12"
-version = "8.9.2.26"
-description = "cuDNN runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl", hash = "sha256:5ccb288774fdfb07a7e7025ffec286971c06d8d7b4fb162525334616d7629ff9"},
-]
-
-[package.dependencies]
-nvidia-cublas-cu12 = "*"
-
 [[package]]
 name = "nvidia-cufft-cu11"
 version = "10.9.0.58"
@@ -1922,17 +1865,6 @@ files = [
     {file = "nvidia_cufft_cu11-10.9.0.58-py3-none-win_amd64.whl", hash = "sha256:c4d316f17c745ec9c728e30409612eaf77a8404c3733cdf6c9c1569634d1ca03"},
 ]
 
-[[package]]
-name = "nvidia-cufft-cu12"
-version = "11.0.2.54"
-description = "CUFFT native runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl", hash = "sha256:794e3948a1aa71fd817c3775866943936774d1c14e7628c74f6f7417224cdf56"},
-    {file = "nvidia_cufft_cu12-11.0.2.54-py3-none-win_amd64.whl", hash = "sha256:d9ac353f78ff89951da4af698f80870b1534ed69993f10a4cf1d96f21357e253"},
-]
-
 [[package]]
 name = "nvidia-curand-cu11"
 version = "10.3.0.86"
@@ -1944,17 +1876,6 @@ files = [
     {file = "nvidia_curand_cu11-10.3.0.86-py3-none-win_amd64.whl", hash = "sha256:8fa8365065fc3e3760d7437b08f164a6bcf8f7124f3b544d2463ded01e6bdc70"},
 ]
 
-[[package]]
-name = "nvidia-curand-cu12"
-version = "10.3.2.106"
-description = "CURAND native runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl", hash = "sha256:9d264c5036dde4e64f1de8c50ae753237c12e0b1348738169cd0f8a536c0e1e0"},
-    {file = "nvidia_curand_cu12-10.3.2.106-py3-none-win_amd64.whl", hash = "sha256:75b6b0c574c0037839121317e17fd01f8a69fd2ef8e25853d826fec30bdba74a"},
-]
-
 [[package]]
 name = "nvidia-cusolver-cu11"
 version = "11.4.1.48"
@@ -1969,22 +1890,6 @@ files = [
 [package.dependencies]
 nvidia-cublas-cu11 = "*"
 
-[[package]]
-name = "nvidia-cusolver-cu12"
-version = "11.4.5.107"
-description = "CUDA solver native runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl", hash = "sha256:8a7ec542f0412294b15072fa7dab71d31334014a69f953004ea7a118206fe0dd"},
-    {file = "nvidia_cusolver_cu12-11.4.5.107-py3-none-win_amd64.whl", hash = "sha256:74e0c3a24c78612192a74fcd90dd117f1cf21dea4822e66d89e8ea80e3cd2da5"},
-]
-
-[package.dependencies]
-nvidia-cublas-cu12 = "*"
-nvidia-cusparse-cu12 = "*"
-nvidia-nvjitlink-cu12 = "*"
-
 [[package]]
 name = "nvidia-cusparse-cu11"
 version = "11.7.5.86"
@@ -1996,20 +1901,6 @@ files = [
     {file = "nvidia_cusparse_cu11-11.7.5.86-py3-none-win_amd64.whl", hash = "sha256:a0f6ee81cd91be606fc2f55992d06b09cd4e86d74b6ae5e8dd1631cf7f5a8706"},
 ]
 
-[[package]]
-name = "nvidia-cusparse-cu12"
-version = "12.1.0.106"
-description = "CUSPARSE native runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl", hash = "sha256:f3b50f42cf363f86ab21f720998517a659a48131e8d538dc02f8768237bd884c"},
-    {file = "nvidia_cusparse_cu12-12.1.0.106-py3-none-win_amd64.whl", hash = "sha256:b798237e81b9719373e8fae8d4f091b70a0cf09d9d85c95a557e11df2d8e9a5a"},
-]
-
-[package.dependencies]
-nvidia-nvjitlink-cu12 = "*"
-
 [[package]]
 name = "nvidia-nccl-cu11"
 version = "2.16.5"
@@ -2020,38 +1911,6 @@ files = [
     {file = "nvidia_nccl_cu11-2.16.5-py3-none-manylinux1_x86_64.whl", hash = "sha256:948cc9a8c659fc6cc3456dd54844fe203519b82ae87e3e94b9818dd9d94deaad"},
 ]
 
-[[package]]
-name = "nvidia-nccl-cu12"
-version = "2.18.1"
-description = "NVIDIA Collective Communication Library (NCCL) Runtime"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_nccl_cu12-2.18.1-py3-none-manylinux1_x86_64.whl", hash = "sha256:1a6c4acefcbebfa6de320f412bf7866de856e786e0462326ba1bac40de0b5e71"},
-]
-
-[[package]]
-name = "nvidia-nvjitlink-cu12"
-version = "12.3.101"
-description = "Nvidia JIT LTO Library"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_nvjitlink_cu12-12.3.101-py3-none-manylinux1_x86_64.whl", hash = "sha256:64335a8088e2b9d196ae8665430bc6a2b7e6ef2eb877a9c735c804bd4ff6467c"},
-    {file = "nvidia_nvjitlink_cu12-12.3.101-py3-none-win_amd64.whl", hash = "sha256:1b2e317e437433753530792f13eece58f0aec21a2b05903be7bffe58a606cbd1"},
-]
-
-[[package]]
-name = "nvidia-nvtx-cu12"
-version = "12.1.105"
-description = "NVIDIA Tools Extension"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl", hash = "sha256:dc21cf308ca5691e7c04d962e213f8a4aa9bbfa23d95412f452254c2caeb09e5"},
-    {file = "nvidia_nvtx_cu12-12.1.105-py3-none-win_amd64.whl", hash = "sha256:65f4d98982b31b60026e0e6de73fbdfc09d08a96f4656dd3665ca616a11e1e82"},
-]
-
 [[package]]
 name = "oauthlib"
 version = "3.2.2"
@@ -2086,9 +1945,9 @@ files = [
 
 [package.dependencies]
 numpy = [
+    {version = ">=1.23.5", markers = "python_version >= \"3.11\""},
     {version = ">=1.21.4", markers = "python_version >= \"3.10\" and platform_system == \"Darwin\" and python_version < \"3.11\""},
     {version = ">=1.21.2", markers = "platform_system != \"Darwin\" and python_version >= \"3.10\" and python_version < \"3.11\""},
-    {version = ">=1.23.5", markers = "python_version >= \"3.11\""},
 ]
 
 [[package]]
@@ -2156,8 +2015,8 @@ files = [
 
 [package.dependencies]
 numpy = [
-    {version = ">=1.22.4,<2", markers = "python_version < \"3.11\""},
     {version = ">=1.23.2,<2", markers = "python_version == \"3.11\""},
+    {version = ">=1.22.4,<2", markers = "python_version < \"3.11\""},
 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
@@ -3310,31 +3169,53 @@ files = [
 
 [[package]]
 name = "torch"
-version = "2.1.2"
+version = "2.1.2+cpu"
 description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "torch-2.1.2-cp310-cp310-manylinux1_x86_64.whl", hash = "sha256:3a871edd6c02dae77ad810335c0833391c1a4ce49af21ea8cf0f6a5d2096eea8"},
-    {file = "torch-2.1.2-cp310-cp310-manylinux2014_aarch64.whl", hash = "sha256:bef6996c27d8f6e92ea4e13a772d89611da0e103b48790de78131e308cf73076"},
-    {file = "torch-2.1.2-cp310-cp310-win_amd64.whl", hash = "sha256:0e13034fd5fb323cbbc29e56d0637a3791e50dd589616f40c79adfa36a5a35a1"},
-    {file = "torch-2.1.2-cp310-none-macosx_10_9_x86_64.whl", hash = "sha256:d9b535cad0df3d13997dbe8bd68ac33e0e3ae5377639c9881948e40794a61403"},
-    {file = "torch-2.1.2-cp310-none-macosx_11_0_arm64.whl", hash = "sha256:f9a55d55af02826ebfbadf4e9b682f0f27766bc33df8236b48d28d705587868f"},
-    {file = "torch-2.1.2-cp311-cp311-manylinux1_x86_64.whl", hash = "sha256:a6ebbe517097ef289cc7952783588c72de071d4b15ce0f8b285093f0916b1162"},
-    {file = "torch-2.1.2-cp311-cp311-manylinux2014_aarch64.whl", hash = "sha256:8f32ce591616a30304f37a7d5ea80b69ca9e1b94bba7f308184bf616fdaea155"},
-    {file = "torch-2.1.2-cp311-cp311-win_amd64.whl", hash = "sha256:e0ee6cf90c8970e05760f898d58f9ac65821c37ffe8b04269ec787aa70962b69"},
-    {file = "torch-2.1.2-cp311-none-macosx_10_9_x86_64.whl", hash = "sha256:76d37967c31c99548ad2c4d3f2cf191db48476f2e69b35a0937137116da356a1"},
-    {file = "torch-2.1.2-cp311-none-macosx_11_0_arm64.whl", hash = "sha256:e2d83f07b4aac983453ea5bf8f9aa9dacf2278a8d31247f5d9037f37befc60e4"},
-    {file = "torch-2.1.2-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:f41fe0c7ecbf903a568c73486139a75cfab287a0f6c17ed0698fdea7a1e8641d"},
-    {file = "torch-2.1.2-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:e3225f47d50bb66f756fe9196a768055d1c26b02154eb1f770ce47a2578d3aa7"},
-    {file = "torch-2.1.2-cp38-cp38-win_amd64.whl", hash = "sha256:33d59cd03cb60106857f6c26b36457793637512998666ee3ce17311f217afe2b"},
-    {file = "torch-2.1.2-cp38-none-macosx_10_9_x86_64.whl", hash = "sha256:8e221deccd0def6c2badff6be403e0c53491805ed9915e2c029adbcdb87ab6b5"},
-    {file = "torch-2.1.2-cp38-none-macosx_11_0_arm64.whl", hash = "sha256:05b18594f60a911a0c4f023f38a8bda77131fba5fd741bda626e97dcf5a3dd0a"},
-    {file = "torch-2.1.2-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:9ca96253b761e9aaf8e06fb30a66ee301aecbf15bb5a303097de1969077620b6"},
-    {file = "torch-2.1.2-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:d93ba70f67b08c2ae5598ee711cbc546a1bc8102cef938904b8c85c2089a51a0"},
-    {file = "torch-2.1.2-cp39-cp39-win_amd64.whl", hash = "sha256:255b50bc0608db177e6a3cc118961d77de7e5105f07816585fa6f191f33a9ff3"},
-    {file = "torch-2.1.2-cp39-none-macosx_10_9_x86_64.whl", hash = "sha256:6984cd5057c0c977b3c9757254e989d3f1124f4ce9d07caa6cb637783c71d42a"},
-    {file = "torch-2.1.2-cp39-none-macosx_11_0_arm64.whl", hash = "sha256:bc195d7927feabc0eb7c110e457c955ed2ab616f3c7c28439dd4188cf589699f"},
+    {file = "torch-2.1.2+cpu-cp310-cp310-linux_x86_64.whl", hash = "sha256:bf3ca897f8c7c218dd6c4b1cc5eec57b4f4e71106b0b8120e92f5fdaf4acf6cd"},
+    {file = "torch-2.1.2+cpu-cp310-cp310-win_amd64.whl", hash = "sha256:679458a652006bc5b9d3972f046ae299039dcc63f465ac623b439cbc27a3645c"},
+    {file = "torch-2.1.2+cpu-cp311-cp311-linux_x86_64.whl", hash = "sha256:6acac7871cca2b72f00b60496dd7d59d7d8247721f374705b8f9c6b9aeea482a"},
+    {file = "torch-2.1.2+cpu-cp311-cp311-win_amd64.whl", hash = "sha256:d7ed25db586afef2c022eb143471c6742088decbe05ed1f879fac770e67df189"},
+    {file = "torch-2.1.2+cpu-cp38-cp38-linux_x86_64.whl", hash = "sha256:c4620b08e9b8572594861ebedaf739d86801068a48c0399cbdf6559d1d351789"},
+    {file = "torch-2.1.2+cpu-cp38-cp38-win_amd64.whl", hash = "sha256:8b90d5c0023891717dfc5659eebe6c57c3632db1e3981e22e523be51c4c962c9"},
+    {file = "torch-2.1.2+cpu-cp39-cp39-linux_x86_64.whl", hash = "sha256:10df25736edb00852eca6041941e99d13502e65773d5c6164372eaaab83d976b"},
+    {file = "torch-2.1.2+cpu-cp39-cp39-win_amd64.whl", hash = "sha256:83bac7f809c09700c227abc9e3474e3a847a3f4c1bb2443aa16004f36a1e7e43"},
+]
+
+[package.dependencies]
+filelock = "*"
+fsspec = "*"
+jinja2 = "*"
+networkx = "*"
+sympy = "*"
+typing-extensions = "*"
+
+[package.extras]
+dynamo = ["jinja2"]
+opt-einsum = ["opt-einsum (>=3.3)"]
+
+[package.source]
+type = "legacy"
+url = "https://download.pytorch.org/whl/cpu"
+reference = "pytorch-cpu"
+
+[[package]]
+name = "torch"
+version = "2.1.2+cu121"
+description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
+optional = false
+python-versions = ">=3.8.0"
+files = [
+    {file = "torch-2.1.2+cu121-cp310-cp310-linux_x86_64.whl", hash = "sha256:b2184b7729ef3b9b10065c074a37c1e603fd99f91e38376e25cb7ed6e1d54696"},
+    {file = "torch-2.1.2+cu121-cp310-cp310-win_amd64.whl", hash = "sha256:9925143dece0e63c5404a72d59eb668ef78795418e96b576f94d75dcea6030b9"},
+    {file = "torch-2.1.2+cu121-cp311-cp311-linux_x86_64.whl", hash = "sha256:ca05cae9334504d1903e16c50ddf045329a859d5b1a27ed2dc1d58ed066df6fa"},
+    {file = "torch-2.1.2+cu121-cp311-cp311-win_amd64.whl", hash = "sha256:c92e9c559a82466fc5989f648807d2c0215bcce09b97ad7a20d038b686783229"},
+    {file = "torch-2.1.2+cu121-cp38-cp38-linux_x86_64.whl", hash = "sha256:daa179bb558f78f2165db974a6744ec8de2ea71eb6aaf362bdae7616012c0302"},
+    {file = "torch-2.1.2+cu121-cp38-cp38-win_amd64.whl", hash = "sha256:44c31fc1e470428682e212473507116ec3afa583d6b79d92858bf3dc24b334ea"},
+    {file = "torch-2.1.2+cu121-cp39-cp39-linux_x86_64.whl", hash = "sha256:eaaf6907e3723c0ca6a91df5e01a7eef8cabec93120e9a50739f5a5f14a2aa46"},
+    {file = "torch-2.1.2+cu121-cp39-cp39-win_amd64.whl", hash = "sha256:2d287804328dfb950ae6d418c9d8561d8f379237cf0710566d80efb96b6cd744"},
 ]
 
