all files

README.md

@@ -1,12 +1 @@
----
-title: Aps
-emoji: 💻
-colorFrom: gray
-colorTo: indigo
-sdk: streamlit
-sdk_version: 1.17.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# aps-streamlit-share

additional/requirements.txt

@@ -0,0 +1,94 @@
+absl-py==1.4.0
+aioice==0.7.6
+aiortc==1.4.0
+altair==4.2.2
+attrs==22.2.0
+av==10.0.0
+blinker==1.5
+cachetools==5.3.0
+certifi==2022.12.7
+cffi==1.15.1
+charset-normalizer==3.0.1
+click==8.1.3
+colorama==0.4.6
+contourpy==1.0.7
+cryptography==38.0.4
+cycler==0.11.0
+decorator==5.1.1
+Deprecated==1.2.13
+dlib
+dnspython==2.3.0
+entrypoints==0.4
+flatbuffers==23.1.21
+fonttools==4.38.0
+gcloud==0.18.3
+gitdb==4.0.10
+GitPython==3.1.30
+google-crc32c==1.5.0
+googleapis-common-protos==1.58.0
+httplib2==0.21.0
+idna==3.4
+importlib-metadata==6.0.0
+imutils==0.5.4
+Jinja2==3.1.2
+jsonschema==4.17.3
+jwcrypto==1.4.2
+kiwisolver==1.4.4
+markdown-it-py==2.1.0
+MarkupSafe==2.1.2
+matplotlib==3.6.3
+mdurl==0.1.2
+mediapipe==0.9.1.0
+netifaces==0.11.0
+numpy==1.24.1
+oauth2client==4.1.3
+opencv-contrib-python==4.7.0.68
+opencv-python==4.7.0.68
+packaging==23.0
+pandas==1.5.3
+Pillow==9.4.0
+protobuf==3.20.3
+pyarrow==11.0.0
+pyasn1==0.4.8
+pyasn1-modules==0.2.8
+pycparser==2.21
+pycryptodome==3.17
+pydeck==0.8.0
+pydub==0.25.1
+pyee==9.0.4
+Pygments==2.14.0
+pylibsrtp==0.8.0
+pymongo==4.3.3
+Pympler==1.0.1
+pyOpenSSL==23.0.0
+pyparsing==3.0.9
+Pyrebase4==4.6.0
+pyrsistent==0.19.3
+python-dateutil==2.8.2
+python-jwt==4.0.0
+pytz==2022.7.1
+pytz-deprecation-shim==0.1.0.post0
+requests==2.28.2
+requests-toolbelt==0.10.1
+rich==13.3.1
+rsa==4.9
+scipy==1.10.0
+semver==2.13.0
+six==1.16.0
+smmap==5.0.0
+streamlit==1.17.0
+streamlit-nested-layout==0.1.1
+streamlit-option-menu==0.3.2
+streamlit-webrtc==0.44.2
+toml==0.10.2
+toolz==0.12.0
+tornado==6.2
+typing_extensions==4.4.0
+tzdata==2022.7
+tzlocal==4.2
+urllib3==1.26.14
+validators==0.20.0
+watchdog==2.2.1
+wincertstore==0.2
+wrapt==1.14.1
+zipp==3.12.0

