From 1c6613b206c60af9daec367c88ca54482d617100 Mon Sep 17 00:00:00 2001
From: slashtechno <77907286+slashtechno@users.noreply.github.com>
Date: Sat, 17 Dec 2022 15:54:47 -0600
Subject: [PATCH] Initial commit

---
 .gitignore      |   2 +
 LICENSE         |  21 ++++++
 environment.yml | Bin 0 -> 4684 bytes
 main.py         | 177 ++++++++++++++++++++++++++++++++++++++++++++++++
 4 files changed, 200 insertions(+)
 create mode 100644 .gitignore
 create mode 100644 LICENSE
 create mode 100644 environment.yml
 create mode 100644 main.py

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..5f81549
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,2 @@
+person.jpg
+config.json
\ No newline at end of file
diff --git a/LICENSE b/LICENSE
new file mode 100644
index 0000000..36eb93f
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2022 slashtechno
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
\ No newline at end of file
diff --git a/environment.yml b/environment.yml
new file mode 100644
index 0000000000000000000000000000000000000000..c8725cc9fb9be14fea7fb56eb2a6f00ed17cc066
GIT binary patch
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diff --git a/main.py b/main.py
new file mode 100644
index 0000000..f531f91
--- /dev/null
+++ b/main.py
@@ -0,0 +1,177 @@
+import datetime
+import face_recognition
+import cv2
+import numpy as np
+from dotenv import load_dotenv
+import os
+import json
+import pathlib
+
+
+load_dotenv()
+URL = os.getenv("URL")
+RUN_SCALE = os.getenv("RUN_SCALE")
+VIEW_SCALE = os.getenv("VIEW_SCALE")
+DATETIME_FORMAT = "%Y-%m-%d %H:%M:%S"
+# RUN_SCALE = 0.25
+# VIEW_SCALE = 0.75
+
+
+def find_face_from_name(name):
+    for face in config["faces"]:
+        if config["faces"][face]["name"] == name:
+            return face
+    return None
+
+
+def write_config():
+    with open(config_path, "w") as config_file:
+        json.dump(config, config_file, indent=4)
+
+
+# Initialize some variables
+face_locations = []
+face_encodings = []
+face_names = []
+known_face_encodings = []
+known_face_names = []
+process_this_frame = True
+
+# Load the config file, if it does not exist or is blank, create it
+config = {
+    "URL": "rtsp://localhost:8554/example",
+    "RUN_SCALE": "0.25",
+    "VIEW_SCALE": "0.75",
+    "faces": {
+        "example1": {"image": "example1.jpg", "last_seen": ""},
+        "example2": {"image": "example2.jpg", "last_seen": ""},
+    },
+}
+config_path = pathlib.Path("config.json")
+if config_path.exists():
+    with open(config_path, "r") as config_file:
+        config = json.load(config_file)
+else:
+    with open(config_path, "w") as config_file:
+        json.dump(config, config_file, indent=4)
+    print("Config file created, please edit it and restart the program")
+    exit()
+
+
+if URL:
+    config["URL"] = URL
+else:
+    URL = config["URL"]
+if RUN_SCALE:
+    config["RUN_SCALE"] = RUN_SCALE
+else:
+    RUN_SCALE = float(config["RUN_SCALE"])
+if VIEW_SCALE:
+    config["VIEW_SCALE"] = VIEW_SCALE
+else:
+    VIEW_SCALE = float(config["VIEW_SCALE"])
+
+for face in config["faces"]:
+    # Load a sample picture and learn how to recognize it.
+    image = face_recognition.load_image_file(config["faces"][face]["image"])
+    face_encoding = face_recognition.face_encodings(image)[0]
+    known_face_encodings.append(face_encoding)
+    # Append the key to the list of known face names
+    known_face_names.append(face)
+
+video_capture = cv2.VideoCapture(URL)
+# 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)
+
+while True:
+    # Grab a single frame of video
+    ret, frame = video_capture.read()
+
+    # Only process every other frame of video to save time
+    # if process_this_frame:
+    if True:
+        # Resize frame of video to a smaller size for faster face recognition processing
+        run_frame = cv2.resize(frame, (0, 0), fx=RUN_SCALE, fy=RUN_SCALE)
+        view_frame = cv2.resize(frame, (0, 0), fx=VIEW_SCALE, fy=VIEW_SCALE)
+
+        # Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
+        rgb_run_frame = run_frame[:, :, ::-1]
+
+        # Find all the faces and face encodings in the current frame of video
+        # model cnn is gpu accelerated, but hog is cpu only
+        face_locations = face_recognition.face_locations(rgb_run_frame, model="hog")
+        face_encodings = face_recognition.face_encodings(rgb_run_frame, face_locations)
+
+        face_names = []
+        for face_encoding in face_encodings:
+            # See if the face is a match for the known face(s)
+            matches = face_recognition.compare_faces(
+                known_face_encodings, face_encoding
+            )
+            name = "Unknown"
+
+            # Or instead, use the known face with the smallest distance to the new face
+            face_distances = face_recognition.face_distance(
+                known_face_encodings, face_encoding
+            )
+            best_match_index = np.argmin(face_distances)
+            if matches[best_match_index]:
+                # print("For debugging, I found a face!!!! :D this should not be included in the final product lol :P")
+                name = known_face_names[best_match_index]
+                last_seen = config["faces"][name]["last_seen"]
+                # If it's never been seen, set the last seen time to six seconds ago so it will be seen
+                # Kind of a hacky way to do it, but it works... hopefully
+                if last_seen == "":
+                    print(f"{name} has been seen")
+                    config["faces"][name]["last_seen"] = (
+                        datetime.datetime.now() - datetime.timedelta(seconds=6)
+                    ).strftime(DATETIME_FORMAT)
+                    write_config()
+                # Check if the face has been seen in the last 5 seconds
+                if datetime.datetime.now() - datetime.datetime.strptime(
+                    last_seen, DATETIME_FORMAT
+                ) > datetime.timedelta(seconds=5):
+                    print(f"{name} has been seen")
+                # Update the last seen time
+                config["faces"][name]["last_seen"] = datetime.datetime.now().strftime(
+                    DATETIME_FORMAT
+                )
+                write_config()
+            face_names.append(name)
+
+    process_this_frame = not process_this_frame
+
+    # Display the results
+    # Iterate over each face found in the frame to draw a box around it
+    # Zip is used to iterate over two lists at the same time
+    for (top, right, bottom, left), name in zip(face_locations, face_names):
+        # Scale back up face locations since the frame we detected in was scaled to 1/4 size
+        top = int(top * (VIEW_SCALE / RUN_SCALE))
+        right = int(right * (VIEW_SCALE / RUN_SCALE))
+        bottom = int(bottom * (VIEW_SCALE / RUN_SCALE))
+        left = int(left * (VIEW_SCALE / RUN_SCALE))
+
+        # Draw a box around the face
+        cv2.rectangle(view_frame, (left, top), (right, bottom), (0, 0, 255), 2)
+
+        # Draw a label with a name below the face
+        cv2.rectangle(
+            view_frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED
+        )
+        font = cv2.FONT_HERSHEY_DUPLEX
+        cv2.putText(
+            view_frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1
+        )
+
+    # Display the resulting image
+    cv2.imshow("Scaled View", view_frame)
+
+    # Hit 'q' on the keyboard to quit!
+    if cv2.waitKey(1) & 0xFF == ord("q"):
+        break
+
+# Release handle to the webcam
+video_capture.release()
+cv2.destroyAllWindows()