 [package.dependencies]
@@ -3342,17 +3223,6 @@ filelock = "*"
 fsspec = "*"
 jinja2 = "*"
 networkx = "*"
-nvidia-cublas-cu12 = {version = "12.1.3.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cuda-cupti-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cuda-nvrtc-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cuda-runtime-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cudnn-cu12 = {version = "8.9.2.26", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cufft-cu12 = {version = "11.0.2.54", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-curand-cu12 = {version = "10.3.2.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cusolver-cu12 = {version = "11.4.5.107", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-cusparse-cu12 = {version = "12.1.0.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-nccl-cu12 = {version = "2.18.1", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
-nvidia-nvtx-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 sympy = "*"
 triton = {version = "2.1.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 typing-extensions = "*"
@@ -3361,6 +3231,11 @@ typing-extensions = "*"
 dynamo = ["jinja2"]
 opt-einsum = ["opt-einsum (>=3.3)"]
 
+[package.source]
+type = "legacy"
+url = "https://download.pytorch.org/whl/cu121"
+reference = "pytorch-cu121"
+
 [[package]]
 name = "torchvision"
 version = "0.16.2"
@@ -3687,7 +3562,10 @@ files = [
     {file = "wrapt-1.14.1.tar.gz", hash = "sha256:380a85cf89e0e69b7cfbe2ea9f765f004ff419f34194018a6827ac0e3edfed4d"},
 ]
 
+[extras]
+cuda = []
+
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10, <3.12"
-content-hash = "cca966219019e985c9e58093a7a96313b1f521675a829f8d74fc79b89729b6ef"
+content-hash = "7a4791f8d500179d0472f176218cafb6a972038997fd3abcfadc751ba0eade3b"
diff --git a/pyproject.toml b/pyproject.toml
index a4f33c7..ad77d13 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -21,11 +21,11 @@ ultralytics = "^8.0.190"
 hjson = "^3.1.0"
 numpy = "^1.23.2"
 
-# https://github.com/python-poetry/poetry/issues/6409
-torch = ">=2.0.0, !=2.0.1, !=2.1.0"
+# https://github.com/python-poetry/poetry/issues/6409#issuecomment-1911735833
+torch = {version = "^2.1.2", source = "pytorch-cpu", markers = "extra!='cuda'" }
 
 # https://stackoverflow.com/a/76477590/18270659
-# https://discuss.tensorflow.org/t/tensorflow-io-gcs-filesystem-with-windows/18849/4
+# https://discfuss.tensorflow.org/t/tensorflow-io-gcs-filesystem-with-windows/18849/4
 # Might be able to remove this version constraint later
 # Working versions:
 # Python version 3.10.12 and 3.10.5 both work
@@ -38,6 +38,25 @@ tensorflow = {version = "^2.14.0", extras = ["and-cuda"]}
 
 deepface = "^0.0.79"
 
+[tool.poetry.group.remote]
+optional = true
+
+[tool.poetry.group.remote.dependencies]
+torch = {version = "^2.1.2", source = "pytorch-cu121", markers = "extra=='cuda'"}
+
+[tool.poetry.extras]
+cuda = []
+
+[[tool.poetry.source]]
+name = "pytorch-cpu"
+url = "https://download.pytorch.org/whl/cpu"
+priority = "explicit"
+
+[[tool.poetry.source]]
+name = "pytorch-cu121"
+url = "https://download.pytorch.org/whl/cu121"
+priority = "explicit"
+
 [tool.poetry.group.dev.dependencies]
 black = "^23.9.1"
 ruff = "^0.0.291"

From 401c5cee166a1ddec80244e62371212a99913383 Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Sat, 10 Feb 2024 21:48:26 -0600
Subject: [PATCH 08/18] Don't install TensorFlow with `and-cuda`

Most likely, this will prevent the GPU from being used by Deepface.
Thus, the optimal solution would be to do something similar to Torch where the GPU capability is optional.
---
 poetry.lock    | 166 ++++++-------------------------------------------
 pyproject.toml |   5 +-
 2 files changed, 22 insertions(+), 149 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 4877303..0e79ba9 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1797,120 +1797,6 @@ files = [
     {file = "numpy-1.26.2.tar.gz", hash = "sha256:f65738447676ab5777f11e6bbbdb8ce11b785e105f690bc45966574816b6d3ea"},
 ]
 
-[[package]]
-name = "nvidia-cublas-cu11"
-version = "11.11.3.6"
-description = "CUBLAS native runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cublas_cu11-11.11.3.6-py3-none-manylinux1_x86_64.whl", hash = "sha256:39fb40e8f486dd8a2ddb8fdeefe1d5b28f5b99df01c87ab3676f057a74a5a6f3"},
-    {file = "nvidia_cublas_cu11-11.11.3.6-py3-none-win_amd64.whl", hash = "sha256:6ab12b1302bef8ac1ff4414edd1c059e57f4833abef9151683fb8f4de25900be"},
-]
-
-[[package]]
-name = "nvidia-cuda-cupti-cu11"
-version = "11.8.87"
-description = "CUDA profiling tools runtime libs."
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cuda_cupti_cu11-11.8.87-py3-none-manylinux1_x86_64.whl", hash = "sha256:0e50c707df56c75a2c0703dc6b886f3c97a22f37d6f63839f75b7418ba672a8d"},
-    {file = "nvidia_cuda_cupti_cu11-11.8.87-py3-none-win_amd64.whl", hash = "sha256:4332d8550ad5f5b673f98d08e4e4f82030cb604c66d8d5ee919399ea01312e58"},
-]
-
-[[package]]
-name = "nvidia-cuda-nvcc-cu11"
-version = "11.8.89"
-description = "CUDA nvcc"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cuda_nvcc_cu11-11.8.89-py3-none-manylinux1_x86_64.whl", hash = "sha256:3e25894debe6ce87e6dbb99b2311fba6f56c1b647daae2c4e5de537dc5d88876"},
-    {file = "nvidia_cuda_nvcc_cu11-11.8.89-py3-none-win_amd64.whl", hash = "sha256:bcfb622d2449982812eb0fa43b3de0593e877edd33790f423a228ed1be62378c"},
-]
-
-[[package]]
-name = "nvidia-cuda-runtime-cu11"
-version = "11.8.89"
-description = "CUDA Runtime native Libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cuda_runtime_cu11-11.8.89-py3-none-manylinux1_x86_64.whl", hash = "sha256:f587bd726eb2f7612cf77ce38a2c1e65cf23251ff49437f6161ce0d647f64f7c"},
-    {file = "nvidia_cuda_runtime_cu11-11.8.89-py3-none-win_amd64.whl", hash = "sha256:f60c9fdaed8065b38de8097867240efc5556a8a710007146daeb9082334a6e63"},
-]
-
-[[package]]
-name = "nvidia-cudnn-cu11"
-version = "8.7.0.84"
-description = "cuDNN runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cudnn_cu11-8.7.0.84-py3-none-manylinux1_x86_64.whl", hash = "sha256:b3e062498fbbb1c1930435a6a454c1b41c903e1e65b7063bd2b4021e8285408e"},
-]
-
-[package.dependencies]
-nvidia-cublas-cu11 = "*"
-
-[[package]]
-name = "nvidia-cufft-cu11"
-version = "10.9.0.58"
-description = "CUFFT native runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cufft_cu11-10.9.0.58-py3-none-manylinux1_x86_64.whl", hash = "sha256:222f9da70c80384632fd6035e4c3f16762d64ea7a843829cb278f98b3cb7dd81"},
-    {file = "nvidia_cufft_cu11-10.9.0.58-py3-none-win_amd64.whl", hash = "sha256:c4d316f17c745ec9c728e30409612eaf77a8404c3733cdf6c9c1569634d1ca03"},
-]
-
-[[package]]
-name = "nvidia-curand-cu11"
-version = "10.3.0.86"
-description = "CURAND native runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_curand_cu11-10.3.0.86-py3-none-manylinux1_x86_64.whl", hash = "sha256:ac439548c88580269a1eb6aeb602a5aed32f0dbb20809a31d9ed7d01d77f6bf5"},
-    {file = "nvidia_curand_cu11-10.3.0.86-py3-none-win_amd64.whl", hash = "sha256:8fa8365065fc3e3760d7437b08f164a6bcf8f7124f3b544d2463ded01e6bdc70"},
-]
-
-[[package]]
-name = "nvidia-cusolver-cu11"
-version = "11.4.1.48"
-description = "CUDA solver native runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cusolver_cu11-11.4.1.48-py3-none-manylinux1_x86_64.whl", hash = "sha256:ca538f545645b7e6629140786d3127fe067b3d5a085bd794cde5bfe877c8926f"},
-    {file = "nvidia_cusolver_cu11-11.4.1.48-py3-none-win_amd64.whl", hash = "sha256:7efe43b113495a64e2cf9a0b4365bd53b0a82afb2e2cf91e9f993c9ef5e69ee8"},
-]
-
-[package.dependencies]
-nvidia-cublas-cu11 = "*"
-
-[[package]]
-name = "nvidia-cusparse-cu11"
-version = "11.7.5.86"
-description = "CUSPARSE native runtime libraries"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_cusparse_cu11-11.7.5.86-py3-none-manylinux1_x86_64.whl", hash = "sha256:4ae709fe78d3f23f60acaba8c54b8ad556cf16ca486e0cc1aa92dca7555d2d2b"},
-    {file = "nvidia_cusparse_cu11-11.7.5.86-py3-none-win_amd64.whl", hash = "sha256:a0f6ee81cd91be606fc2f55992d06b09cd4e86d74b6ae5e8dd1631cf7f5a8706"},
-]
-
-[[package]]
-name = "nvidia-nccl-cu11"
-version = "2.16.5"
-description = "NVIDIA Collective Communication Library (NCCL) Runtime"
-optional = false
-python-versions = ">=3"
-files = [
-    {file = "nvidia_nccl_cu11-2.16.5-py3-none-manylinux1_x86_64.whl", hash = "sha256:948cc9a8c659fc6cc3456dd54844fe203519b82ae87e3e94b9818dd9d94deaad"},
-]
-
 [[package]]
 name = "oauthlib"
 version = "3.2.2"
@@ -2179,6 +2065,23 @@ files = [
 docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.1)", "sphinx-autodoc-typehints (>=1.24)"]
 test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4)", "pytest-cov (>=4.1)", "pytest-mock (>=3.11.1)"]
 
+[[package]]
+name = "prettytable"
+version = "3.9.0"
+description = "A simple Python library for easily displaying tabular data in a visually appealing ASCII table format"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "prettytable-3.9.0-py3-none-any.whl", hash = "sha256:a71292ab7769a5de274b146b276ce938786f56c31cf7cea88b6f3775d82fe8c8"},
+    {file = "prettytable-3.9.0.tar.gz", hash = "sha256:f4ed94803c23073a90620b201965e5dc0bccf1760b7a7eaf3158cab8aaffdf34"},
+]
+
+[package.dependencies]
+wcwidth = "*"
+
+[package.extras]
+tests = ["pytest", "pytest-cov", "pytest-lazy-fixture"]
+
 [[package]]
 name = "prompt-toolkit"
 version = "3.0.43"
@@ -3018,16 +2921,6 @@ keras = ">=2.14.0,<2.15"
 libclang = ">=13.0.0"
 ml-dtypes = "0.2.0"
 numpy = ">=1.23.5,<2.0.0"
-nvidia-cublas-cu11 = {version = "11.11.3.6", optional = true, markers = "extra == \"and-cuda\""}
-nvidia-cuda-cupti-cu11 = {version = "11.8.87", optional = true, markers = "extra == \"and-cuda\""}
-nvidia-cuda-nvcc-cu11 = {version = "11.8.89", optional = true, markers = "extra == \"and-cuda\""}
-nvidia-cuda-runtime-cu11 = {version = "11.8.89", optional = true, markers = "extra == \"and-cuda\""}
-nvidia-cudnn-cu11 = {version = "8.7.0.84", optional = true, markers = "extra == \"and-cuda\""}
-nvidia-cufft-cu11 = {version = "10.9.0.58", optional = true, markers = "extra == \"and-cuda\""}
-nvidia-curand-cu11 = {version = "10.3.0.86", optional = true, markers = "extra == \"and-cuda\""}
-nvidia-cusolver-cu11 = {version = "11.4.1.48", optional = true, markers = "extra == \"and-cuda\""}
-nvidia-cusparse-cu11 = {version = "11.7.5.86", optional = true, markers = "extra == \"and-cuda\""}
-nvidia-nccl-cu11 = {version = "2.16.5", optional = true, markers = "extra == \"and-cuda\""}
 opt-einsum = ">=2.3.2"
 packaging = "*"
 protobuf = ">=3.20.3,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
@@ -3036,7 +2929,6 @@ six = ">=1.12.0"
 tensorboard = ">=2.14,<2.15"
 tensorflow-estimator = ">=2.14.0,<2.15"
 tensorflow-io-gcs-filesystem = ">=0.23.1"
-tensorrt = {version = "8.5.3.1", optional = true, markers = "extra == \"and-cuda\""}
 termcolor = ">=1.1.0"
 typing-extensions = ">=3.6.6"
 wrapt = ">=1.11.0,<1.15"
@@ -3089,28 +2981,6 @@ tensorflow-cpu = ["tensorflow-cpu (>=2.11.0,<2.12.0)"]
 tensorflow-gpu = ["tensorflow-gpu (>=2.11.0,<2.12.0)"]
 tensorflow-rocm = ["tensorflow-rocm (>=2.11.0,<2.12.0)"]
 
-[[package]]
-name = "tensorrt"
-version = "8.5.3.1"
-description = "A high performance deep learning inference library"
-optional = false
-python-versions = "*"
-files = [
-    {file = "tensorrt-8.5.3.1-cp310-none-manylinux_2_17_x86_64.whl", hash = "sha256:00375391073e51c1d662cc116f5472a921f27d75bb617c0195b3479633c625f3"},
-    {file = "tensorrt-8.5.3.1-cp36-none-manylinux_2_17_x86_64.whl", hash = "sha256:a88f0e0dc0d604232c4ee155f2266b179a783fc2268291701581b02ac5b90c4c"},
-    {file = "tensorrt-8.5.3.1-cp37-none-manylinux_2_17_x86_64.whl", hash = "sha256:8b7b848a995ccfa08b328c864682a6696d0f01af823af78e73e1ab54fb19d1ae"},
-    {file = "tensorrt-8.5.3.1-cp38-none-manylinux_2_17_x86_64.whl", hash = "sha256:702a122b8d533765534632d8df646497e010b24ff296c957eb5519170ffd9860"},
-    {file = "tensorrt-8.5.3.1-cp39-none-manylinux_2_17_x86_64.whl", hash = "sha256:77f6db65af8ed5f819de0487350f0f447ed14eeccde5dae83fdf1027b89df2a0"},
-]
-
-[package.dependencies]
-nvidia-cublas-cu11 = "*"
-nvidia-cuda-runtime-cu11 = "*"
-nvidia-cudnn-cu11 = "*"
-
-[package.extras]
-numpy = ["numpy"]
-
 [[package]]
 name = "termcolor"
 version = "2.4.0"
@@ -3568,4 +3438,4 @@ cuda = []
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10, <3.12"
-content-hash = "7a4791f8d500179d0472f176218cafb6a972038997fd3abcfadc751ba0eade3b"
+content-hash = "afccb2c101f032f98e359c16301255f6b1be4fdb4054264d1a7cb2ebba74717d"
diff --git a/pyproject.toml b/pyproject.toml
index ad77d13..3cc461e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -33,10 +33,13 @@ torch = {version = "^2.1.2", source = "pytorch-cpu", markers = "extra!='cuda'" }
 # cuDNN version - 8.8.1
 # Installed from Nvidia website - nvidia-cuda-toolkit is not installed, but default PopOS drivers are installed
 tensorflow-io-gcs-filesystem = "0.31.0"
-tensorflow = {version = "^2.14.0", extras = ["and-cuda"]}
+# So this wasn't working on Windows, so unless there's a way to optionally install this, we'll install it without and-cuda
+# tensorflow = {version = "^2.14.0", extras = ["and-cuda"]}
+tensorflow = {version = "^2.14.0"}
 
 
 deepface = "^0.0.79"
+prettytable = "^3.9.0"
 
 [tool.poetry.group.remote]
 optional = true

From 1a09004e3fd7852e989ed67dae97f51f3b1723e6 Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Sun, 11 Feb 2024 14:27:05 -0600
Subject: [PATCH 09/18] Made GPU capability toggleable

---
 README.md                 |  1 +
 pyproject.toml            | 12 +++++++-----
 wyzely_detect/__main__.py |  2 +-
 3 files changed, 9 insertions(+), 6 deletions(-)

diff --git a/README.md b/README.md
index b858d52..1fe061f 100644
--- a/README.md
+++ b/README.md
@@ -49,6 +49,7 @@ This assumes you have Python 3.10 or 3.11 installed
 
 #### Poetry  
 1. `poetry install`  
+    a. For GPU support, use `poetry install -E cuda --with gpu`
 2. `poetry run -- wyzely-detect`  
 ### Configuration  
 The following are some basic CLI options. Most flags have environment variable equivalents which can be helpful when using Docker. 
diff --git a/pyproject.toml b/pyproject.toml
index 3cc461e..7da2d9b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -22,6 +22,7 @@ hjson = "^3.1.0"
 numpy = "^1.23.2"
 
 # https://github.com/python-poetry/poetry/issues/6409#issuecomment-1911735833
+# To install with GPU, use poetry install -E cuda --with gpu
 torch = {version = "^2.1.2", source = "pytorch-cpu", markers = "extra!='cuda'" }
 
 # https://stackoverflow.com/a/76477590/18270659
@@ -33,21 +34,22 @@ torch = {version = "^2.1.2", source = "pytorch-cpu", markers = "extra!='cuda'" }
 # cuDNN version - 8.8.1
 # Installed from Nvidia website - nvidia-cuda-toolkit is not installed, but default PopOS drivers are installed
 tensorflow-io-gcs-filesystem = "0.31.0"
-# So this wasn't working on Windows, so unless there's a way to optionally install this, we'll install it without and-cuda
-# tensorflow = {version = "^2.14.0", extras = ["and-cuda"]}
-tensorflow = {version = "^2.14.0"}
+tensorflow = {version = "^2.14.0", markers = "extra!='cuda'"}
 
 
 deepface = "^0.0.79"
 prettytable = "^3.9.0"
 
-[tool.poetry.group.remote]
+
+[tool.poetry.group.gpu]
 optional = true
 
-[tool.poetry.group.remote.dependencies]
+[tool.poetry.group.gpu.dependencies]
 torch = {version = "^2.1.2", source = "pytorch-cu121", markers = "extra=='cuda'"}
+tensorflow = {version = "^2.14.0", extras = ["and-cuda"], markers = "extra=='cuda'"}
 
 [tool.poetry.extras]
+# Might be better to rename this to nocpu since it's more accurate
 cuda = []
 
 [[tool.poetry.source]]
diff --git a/wyzely_detect/__main__.py b/wyzely_detect/__main__.py
index 19ecf3b..5debc7b 100644
--- a/wyzely_detect/__main__.py
+++ b/wyzely_detect/__main__.py
@@ -2,7 +2,7 @@
 from pathlib import Path
 import cv2
 
-from PrettyTable import PrettyTable
+from prettytable import PrettyTable
 
 # import hjson as json
 import torch

From 494708a37664a6b44642c3595ec2fb9b97a36886 Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Sun, 11 Feb 2024 15:41:46 -0600
Subject: [PATCH 10/18] Supress TensorFlow warnings; update dependencies

Also use PrettyTable to list source resolution
---
 poetry.lock                  | 1344 +++++++++++++++++++---------------
 pyproject.toml               |    4 +-
 wyzely_detect/__main__.py    |   28 +-
 wyzely_detect/utils/utils.py |    9 +-
 4 files changed, 791 insertions(+), 594 deletions(-)

diff --git a/poetry.lock b/poetry.lock
index 0e79ba9..e8743f9 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2,13 +2,13 @@
 
 [[package]]
 name = "absl-py"
-version = "2.0.0"
+version = "2.1.0"
 description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "absl-py-2.0.0.tar.gz", hash = "sha256:d9690211c5fcfefcdd1a45470ac2b5c5acd45241c3af71eed96bc5441746c0d5"},
-    {file = "absl_py-2.0.0-py3-none-any.whl", hash = "sha256:9a28abb62774ae4e8edbe2dd4c49ffcd45a6a848952a5eccc6a49f3f0fc1e2f3"},
+    {file = "absl-py-2.1.0.tar.gz", hash = "sha256:7820790efbb316739cde8b4e19357243fc3608a152024288513dd968d7d959ff"},
+    {file = "absl_py-2.1.0-py3-none-any.whl", hash = "sha256:526a04eadab8b4ee719ce68f204172ead1027549089702d99b9059f129ff1308"},
 ]
 
 [[package]]
@@ -35,13 +35,13 @@ trio = ["trio (>=0.23)"]
 
 [[package]]
 name = "appnope"
-version = "0.1.3"
+version = "0.1.4"
 description = "Disable App Nap on macOS >= 10.9"
 optional = false
-python-versions = "*"
+python-versions = ">=3.6"
 files = [
-    {file = "appnope-0.1.3-py2.py3-none-any.whl", hash = "sha256:265a455292d0bd8a72453494fa24df5a11eb18373a60c7c0430889f22548605e"},
-    {file = "appnope-0.1.3.tar.gz", hash = "sha256:02bd91c4de869fbb1e1c50aafc4098827a7a54ab2f39d9dcba6c9547ed920e24"},
+    {file = "appnope-0.1.4-py2.py3-none-any.whl", hash = "sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c"},
+    {file = "appnope-0.1.4.tar.gz", hash = "sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee"},
 ]
 
 [[package]]
@@ -98,19 +98,22 @@ tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "p
 
 [[package]]
 name = "beautifulsoup4"
-version = "4.12.2"
+version = "4.12.3"
 description = "Screen-scraping library"
 optional = false
 python-versions = ">=3.6.0"
 files = [
-    {file = "beautifulsoup4-4.12.2-py3-none-any.whl", hash = "sha256:bd2520ca0d9d7d12694a53d44ac482d181b4ec1888909b035a3dbf40d0f57d4a"},
-    {file = "beautifulsoup4-4.12.2.tar.gz", hash = "sha256:492bbc69dca35d12daac71c4db1bfff0c876c00ef4a2ffacce226d4638eb72da"},
+    {file = "beautifulsoup4-4.12.3-py3-none-any.whl", hash = "sha256:b80878c9f40111313e55da8ba20bdba06d8fa3969fc68304167741bbf9e082ed"},
+    {file = "beautifulsoup4-4.12.3.tar.gz", hash = "sha256:74e3d1928edc070d21748185c46e3fb33490f22f52a3addee9aee0f4f7781051"},
 ]
 
 [package.dependencies]
 soupsieve = ">1.2"
 
 [package.extras]
+cchardet = ["cchardet"]
+chardet = ["chardet"]
+charset-normalizer = ["charset-normalizer"]
 html5lib = ["html5lib"]
 lxml = ["lxml"]
 
@@ -202,13 +205,13 @@ files = [
 
 [[package]]
 name = "certifi"
-version = "2023.11.17"
+version = "2024.2.2"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "certifi-2023.11.17-py3-none-any.whl", hash = "sha256:e036ab49d5b79556f99cfc2d9320b34cfbe5be05c5871b51de9329f0603b0474"},
-    {file = "certifi-2023.11.17.tar.gz", hash = "sha256:9b469f3a900bf28dc19b8cfbf8019bf47f7fdd1a65a1d4ffb98fc14166beb4d1"},
+    {file = "certifi-2024.2.2-py3-none-any.whl", hash = "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"},
+    {file = "certifi-2024.2.2.tar.gz", hash = "sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f"},
 ]
 
 [[package]]
@@ -401,13 +404,13 @@ files = [
 
 [[package]]
 name = "comm"
-version = "0.2.0"
+version = "0.2.1"
 description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "comm-0.2.0-py3-none-any.whl", hash = "sha256:2da8d9ebb8dd7bfc247adaff99f24dce705638a8042b85cb995066793e391001"},
-    {file = "comm-0.2.0.tar.gz", hash = "sha256:a517ea2ca28931c7007a7a99c562a0fa5883cfb48963140cf642c41c948498be"},
+    {file = "comm-0.2.1-py3-none-any.whl", hash = "sha256:87928485c0dfc0e7976fd89fc1e187023cf587e7c353e4a9b417555b44adf021"},
+    {file = "comm-0.2.1.tar.gz", hash = "sha256:0bc91edae1344d39d3661dcbc36937181fdaddb304790458f8b044dbc064b89a"},
 ]
 
 [package.dependencies]
@@ -496,29 +499,33 @@ tests = ["pytest", "pytest-cov", "pytest-xdist"]
 
 [[package]]
 name = "debugpy"
-version = "1.8.0"
+version = "1.8.1"
 description = "An implementation of the Debug Adapter Protocol for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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-    {file = "debugpy-1.8.0-cp310-cp310-win_amd64.whl", hash = "sha256:5d9de202f5d42e62f932507ee8b21e30d49aae7e46d5b1dd5c908db1d7068637"},
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+    {file = "debugpy-1.8.1.zip", hash = "sha256:f696d6be15be87aef621917585f9bb94b1dc9e8aced570db1b8a6fc14e8f9b42"},
 ]
 
 [[package]]
@@ -643,13 +650,13 @@ termcolor = "*"
 
 [[package]]
 name = "flask"
-version = "3.0.0"
+version = "3.0.2"
 description = "A simple framework for building complex web applications."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "flask-3.0.0-py3-none-any.whl", hash = "sha256:21128f47e4e3b9d597a3e8521a329bf56909b690fcc3fa3e477725aa81367638"},
-    {file = "flask-3.0.0.tar.gz", hash = "sha256:cfadcdb638b609361d29ec22360d6070a77d7463dcb3ab08d2c2f2f168845f58"},
+    {file = "flask-3.0.2-py3-none-any.whl", hash = "sha256:3232e0e9c850d781933cf0207523d1ece087eb8d87b23777ae38456e2fbe7c6e"},
+    {file = "flask-3.0.2.tar.gz", hash = "sha256:822c03f4b799204250a7ee84b1eddc40665395333973dfb9deebfe425fefcb7d"},
 ]
 
 [package.dependencies]
@@ -676,60 +683,60 @@ files = [
 
 [[package]]
 name = "fonttools"
-version = "4.47.0"
+version = "4.48.1"
 description = "Tools to manipulate font files"
 optional = false
 python-versions = ">=3.8"
 files = [
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 graphite = ["lz4 (>=1.7.4.2)"]
 interpolatable = ["munkres", "pycairo", "scipy"]
-lxml = ["lxml (>=4.0,<5)"]
+lxml = ["lxml (>=4.0)"]
 pathops = ["skia-pathops (>=0.5.0)"]
 plot = ["matplotlib"]
 repacker = ["uharfbuzz (>=0.23.0)"]
@@ -741,13 +748,13 @@ woff = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "zopfli (>=0.1.4)"]
 
 [[package]]
 name = "fsspec"
-version = "2023.12.2"
+version = "2024.2.0"
 description = "File-system specification"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.extras]
@@ -765,7 +772,7 @@ github = ["requests"]
 gs = ["gcsfs"]
 gui = ["panel"]
 hdfs = ["pyarrow (>=1)"]
-http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "requests"]
+http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)"]
 libarchive = ["libarchive-c"]
 oci = ["ocifs"]
 s3 = ["s3fs"]
@@ -787,31 +794,33 @@ files = [
 
 [[package]]
 name = "gdown"
-version = "4.7.1"
-description = "Google Drive direct download of big files."
+version = "5.1.0"
+description = "Google Drive Public File/Folder Downloader"
 optional = false
-python-versions = "*"
+python-versions = ">=3.8"
 files = [
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 [package.dependencies]
 beautifulsoup4 = "*"
 filelock = "*"
 requests = {version = "*", extras = ["socks"]}
-six = "*"
 tqdm = "*"
 
+[package.extras]
+test = ["build", "mypy", "pytest", "pytest-xdist", "ruff", "twine", "types-requests"]
+
 [[package]]
 name = "google-auth"
-version = "2.25.2"
+version = "2.27.0"
 description = "Google Authentication Library"
 optional = false
 python-versions = ">=3.7"
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 ]
 
 [package.dependencies]
@@ -861,69 +870,69 @@ six = "*"
 
 [[package]]
 name = "grpcio"
-version = "1.60.0"
+version = "1.60.1"
 description = "HTTP/2-based RPC framework"
 optional = false
 python-versions = ">=3.7"
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 [package.extras]
-protobuf = ["grpcio-tools (>=1.60.0)"]
+protobuf = ["grpcio-tools (>=1.60.1)"]
 
 [[package]]
 name = "gunicorn"
@@ -1062,13 +1071,13 @@ files = [
 
 [[package]]
 name = "ipykernel"
-version = "6.28.0"
+version = "6.29.2"
 description = "IPython Kernel for Jupyter"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
@@ -1091,17 +1100,17 @@ cov = ["coverage[toml]", "curio", "matplotlib", "pytest-cov", "trio"]
 docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "trio"]
 pyqt5 = ["pyqt5"]
 pyside6 = ["pyside6"]
-test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio", "pytest-cov", "pytest-timeout"]
+test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (==0.23.4)", "pytest-cov", "pytest-timeout"]
 
 [[package]]
 name = "ipython"
-version = "8.19.0"
+version = "8.21.0"
 description = "IPython: Productive Interactive Computing"
 optional = false
 python-versions = ">=3.10"
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 ]
 
 [package.dependencies]
@@ -1117,17 +1126,17 @@ stack-data = "*"
 traitlets = ">=5"
 
 [package.extras]
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+all = ["black", "curio", "docrepr", "exceptiongroup", "ipykernel", "ipyparallel", "ipywidgets", "matplotlib", "matplotlib (!=3.2.0)", "nbconvert", "nbformat", "notebook", "numpy (>=1.23)", "pandas", "pickleshare", "pytest (<8)", "pytest-asyncio (<0.22)", "qtconsole", "setuptools (>=18.5)", "sphinx (>=1.3)", "sphinx-rtd-theme", "stack-data", "testpath", "trio", "typing-extensions"]
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 notebook = ["ipywidgets", "notebook"]
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 [[package]]
 name = "itsdangerous"
@@ -1161,13 +1170,13 @@ testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
 
 [[package]]
 name = "jinja2"
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+version = "3.1.3"
 description = "A very fast and expressive template engine."
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 [package.dependencies]
@@ -1178,13 +1187,13 @@ i18n = ["Babel (>=2.7)"]
 
 [[package]]
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+version = "4.21.1"
 description = "An implementation of JSON Schema validation for Python"
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 [package.dependencies]
@@ -1235,13 +1244,13 @@ test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pyt
 
 [[package]]
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 [package.dependencies]
@@ -1410,13 +1419,13 @@ files = [
 
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 [package.extras]
@@ -1425,71 +1434,71 @@ testing = ["coverage", "pyyaml"]
 
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@@ -1667,13 +1676,13 @@ test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=
 
 [[package]]
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 [package.dependencies]
@@ -1725,13 +1734,13 @@ test = ["pep440", "pre-commit", "pytest", "testpath"]
 
 [[package]]
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 [[package]]
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 description = "Fundamental package for array computing in Python"
 optional = false
 python-versions = ">=3.9"
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 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
-tzdata = ">=2022.1"
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-xml = ["lxml (>=4.8.0)"]
+xml = ["lxml (>=4.9.2)"]
 
 [[package]]
 name = "pandocfilters"
-version = "1.5.0"
+version = "1.5.1"
 description = "Utilities for writing pandoc filters in python"
 optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
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 ]
 
 [[package]]
@@ -1985,85 +2112,103 @@ ptyprocess = ">=0.5"
 
 [[package]]
 name = "pillow"
-version = "10.1.0"
+version = "10.2.0"
 description = "Python Imaging Library (Fork)"
 optional = false
 python-versions = ">=3.8"
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+version = "2024.1"
 description = "World timezone definitions, modern and historical"
 optional = false
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 [[package]]
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-version = "0.32.0"
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 dev = ["click", "cython-lint (>=0.12.2)", "doit (>=0.36.0)", "mypy", "pycodestyle", "pydevtool", "rich-click", "ruff", "types-psutil", "typing_extensions"]
 doc = ["jupytext", "matplotlib (>2)", "myst-nb", "numpydoc", "pooch", "pydata-sphinx-theme (==0.9.0)", "sphinx (!=4.1.0)", "sphinx-design (>=0.2.0)"]
-test = ["asv", "gmpy2", "mpmath", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
+test = ["asv", "gmpy2", "hypothesis", "mpmath", "pooch", "pytest", "pytest-cov", "pytest-timeout", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
 
 [[package]]
 name = "seaborn"
-version = "0.13.1"
+version = "0.13.2"
 description = "Statistical data visualization"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "seaborn-0.13.1-py3-none-any.whl", hash = "sha256:6baa69b6d1169ae59037971491c450c0b73332b42bd4b23570b62a546bc61cb8"},
-    {file = "seaborn-0.13.1.tar.gz", hash = "sha256:bfad65e9c5989e5e1897e61bdbd2f22e62455940ca76fd49eca3ed69345b9179"},
+    {file = "seaborn-0.13.2-py3-none-any.whl", hash = "sha256:636f8336facf092165e27924f223d3c62ca560b1f2bb5dff7ab7fad265361987"},
+    {file = "seaborn-0.13.2.tar.gz", hash = "sha256:93e60a40988f4d65e9f4885df477e2fdaff6b73a9ded434c1ab356dd57eefff7"},
 ]
 
 [package.dependencies]
@@ -2921,6 +3066,16 @@ keras = ">=2.14.0,<2.15"
 libclang = ">=13.0.0"
 ml-dtypes = "0.2.0"
 numpy = ">=1.23.5,<2.0.0"
+nvidia-cublas-cu11 = {version = "11.11.3.6", optional = true, markers = "extra == \"and-cuda\""}
+nvidia-cuda-cupti-cu11 = {version = "11.8.87", optional = true, markers = "extra == \"and-cuda\""}
+nvidia-cuda-nvcc-cu11 = {version = "11.8.89", optional = true, markers = "extra == \"and-cuda\""}
+nvidia-cuda-runtime-cu11 = {version = "11.8.89", optional = true, markers = "extra == \"and-cuda\""}
+nvidia-cudnn-cu11 = {version = "8.7.0.84", optional = true, markers = "extra == \"and-cuda\""}
+nvidia-cufft-cu11 = {version = "10.9.0.58", optional = true, markers = "extra == \"and-cuda\""}
+nvidia-curand-cu11 = {version = "10.3.0.86", optional = true, markers = "extra == \"and-cuda\""}
+nvidia-cusolver-cu11 = {version = "11.4.1.48", optional = true, markers = "extra == \"and-cuda\""}
+nvidia-cusparse-cu11 = {version = "11.7.5.86", optional = true, markers = "extra == \"and-cuda\""}
+nvidia-nccl-cu11 = {version = "2.16.5", optional = true, markers = "extra == \"and-cuda\""}
 opt-einsum = ">=2.3.2"
 packaging = "*"
 protobuf = ">=3.20.3,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
@@ -2929,6 +3084,7 @@ six = ">=1.12.0"
 tensorboard = ">=2.14,<2.15"
 tensorflow-estimator = ">=2.14.0,<2.15"
 tensorflow-io-gcs-filesystem = ">=0.23.1"
+tensorrt = {version = "8.5.3.1", optional = true, markers = "extra == \"and-cuda\""}
 termcolor = ">=1.1.0"
 typing-extensions = ">=3.6.6"
 wrapt = ">=1.11.0,<1.15"
@@ -2981,6 +3137,28 @@ tensorflow-cpu = ["tensorflow-cpu (>=2.11.0,<2.12.0)"]
 tensorflow-gpu = ["tensorflow-gpu (>=2.11.0,<2.12.0)"]
 tensorflow-rocm = ["tensorflow-rocm (>=2.11.0,<2.12.0)"]
 
+[[package]]
+name = "tensorrt"
+version = "8.5.3.1"
+description = "A high performance deep learning inference library"
+optional = true
+python-versions = "*"
+files = [
+    {file = "tensorrt-8.5.3.1-cp310-none-manylinux_2_17_x86_64.whl", hash = "sha256:00375391073e51c1d662cc116f5472a921f27d75bb617c0195b3479633c625f3"},
+    {file = "tensorrt-8.5.3.1-cp36-none-manylinux_2_17_x86_64.whl", hash = "sha256:a88f0e0dc0d604232c4ee155f2266b179a783fc2268291701581b02ac5b90c4c"},
+    {file = "tensorrt-8.5.3.1-cp37-none-manylinux_2_17_x86_64.whl", hash = "sha256:8b7b848a995ccfa08b328c864682a6696d0f01af823af78e73e1ab54fb19d1ae"},
+    {file = "tensorrt-8.5.3.1-cp38-none-manylinux_2_17_x86_64.whl", hash = "sha256:702a122b8d533765534632d8df646497e010b24ff296c957eb5519170ffd9860"},
+    {file = "tensorrt-8.5.3.1-cp39-none-manylinux_2_17_x86_64.whl", hash = "sha256:77f6db65af8ed5f819de0487350f0f447ed14eeccde5dae83fdf1027b89df2a0"},
+]
+
+[package.dependencies]
+nvidia-cublas-cu11 = "*"
+nvidia-cuda-runtime-cu11 = "*"
+nvidia-cudnn-cu11 = "*"
+
+[package.extras]
+numpy = ["numpy"]
+
 [[package]]
 name = "termcolor"
 version = "2.4.0"
@@ -3166,13 +3344,13 @@ files = [
 
 [[package]]
 name = "tqdm"
-version = "4.66.1"
+version = "4.66.2"
 description = "Fast, Extensible Progress Meter"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "tqdm-4.66.1-py3-none-any.whl", hash = "sha256:d302b3c5b53d47bce91fea46679d9c3c6508cf6332229aa1e7d8653723793386"},
-    {file = "tqdm-4.66.1.tar.gz", hash = "sha256:d88e651f9db8d8551a62556d3cff9e3034274ca5d66e93197cf2490e2dcb69c7"},
+    {file = "tqdm-4.66.2-py3-none-any.whl", hash = "sha256:1ee4f8a893eb9bef51c6e35730cebf234d5d0b6bd112b0271e10ed7c24a02bd9"},
+    {file = "tqdm-4.66.2.tar.gz", hash = "sha256:6cd52cdf0fef0e0f543299cfc96fec90d7b8a7e88745f411ec33eb44d5ed3531"},
 ]
 
 [package.dependencies]
@@ -3186,13 +3364,13 @@ telegram = ["requests"]
 
 [[package]]
 name = "traitlets"
-version = "5.14.0"
+version = "5.14.1"
 description = "Traitlets Python configuration system"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "traitlets-5.14.0-py3-none-any.whl", hash = "sha256:f14949d23829023013c47df20b4a76ccd1a85effb786dc060f34de7948361b33"},
-    {file = "traitlets-5.14.0.tar.gz", hash = "sha256:fcdaa8ac49c04dfa0ed3ee3384ef6dfdb5d6f3741502be247279407679296772"},
+    {file = "traitlets-5.14.1-py3-none-any.whl", hash = "sha256:2e5a030e6eff91737c643231bfcf04a65b0132078dad75e4936700b213652e74"},
+    {file = "traitlets-5.14.1.tar.gz", hash = "sha256:8585105b371a04b8316a43d5ce29c098575c2e477850b62b848b964f1444527e"},
 ]
 
 [package.extras]
@@ -3248,13 +3426,13 @@ files = [
 
 [[package]]
 name = "ultralytics"
-version = "8.0.231"
+version = "8.1.11"
 description = "Ultralytics YOLOv8 for SOTA object detection, multi-object tracking, instance segmentation, pose estimation and image classification."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "ultralytics-8.0.231-py3-none-any.whl", hash = "sha256:bad23d0a13a466bb4839740c7f07d756e65934081d05d3a4f7f0676fc84657dc"},
-    {file = "ultralytics-8.0.231.tar.gz", hash = "sha256:f7647c143e516f7e63b625f10896bf82a8d49cf1ba5e920a2863f9f40204b4c6"},
+    {file = "ultralytics-8.1.11-py3-none-any.whl", hash = "sha256:38b4e45d344f0a2b1d2ce97d89723527a0059d3c7f7d0cdc404bc743ca5c626a"},
+    {file = "ultralytics-8.1.11.tar.gz", hash = "sha256:7e7e53598a3766a0c0407aaf7a90aff45c60d6aee21ecf744de71be6421d0e72"},
 ]
 
 [package.dependencies]
@@ -3275,36 +3453,38 @@ torchvision = ">=0.9.0"
 tqdm = ">=4.64.0"
 
 [package.extras]
-dev = ["check-manifest", "coverage[toml]", "ipython", "mkdocs-material", "mkdocs-redirects", "mkdocs-ultralytics-plugin (>=0.0.34)", "mkdocstrings[python]", "pre-commit", "pytest", "pytest-cov"]
-export = ["coremltools (>=7.0)", "jax (<=0.4.21)", "jaxlib (<=0.4.21)", "onnx (>=1.12.0)", "openvino-dev (>=2023.0)", "tensorflow (<=2.13.1)", "tensorflowjs (>=3.9.0)"]
-extra = ["albumentations (>=1.0.3)", "ipython", "pycocotools (>=2.0.6)"]
+dev = ["check-manifest", "coverage[toml]", "ipython", "mkdocs-jupyter", "mkdocs-material", "mkdocs-redirects", "mkdocs-ultralytics-plugin (>=0.0.43)", "mkdocstrings[python]", "pre-commit", "pytest", "pytest-cov"]
+explorer = ["duckdb", "lancedb", "streamlit"]
+export = ["coremltools (>=7.0)", "onnx (>=1.12.0)", "openvino-dev (>=2023.0)", "tensorflow (<=2.13.1)", "tensorflowjs (>=3.9.0)"]
+extra = ["albumentations (>=1.0.3)", "hub-sdk (>=0.0.2)", "ipython", "pycocotools (>=2.0.6)"]
 logging = ["comet", "dvclive (>=2.12.0)", "tensorboard (>=2.13.0)"]
 
 [[package]]
 name = "urllib3"
-version = "2.1.0"
+version = "2.2.0"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "urllib3-2.1.0-py3-none-any.whl", hash = "sha256:55901e917a5896a349ff771be919f8bd99aff50b79fe58fec595eb37bbc56bb3"},
-    {file = "urllib3-2.1.0.tar.gz", hash = "sha256:df7aa8afb0148fa78488e7899b2c59b5f4ffcfa82e6c54ccb9dd37c1d7b52d54"},
+    {file = "urllib3-2.2.0-py3-none-any.whl", hash = "sha256:ce3711610ddce217e6d113a2732fafad960a03fd0318c91faa79481e35c11224"},
+    {file = "urllib3-2.2.0.tar.gz", hash = "sha256:051d961ad0c62a94e50ecf1af379c3aba230c66c710493493560c0c223c49f20"},
 ]
 
 [package.extras]
 brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
+h2 = ["h2 (>=4,<5)"]
 socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
 zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "wcwidth"
-version = "0.2.12"
+version = "0.2.13"
 description = "Measures the displayed width of unicode strings in a terminal"
 optional = false
 python-versions = "*"
 files = [
-    {file = "wcwidth-0.2.12-py2.py3-none-any.whl", hash = "sha256:f26ec43d96c8cbfed76a5075dac87680124fa84e0855195a6184da9c187f133c"},
-    {file = "wcwidth-0.2.12.tar.gz", hash = "sha256:f01c104efdf57971bcb756f054dd58ddec5204dd15fa31d6503ea57947d97c02"},
+    {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"},
+    {file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"},
 ]
 
 [[package]]
@@ -3438,4 +3618,4 @@ cuda = []
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10, <3.12"
-content-hash = "afccb2c101f032f98e359c16301255f6b1be4fdb4054264d1a7cb2ebba74717d"
+content-hash = "e158655385434802fc095f19c2fd22718379ecb71e0e4c1ade266f23da315bc4"
diff --git a/pyproject.toml b/pyproject.toml
index 7da2d9b..4cb31da 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -23,7 +23,7 @@ numpy = "^1.23.2"
 
 # https://github.com/python-poetry/poetry/issues/6409#issuecomment-1911735833
 # To install with GPU, use poetry install -E cuda --with gpu
-torch = {version = "^2.1.2", source = "pytorch-cpu", markers = "extra!='cuda'" }
+torch = {version = "2.1.*", source = "pytorch-cpu", markers = "extra!='cuda'" }
 
 # https://stackoverflow.com/a/76477590/18270659
 # https://discfuss.tensorflow.org/t/tensorflow-io-gcs-filesystem-with-windows/18849/4
@@ -45,7 +45,7 @@ prettytable = "^3.9.0"
 optional = true
 
 [tool.poetry.group.gpu.dependencies]
-torch = {version = "^2.1.2", source = "pytorch-cu121", markers = "extra=='cuda'"}
+torch = {version = "2.1.*", source = "pytorch-cu121", markers = "extra=='cuda'"}
 tensorflow = {version = "^2.14.0", extras = ["and-cuda"], markers = "extra=='cuda'"}
 
 [tool.poetry.extras]
diff --git a/wyzely_detect/__main__.py b/wyzely_detect/__main__.py
index 5debc7b..dc02114 100644
--- a/wyzely_detect/__main__.py
+++ b/wyzely_detect/__main__.py
@@ -1,6 +1,7 @@
 # import face_recognition
 from pathlib import Path
 import cv2
+import os
 
 from prettytable import PrettyTable
 
@@ -18,7 +19,7 @@ args = None
 def main():
     global objects_and_peoples
     global args 
-    # RUN_BY_COMPOSE = os.getenv("RUN_BY_COMPOSE") # Replace this with code to check for gpu
+
 
     args = argparser.parse_args()
 
@@ -49,7 +50,9 @@ def main():
     # Set the video capture to the appropriate source
     if not args.rtsp_url and not args.capture_device:
         print("No stream or capture device set, defaulting to capture device 0")
-        args.capture_device = [0]
+        video_sources = {
+            "devices": [cv2.VideoCapture(0)]
+        }
     else:
         video_sources = {
             "streams": [cv2.VideoCapture(url) for url in args.rtsp_url],
@@ -60,13 +63,22 @@ def main():
     # This makes it so that the video capture will only grab the most recent frame
     # However, this means that the video may be choppy
     # Only do this for streams
-    for stream in video_sources["streams"]:
-        stream.set(cv2.CAP_PROP_BUFFERSIZE, 1)
+    try:
+        for stream in video_sources["streams"]:
+            stream.set(cv2.CAP_PROP_BUFFERSIZE, 1)
+    # If there are no streams, this will throw a KeyError
+    except KeyError:
+        pass
+
+    # Print out the resolution of the video sources. Ideally, change this so the device ID/url is also printed
+    pretty_table = PrettyTable(field_names=["Source Type", "Resolution"])
+    for source_type, sources in video_sources.items():
+        for source in sources:
+            pretty_table.add_row(
+                [source_type, f"{source.get(cv2.CAP_PROP_FRAME_WIDTH)}x{source.get(cv2.CAP_PROP_FRAME_HEIGHT)}"]
+            )
+    print(pretty_table)
 
-    # Print the resolution of the video
-    print(
-        f"Video resolution: {video_capture.get(cv2.CAP_PROP_FRAME_WIDTH)}x{video_capture.get(cv2.CAP_PROP_FRAME_HEIGHT)}"  # noqa: E501
-    )
     print
     print("Beginning video capture...")
     while True:
diff --git a/wyzely_detect/utils/utils.py b/wyzely_detect/utils/utils.py
index 0a12de2..5ac48c7 100644
--- a/wyzely_detect/utils/utils.py
+++ b/wyzely_detect/utils/utils.py
@@ -1,8 +1,13 @@
 import cv2
+import os
 import numpy as np
 from pathlib import Path
-from deepface import DeepFace
-from . import notify
+# https://stackoverflow.com/a/42121886/18270659
+os.environ['TF_CPP_MIN_LOG_LEVEL']='3'
+
+
+from deepface import DeepFace # noqa: E402
+from . import notify # noqa: E402
 
 first_face_try = True
 

From 8f500e01866b09c45bedb01755a85ace2d558bdd Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Fri, 16 Feb 2024 12:34:39 -0600
Subject: [PATCH 11/18] Multiple sources can now be used Added
 `--fake-second-source` to help with debugging

---
 .vscode/launch.json             |  2 +-
 wyzely_detect/__main__.py       | 55 +++++++++++++++++++++------------
 wyzely_detect/utils/cli_args.py | 28 ++++++++++++++---
 3 files changed, 61 insertions(+), 24 deletions(-)

diff --git a/.vscode/launch.json b/.vscode/launch.json
index 5990161..6f0fe56 100644
--- a/.vscode/launch.json
+++ b/.vscode/launch.json
@@ -10,7 +10,7 @@
             "request": "launch",
             "module": "wyzely_detect",
             "args": [
-                "--run-scale", "0.25", "--view-scale", "0.5", "--no-remove-representations"
+                "--run-scale", "0.25", "--view-scale", "0.5", "--no-remove-representations", "--fake-second-source"
             ],
             "justMyCode": true
         },
diff --git a/wyzely_detect/__main__.py b/wyzely_detect/__main__.py
index dc02114..89005df 100644
--- a/wyzely_detect/__main__.py
+++ b/wyzely_detect/__main__.py
@@ -59,6 +59,17 @@ def main():
             "devices": [cv2.VideoCapture(device) for device in args.capture_device],
         }
 
+    if args.fake_second_source:
+        try:
+            video_sources["devices"].append(video_sources["devices"][0])
+        except KeyError:
+            print("No capture device to use as second source. Trying stream.")
+            try:
+                video_sources["devices"].append(video_sources["devices"][0])
+            except KeyError:
+                print("No stream to use as a second source")
+                # When the code tries to resize the nonexistent capture device 1, the program will fail
+
     # Eliminate lag by setting the buffer size to 1
     # This makes it so that the video capture will only grab the most recent frame
     # However, this means that the video may be choppy
@@ -74,6 +85,7 @@ def main():
     pretty_table = PrettyTable(field_names=["Source Type", "Resolution"])
     for source_type, sources in video_sources.items():
         for source in sources:
+            # TODO: Add check to see if resolution is 0x0, and if it is, print a warning or just fail
             pretty_table.add_row(
                 [source_type, f"{source.get(cv2.CAP_PROP_FRAME_WIDTH)}x{source.get(cv2.CAP_PROP_FRAME_HEIGHT)}"]
             )
@@ -83,31 +95,36 @@ def main():
     print("Beginning video capture...")
     while True:
         # Grab a single frame of video
-        ret, frame = video_capture.read()
+        frames = []
+        # frames = [source.read() for sources in video_sources.values() for source in sources]
+        for list_of_sources in video_sources.values():
+            frames.extend([source.read()[1] for source in list_of_sources])
+        frames_to_show = []
+        for frame in frames:
+            frames_to_show.append(utils.process_footage(
+                frame = frame,
+                run_scale = args.run_scale,
+                view_scale = args.view_scale,
 
-        frame_to_show = utils.process_footage(
-            frame = frame,
-            run_scale = args.run_scale,
-            view_scale = args.view_scale,
+                faces_directory=Path(args.faces_directory),
+                face_confidence_threshold=args.face_confidence_threshold,
+                no_remove_representations=args.no_remove_representations,
 
-            faces_directory=Path(args.faces_directory),
-            face_confidence_threshold=args.face_confidence_threshold,
-            no_remove_representations=args.no_remove_representations,
+                detection_window=args.detection_window,
+                detection_duration=args.detection_duration,
+                notification_window=args.notification_window,
 
-            detection_window=args.detection_window,
-            detection_duration=args.detection_duration,
-            notification_window=args.notification_window,
+                ntfy_url=args.ntfy_url,
 
-            ntfy_url=args.ntfy_url,
-
-            model=model,
-            detect_object=args.detect_object,
-            object_confidence_threshold=args.object_confidence_threshold,
-        )
+                model=model,
+                detect_object=args.detect_object,
+                object_confidence_threshold=args.object_confidence_threshold,
+            ))
         # Display the resulting frame
         # TODO: When multi-camera support is added, this needs to be changed to allow all feeds
         if not args.no_display:
-            cv2.imshow("Video", frame_to_show)
+            for i, frame_to_show in enumerate(frames_to_show):    
+                cv2.imshow(f"Video {i}", frame_to_show)
 
         # Hit 'q' on the keyboard to quit!
         if cv2.waitKey(1) & 0xFF == ord("q"):
@@ -115,7 +132,7 @@ def main():
 
     # Release handle to the webcam
     print("Releasing video capture")
-    video_capture.release()
+    [source.release() for sources in video_sources.values() for source in sources]
     cv2.destroyAllWindows()
 
 
diff --git a/wyzely_detect/utils/cli_args.py b/wyzely_detect/utils/cli_args.py
index 6337c76..2b9cfad 100644
--- a/wyzely_detect/utils/cli_args.py
+++ b/wyzely_detect/utils/cli_args.py
@@ -21,7 +21,7 @@ def set_argparse():
     argparser = argparse.ArgumentParser(
         prog="Wyzely Detect",
         description="Recognize faces/objects in a video stream (from a webcam or a security camera) and send notifications to your devices",  # noqa: E501
-        epilog=":)",
+        epilog="For env bool options, setting them to anything except for an empty string will enable them."
     )
 
 
@@ -69,7 +69,9 @@ def set_argparse():
     video_options.add_argument(
         "--no-display",
         default=os.environ["NO_DISPLAY"]
-        if "NO_DISPLAY" in os.environ and os.environ["NO_DISPLAY"] != ""
+        if "NO_DISPLAY" in os.environ
+        and os.environ["NO_DISPLAY"] != ""
+        and os.environ["NO_DISPLAY"].lower() != "false"
         else False,
         action="store_true",
         help="Don't display the video feed",
@@ -78,7 +80,9 @@ def set_argparse():
         '-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"] != ""
+        if "FORCE_DISABLE_TENSORFLOW_GPU" in os.environ 
+        and os.environ["FORCE_DISABLE_TENSORFLOW_GPU"] != ""
+        and os.environ["FORCE_DISABLE_TENSORFLOW_GPU"].lower() != "false"
         else False,
         action="store_true",
         help="Force disable tensorflow GPU through env since sometimes it's not worth it to install cudnn and whatnot",
@@ -146,6 +150,7 @@ def set_argparse():
         default=os.environ["NO_REMOVE_REPRESENTATIONS"]
         if "NO_REMOVE_REPRESENTATIONS" in os.environ
         and os.environ["NO_REMOVE_REPRESENTATIONS"] != ""
+        and os.environ["NO_REMOVE_REPRESENTATIONS"].lower() != "false"
         else False,
         action="store_true",
         help="Don't remove representations_<model>.pkl at the start of the program. Greatly improves startup time, but doesn't take into account changes to the faces directory since it was created",  # noqa: E501
@@ -166,12 +171,27 @@ def set_argparse():
         "--object-confidence-threshold",
         default=os.environ["OBJECT_CONFIDENCE_THRESHOLD"]
         if "OBJECT_CONFIDENCE_THRESHOLD" in os.environ
-        and os.environ["OBJECT_CONFIDENCE_THRESHOLD"] != ""
+        and os.environ["OBJECT_CONFIDENCE_THRESHOLD"] != "" 
+        # I think this should always be a str so using lower shouldn't be a problem. 
+        # Also, if the first check fails the rest shouldn't be run 
+        and os.environ["OBJECT_CONFIDENCE_THRESHOLD"].lower() != "false"
         else 0.6,
         type=float,
         help="The confidence threshold to use",
     )
 
+    debug = argparser.add_argument_group("Debug options")
+    debug.add_argument(
+        "--fake-second-source",
+        help="Duplicate the first source and use it as a second source. Capture device takes priority.",
+        action="store_true",
+        default=os.environ["FAKE_SECOND_SOURCE"]
+        if "FAKE_SECOND_SOURCE" in os.environ
+        and os.environ["FAKE_SECOND_SOURCE"] != ""
+        and os.environ["FAKE_SECOND_SOURCE"].lower() != "false"
+        else False,
+    )
+
     # return argparser
 
 

From bbcede0b3e9fd849e672b3e2f84c436ff7509522 Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Fri, 16 Feb 2024 12:45:31 -0600
Subject: [PATCH 12/18] Check if video source is valid

---
 wyzely_detect/__main__.py | 11 +++++++++--
 1 file changed, 9 insertions(+), 2 deletions(-)

diff --git a/wyzely_detect/__main__.py b/wyzely_detect/__main__.py
index 89005df..1e9a407 100644
--- a/wyzely_detect/__main__.py
+++ b/wyzely_detect/__main__.py
@@ -1,7 +1,6 @@
 # import face_recognition
 from pathlib import Path
 import cv2
-import os
 
 from prettytable import PrettyTable
 
@@ -85,7 +84,15 @@ def main():
     pretty_table = PrettyTable(field_names=["Source Type", "Resolution"])
     for source_type, sources in video_sources.items():
         for source in sources:
-            # TODO: Add check to see if resolution is 0x0, and if it is, print a warning or just fail
+            if source.get(cv2.CAP_PROP_FRAME_WIDTH) == 0 or source.get(cv2.CAP_PROP_FRAME_HEIGHT) == 0:
+                message = "Capture for a source failed as resolution is 0x0.\n"
+                if source_type == "streams":
+                    message += "Check if the stream URL is correct and if the stream is online."
+                else:
+                    message += "Check if the capture device is connected, working, and not in use by another program."
+                print(message)
+                # Maybe use os.exit() instead?
+                exit(1)
             pretty_table.add_row(
                 [source_type, f"{source.get(cv2.CAP_PROP_FRAME_WIDTH)}x{source.get(cv2.CAP_PROP_FRAME_HEIGHT)}"]
             )

From b48edef2500ddc266c8226145defa5d831a67d46 Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Fri, 16 Feb 2024 12:48:52 -0600
Subject: [PATCH 13/18] Python `3.10.12` seems to work well

---
 .python-version | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.python-version b/.python-version
index 9ac3804..939821c 100644
--- a/.python-version
+++ b/.python-version
@@ -1 +1 @@
-3.11.5
+3.10.12
\ No newline at end of file

From c7d488d9931e51e7c8633ae931b4f3e8e7ec2093 Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Fri, 16 Feb 2024 13:01:02 -0600
Subject: [PATCH 14/18] Fix various minor issues and format code

---
 wyzely_detect/__main__.py       | 69 ++++++++++++++--------------
 wyzely_detect/utils/cli_args.py | 30 ++++++-------
 wyzely_detect/utils/utils.py    | 79 +++++++++++++++------------------
 3 files changed, 86 insertions(+), 92 deletions(-)

diff --git a/wyzely_detect/__main__.py b/wyzely_detect/__main__.py
index 1e9a407..22afc0e 100644
--- a/wyzely_detect/__main__.py
+++ b/wyzely_detect/__main__.py
@@ -1,7 +1,7 @@
 # import face_recognition
 from pathlib import Path
 import cv2
-
+import sys
 from prettytable import PrettyTable
 
 # import hjson as json
@@ -17,8 +17,7 @@ args = None
 
 def main():
     global objects_and_peoples
-    global args 
-
+    global args
 
     args = argparser.parse_args()
 
@@ -26,7 +25,7 @@ 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(f"Using {torch.cuda.get_device_properties(i).name} for pytorch")
     if torch.cuda.is_available():
         torch.cuda.set_device(0)
         print("Set CUDA device")
@@ -37,9 +36,10 @@ def main():
     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')
+
+        tf.config.set_visible_devices([], "GPU")
+        if tf.config.experimental.list_logical_devices("GPU"):
+            print("GPU disabled unsuccessfully")
         else:
             print("GPU disabled successfully")
 
@@ -49,9 +49,7 @@ def main():
     # Set the video capture to the appropriate source
     if not args.rtsp_url and not args.capture_device:
         print("No stream or capture device set, defaulting to capture device 0")
-        video_sources = {
-            "devices": [cv2.VideoCapture(0)]
-        }
+        video_sources = {"devices": [cv2.VideoCapture(0)]}
     else:
         video_sources = {
             "streams": [cv2.VideoCapture(url) for url in args.rtsp_url],
@@ -84,17 +82,22 @@ def main():
     pretty_table = PrettyTable(field_names=["Source Type", "Resolution"])
     for source_type, sources in video_sources.items():
         for source in sources:
-            if source.get(cv2.CAP_PROP_FRAME_WIDTH) == 0 or source.get(cv2.CAP_PROP_FRAME_HEIGHT) == 0:
+            if (
+                source.get(cv2.CAP_PROP_FRAME_WIDTH) == 0
+                or source.get(cv2.CAP_PROP_FRAME_HEIGHT) == 0
+            ):
                 message = "Capture for a source failed as resolution is 0x0.\n"
                 if source_type == "streams":
                     message += "Check if the stream URL is correct and if the stream is online."
                 else:
                     message += "Check if the capture device is connected, working, and not in use by another program."
                 print(message)
-                # Maybe use os.exit() instead?
-                exit(1)
+                sys.exit(1)
             pretty_table.add_row(
-                [source_type, f"{source.get(cv2.CAP_PROP_FRAME_WIDTH)}x{source.get(cv2.CAP_PROP_FRAME_HEIGHT)}"]
+                [
+                    source_type,
+                    f"{source.get(cv2.CAP_PROP_FRAME_WIDTH)}x{source.get(cv2.CAP_PROP_FRAME_HEIGHT)}",
+                ]
             )
     print(pretty_table)
 
@@ -108,29 +111,27 @@ def main():
             frames.extend([source.read()[1] for source in list_of_sources])
         frames_to_show = []
         for frame in frames:
-            frames_to_show.append(utils.process_footage(
-                frame = frame,
-                run_scale = args.run_scale,
-                view_scale = args.view_scale,
-
-                faces_directory=Path(args.faces_directory),
-                face_confidence_threshold=args.face_confidence_threshold,
-                no_remove_representations=args.no_remove_representations,
-
-                detection_window=args.detection_window,
-                detection_duration=args.detection_duration,
-                notification_window=args.notification_window,
-
-                ntfy_url=args.ntfy_url,
-
-                model=model,
-                detect_object=args.detect_object,
-                object_confidence_threshold=args.object_confidence_threshold,
-            ))
+            frames_to_show.append(
+                utils.process_footage(
+                    frame=frame,
+                    run_scale=args.run_scale,
+                    view_scale=args.view_scale,
+                    faces_directory=Path(args.faces_directory),
+                    face_confidence_threshold=args.face_confidence_threshold,
+                    no_remove_representations=args.no_remove_representations,
+                    detection_window=args.detection_window,
+                    detection_duration=args.detection_duration,
+                    notification_window=args.notification_window,
+                    ntfy_url=args.ntfy_url,
+                    model=model,
+                    detect_object=args.detect_object,
+                    object_confidence_threshold=args.object_confidence_threshold,
+                )
+            )
         # Display the resulting frame
         # TODO: When multi-camera support is added, this needs to be changed to allow all feeds
         if not args.no_display:
-            for i, frame_to_show in enumerate(frames_to_show):    
+            for i, frame_to_show in enumerate(frames_to_show):
                 cv2.imshow(f"Video {i}", frame_to_show)
 
         # Hit 'q' on the keyboard to quit!
diff --git a/wyzely_detect/utils/cli_args.py b/wyzely_detect/utils/cli_args.py
index 2b9cfad..ff6904c 100644
--- a/wyzely_detect/utils/cli_args.py
+++ b/wyzely_detect/utils/cli_args.py
@@ -15,16 +15,14 @@ def set_argparse():
     else:
         print("No .env file found")
 
-
     # 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 = argparse.ArgumentParser(
         prog="Wyzely Detect",
         description="Recognize faces/objects in a video stream (from a webcam or a security camera) and send notifications to your devices",  # noqa: E501
-        epilog="For env bool options, setting them to anything except for an empty string will enable them."
+        epilog="For env bool options, setting them to anything except for an empty string will enable them.",
     )
 
-
     video_options = argparser.add_argument_group("Video Options")
     stream_source = video_options.add_mutually_exclusive_group()
     stream_source.add_argument(
@@ -32,7 +30,9 @@ def set_argparse():
         action="append",
         # If RTSP_URL is in the environment, use it, otherwise just use a blank list
         # This may cause problems down the road, but if it does, env for this can be removed
-        default=[os.environ["RTSP_URL"]] if "RTSP_URL" in os.environ and os.environ["RTSP_URL"] != "" else [],
+        default=[os.environ["RTSP_URL"]]
+        if "RTSP_URL" in os.environ and os.environ["RTSP_URL"] != ""
+        else [],
         type=str,
         help="RTSP camera URL",
     )
@@ -41,7 +41,9 @@ def set_argparse():
         action="append",
         # If CAPTURE_DEVICE is in the environment, use it, otherwise just use a blank list
         # If __main__.py detects that no capture device or remote stream is set, it will default to 0
-        default=[int(os.environ["CAPTURE_DEVICE"])] if "CAPTURE_DEVICE" in os.environ and os.environ["CAPTURE_DEVICE"] != "" else [],
+        default=[int(os.environ["CAPTURE_DEVICE"])]
+        if "CAPTURE_DEVICE" in os.environ and os.environ["CAPTURE_DEVICE"] != ""
+        else [],
         type=int,
         help="Capture device number",
     )
@@ -77,10 +79,10 @@ def set_argparse():
         help="Don't display the video feed",
     )
     video_options.add_argument(
-        '-c',
-        '--force-disable-tensorflow-gpu',
+        "-c",
+        "--force-disable-tensorflow-gpu",
         default=os.environ["FORCE_DISABLE_TENSORFLOW_GPU"]
-        if "FORCE_DISABLE_TENSORFLOW_GPU" in os.environ 
+        if "FORCE_DISABLE_TENSORFLOW_GPU" in os.environ
         and os.environ["FORCE_DISABLE_TENSORFLOW_GPU"] != ""
         and os.environ["FORCE_DISABLE_TENSORFLOW_GPU"].lower() != "false"
         else False,
@@ -126,7 +128,6 @@ def set_argparse():
         help="The time (seconds) before another notification can be sent",
     )
 
-
     face_recognition = argparser.add_argument_group("Face Recognition options")
     face_recognition.add_argument(
         "--faces-directory",
@@ -156,8 +157,6 @@ def set_argparse():
         help="Don't remove representations_<model>.pkl at the start of the program. Greatly improves startup time, but doesn't take into account changes to the faces directory since it was created",  # noqa: E501
     )
 
-
-
     object_detection = argparser.add_argument_group("Object Detection options")
     object_detection.add_argument(
         "--detect-object",
@@ -171,11 +170,10 @@ def set_argparse():
         "--object-confidence-threshold",
         default=os.environ["OBJECT_CONFIDENCE_THRESHOLD"]
         if "OBJECT_CONFIDENCE_THRESHOLD" in os.environ
-        and os.environ["OBJECT_CONFIDENCE_THRESHOLD"] != "" 
-        # I think this should always be a str so using lower shouldn't be a problem. 
-        # Also, if the first check fails the rest shouldn't be run 
-        and os.environ["OBJECT_CONFIDENCE_THRESHOLD"].lower() != "false"
-        else 0.6,
+        and os.environ["OBJECT_CONFIDENCE_THRESHOLD"] != ""
+        # I think this should always be a str so using lower shouldn't be a problem.
+        # Also, if the first check fails the rest shouldn't be run
+        and os.environ["OBJECT_CONFIDENCE_THRESHOLD"].lower() != "false" else 0.6,
         type=float,
         help="The confidence threshold to use",
     )
diff --git a/wyzely_detect/utils/utils.py b/wyzely_detect/utils/utils.py
index 5ac48c7..c13c01f 100644
--- a/wyzely_detect/utils/utils.py
+++ b/wyzely_detect/utils/utils.py
@@ -2,12 +2,13 @@ import cv2
 import os
 import numpy as np
 from pathlib import Path
+
 # https://stackoverflow.com/a/42121886/18270659
-os.environ['TF_CPP_MIN_LOG_LEVEL']='3'
+os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3"
 
 
-from deepface import DeepFace # noqa: E402
-from . import notify # noqa: E402
+from deepface import DeepFace  # noqa: E402
+from . import notify  # noqa: E402
 
 first_face_try = True
 
@@ -21,36 +22,30 @@ objects_and_peoples = {
 def process_footage(
     # Frame
     frame: np.ndarray = None,
-
     # scale
     run_scale: float = None,
     view_scale: float = None,
-
     # Face stuff
     faces_directory: str = None,
     face_confidence_threshold: float = None,
     no_remove_representations: bool = False,
-
     # Timer stuff
     detection_window: int = None,
     detection_duration: int = None,
     notification_window: int = None,
-
     ntfy_url: str = None,
-
     # Object stuff
     # YOLO object
-    model = None,
+    model=None,
     detect_object: list = None,
-    object_confidence_threshold = None
+    object_confidence_threshold=None,
 ) -> np.ndarray:
     """
     Takes in a frame and processes it
-    """ 
+    """
 
     global objects_and_peoples
 
-    
     # Resize frame of video to a smaller size for faster recognition processing
     run_frame = cv2.resize(frame, (0, 0), fx=run_scale, fy=run_scale)
     # view_frame = cv2.resize(frame, (0, 0), fx=args.view_scale, fy=args.view_scale)
@@ -60,7 +55,7 @@ def process_footage(
     path_to_faces = Path(faces_directory)
     path_to_faces_exists = path_to_faces.is_dir()
 
-    for i, r in enumerate(results):
+    for r in results:
         # list of dicts with each dict containing a label, x1, y1, x2, y2
         plot_boxes = []
 
@@ -105,7 +100,8 @@ def process_footage(
             # Also, make sure that the objects to detect are in the list of objects_and_peoples
             # If it isn't, print a warning
             for obj in detect_object:
-                if obj not in objects_and_peoples["objects"].keys():
+                # .keys() shouldn't be needed
+                if obj not in objects_and_peoples["objects"]:
                     print(
                         f"Warning: {obj} is not in the list of objects the model can detect!"
                     )
@@ -153,7 +149,6 @@ def process_footage(
                 notification_window=notification_window,
                 ntfy_url=ntfy_url,
             )
-            
 
         # To debug plotting, use r.plot() to cross reference the bounding boxes drawn by the plot_label() and r.plot()
         frame_to_show = plot_label(
@@ -233,26 +228,27 @@ def recognize_face(
     no_remove_representations: bool = False,
 ) -> np.ndarray:
     """
-    Accepts a path to a directory of images of faces to be used as a refference
-    In addition, accepts an opencv image to be used as the frame to be searched
+        Accepts a path to a directory of images of faces to be used as a refference
+        In addition, accepts an opencv image to be used as the frame to be searched
 
-    Returns a single dictonary as currently only 1 face can be detected in each frame
-    Cosine threshold is 0.3, so if the confidence is less than that, it will return None
-    dict contains the following keys: label, x1, y1, x2, y2
-    The directory should be structured as follows:
-    faces/
-        name/
-            image1.jpg
-            image2.jpg
-            image3.jpg
-        name2/
-            image1.jpg
-            image2.jpg
-            image3.jpg
-    (not neccessarily jpgs, but you get the idea)
+        Returns a single dictonary as currently only 1 face can be detected in each frame
+        Cosine threshold is 0.3, so if the confidence is less than that, it will return None
+        dict conta                # Maybe use os.exit() instead?
+    ins the following keys: label, x1, y1, x2, y2
+        The directory should be structured as follows:
+        faces/
+            name/
+                image1.jpg
+                image2.jpg
+                image3.jpg
+            name2/
+                image1.jpg
+                image2.jpg
+                image3.jpg
+        (not neccessarily jpgs, but you get the idea)
 
-    Point is, `name` is the name of the person in the images in the directory `name`
-    That name will be used as the label for the face in the frame
+        Point is, `name` is the name of the person in the images in the directory `name`
+        That name will be used as the label for the face in the frame
     """
     global first_face_try
 
@@ -285,8 +281,11 @@ def recognize_face(
             model_name="ArcFace",
             detector_backend="opencv",
         )
-    
-    except (ValueError) as e:
+        """
+        Example dataframe, for reference
+        identity  (path to image) | source_x | source_y | source_w | source_h | VGG-Face_cosine (pretty much the confidence \_('_')_/) 
+        """
+    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
@@ -295,11 +294,12 @@ def recognize_face(
             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)
+            "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 
+            return None
         else:
             raise e
     # Iteate over the dataframes
@@ -338,8 +338,3 @@ def recognize_face(
         )
         return to_return
     return None
-
-    """
-    Example dataframe, for reference
-    identity  (path to image) | source_x | source_y | source_w | source_h | VGG-Face_cosine (pretty much the confidence \_('_')_/) 
-    """

From 37d39d434f90b444e2f83261f48f2011abe6c0d5 Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Fri, 16 Feb 2024 13:05:27 -0600
Subject: [PATCH 15/18] Fixed the following: * Unused global var
 `objects_and_peoples` (`__main.py__`) * Random `print` (`__main.py__`) *
 Unescaped backslash (`utils.py`)

---
 wyzely_detect/__main__.py    | 3 ---
 wyzely_detect/utils/utils.py | 2 +-
 2 files changed, 1 insertion(+), 4 deletions(-)

diff --git a/wyzely_detect/__main__.py b/wyzely_detect/__main__.py
index 22afc0e..2512386 100644
--- a/wyzely_detect/__main__.py
+++ b/wyzely_detect/__main__.py
@@ -16,7 +16,6 @@ args = None
 
 
 def main():
-    global objects_and_peoples
     global args
 
     args = argparser.parse_args()
@@ -100,8 +99,6 @@ def main():
                 ]
             )
     print(pretty_table)
-
-    print
     print("Beginning video capture...")
     while True:
         # Grab a single frame of video
diff --git a/wyzely_detect/utils/utils.py b/wyzely_detect/utils/utils.py
index c13c01f..de4503c 100644
--- a/wyzely_detect/utils/utils.py
+++ b/wyzely_detect/utils/utils.py
@@ -283,7 +283,7 @@ def recognize_face(
         )
         """
         Example dataframe, for reference
-        identity  (path to image) | source_x | source_y | source_w | source_h | VGG-Face_cosine (pretty much the confidence \_('_')_/) 
+        identity  (path to image) | source_x | source_y | source_w | source_h | VGG-Face_cosine (pretty much the confidence \\_('_')_/) 
         """
     except ValueError as e:
         if (

From 4285be54b7630397aef198c57d14060d46e613ca Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Fri, 16 Feb 2024 13:11:41 -0600
Subject: [PATCH 16/18] Replaced string with multi-line comment

---
 wyzely_detect/utils/utils.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/wyzely_detect/utils/utils.py b/wyzely_detect/utils/utils.py
index de4503c..000a2c9 100644
--- a/wyzely_detect/utils/utils.py
+++ b/wyzely_detect/utils/utils.py
@@ -281,10 +281,10 @@ def recognize_face(
             model_name="ArcFace",
             detector_backend="opencv",
         )
-        """
+        '''
         Example dataframe, for reference
         identity  (path to image) | source_x | source_y | source_w | source_h | VGG-Face_cosine (pretty much the confidence \\_('_')_/) 
-        """
+        '''
     except ValueError as e:
         if (
             str(e)

From 835e19ed18061328026c3f7ea489b9df577ca8fd Mon Sep 17 00:00:00 2001
From: "deepsource-autofix[bot]"
 <62050782+deepsource-autofix[bot]@users.noreply.github.com>
Date: Fri, 16 Feb 2024 19:13:48 +0000
Subject: [PATCH 17/18] refactor: autofix issues in 1 file

Resolved issues in wyzely_detect/utils/utils.py with DeepSource Autofix
---
 wyzely_detect/utils/utils.py | 5 +----
 1 file changed, 1 insertion(+), 4 deletions(-)

diff --git a/wyzely_detect/utils/utils.py b/wyzely_detect/utils/utils.py
index 000a2c9..4b45577 100644
--- a/wyzely_detect/utils/utils.py
+++ b/wyzely_detect/utils/utils.py
@@ -40,10 +40,7 @@ def process_footage(
     detect_object: list = None,
     object_confidence_threshold=None,
 ) -> np.ndarray:
-    """
-    Takes in a frame and processes it
-    """
-
+    """Takes in a frame and processes it"""
     global objects_and_peoples
 
     # Resize frame of video to a smaller size for faster recognition processing

From f7f5db9f41533434e72c09d6f7f16332d5d91fc4 Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Fri, 16 Feb 2024 13:17:03 -0600
Subject: [PATCH 18/18] Updated TODO comments

---
 wyzely_detect/__main__.py    | 1 -
 wyzely_detect/utils/utils.py | 2 +-
 2 files changed, 1 insertion(+), 2 deletions(-)

diff --git a/wyzely_detect/__main__.py b/wyzely_detect/__main__.py
index 2512386..f516528 100644
--- a/wyzely_detect/__main__.py
+++ b/wyzely_detect/__main__.py
@@ -126,7 +126,6 @@ def main():
                 )
             )
         # Display the resulting frame
-        # TODO: When multi-camera support is added, this needs to be changed to allow all feeds
         if not args.no_display:
             for i, frame_to_show in enumerate(frames_to_show):
                 cv2.imshow(f"Video {i}", frame_to_show)
diff --git a/wyzely_detect/utils/utils.py b/wyzely_detect/utils/utils.py
index 4b45577..1414bbb 100644
--- a/wyzely_detect/utils/utils.py
+++ b/wyzely_detect/utils/utils.py
@@ -12,7 +12,7 @@ from . import notify  # noqa: E402
 
 first_face_try = True
 
-# TODO: When multi-camera support is added, this will need to be changed so that each camera has its own dict
+# TODO: When multi-camera support is ~~added~~ improved, this will need to be changed so that each camera has its own dict
 objects_and_peoples = {
     "objects": {},
     "peoples": {},