app.py

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+import os
+import threading
+
+import av
+import bcrypt
+import pymongo
+import streamlit as st
+from streamlit_option_menu import option_menu
+from streamlit_webrtc import VideoHTMLAttributes, webrtc_streamer
+from twilio.rest import Client
+
+from audio_handling import AudioFrameHandler
+from drowsy_detection import VideoFrameHandler
+
+# Define the audio file to use.
+alarm_file_path = os.path.join("audio", "wake_up.wav")
+logged_in = False
+
+def update_sliders():
+    slider_wait = 1.0
+    eye_thresh = 0.18
+    lip_thresh = 0.2
+
+    client = pymongo.MongoClient("mongodb+srv://admin:Admin123@aps.agcjjww.mongodb.net/?retryWrites=true&w=majority")
+    db = client["aps-db"]
+    slider_values = db["slider-values"]
+
+    if slider_wait != WAIT_TIME:
+        slider_values.update_one({"slider_name": "Wait_Time"}, {"$set": {"value": WAIT_TIME}}, upsert=True)
+    if eye_thresh != EAR_THRESH:
+        slider_values.update_one({"slider_name": "Eye_Threshold"}, {"$set": {"value": EAR_THRESH}}, upsert=True)
+    if lip_thresh != LIP_THRESH:
+        slider_values.update_one({"slider_name": "Lip_Threshold"}, {"$set": {"value": LIP_THRESH}}, upsert=True)
+
+# Streamlit Components
+st.set_page_config(
+    page_title="Drowsiness Detection | APS",
+    page_icon="https://framerusercontent.com/modules/466qV2P53XLpEfUjjmZC/FNnZTYISEsUGPpjII54W/assets/VebAVoINVBFxBTpsrQVLHznVo.png",
+    initial_sidebar_state="expanded",
+    layout="wide",
+)
+
+menu_choice = option_menu(
+            menu_title=None,  
+            options=["Home", "Login", "Signup", "OTP Login", "About"],  
+            icons=["house", "box-arrow-in-right", "pencil-square","telephone", "question-circle"],  
+            menu_icon="cast",  
+            default_index=0,  
+            orientation="horizontal",
+        )
+
+if menu_choice == "Home":
+    st.title("Drowsiness Detection")
+    with st.container():
+        c1, c2, c3 = st.columns(spec=[1, 1, 1])
+        with c1:
+            # The amount of time (in seconds) to wait before sounding the alarm.
+            WAIT_TIME = st.slider("Time to wait before sounding alarm:", 0.0, 5.0, 1.0, 0.25)
+
+        with c2:
+            # Lowest valid value of Eye Aspect Ratio. Ideal values [0.15, 0.2].
+            EAR_THRESH = st.slider("Eye Aspect Ratio threshold:", 0.0, 0.4, 0.18, 0.01)
+        
+        with c3:
+            # Lip threshold to detect yawning
+            LIP_THRESH = st.slider("Lip threshold:", 0.0, 0.4, 0.2, 0.01)
+            LIP_THRESH = LIP_THRESH*100
+
+    thresholds = {
+        "EAR_THRESH": EAR_THRESH,
+        "WAIT_TIME": WAIT_TIME, 
+        "LIP_THRESH": LIP_THRESH
+    }
+    update_sliders()
+
+    # For streamlit-webrtc
+    video_handler = VideoFrameHandler()
+    audio_handler = AudioFrameHandler(sound_file_path=alarm_file_path)
+
+    lock = threading.Lock()  # For thread-safe access & to prevent race-condition.
+    shared_state = {"play_alarm": False}  # Shared state between callbacks.
+
+    def video_frame_callback(frame: av.VideoFrame):
+        frame = frame.to_ndarray(format="bgr24")  # Decode and convert frame to RGB
+
+        frame, play_alarm = video_handler.process(frame, thresholds)  # Process frame
+        with lock:
+            shared_state["play_alarm"] = play_alarm  # Update shared state
+
+        return av.VideoFrame.from_ndarray(frame, format="bgr24")  # Encode and return BGR frame
+
+    def audio_frame_callback(frame: av.AudioFrame):
+        with lock:  # access the current “play_alarm” state
+            play_alarm = shared_state["play_alarm"]
+
+        new_frame: av.AudioFrame = audio_handler.process(frame, play_sound=play_alarm)
+        return new_frame
+
+    ctx = webrtc_streamer(
+        key="drowsiness-detection",
+        video_frame_callback=video_frame_callback,
+        audio_frame_callback=audio_frame_callback,
+        rtc_configuration={"iceServers": [{"urls": ["stun:stun.l.google.com:19302"]}]},  # Add this to config for cloud deployment.
+        media_stream_constraints={"video": {"height": {"ideal": 480}}, "audio": True},
+        video_html_attrs=VideoHTMLAttributes(autoPlay=True, controls=False, muted=False),
+    )
+
+#handling login
+
+if menu_choice == "Login":
+    st.text('Login')
+    email = st.text_input('Enter email')
+    password = st.text_input('Enter password', type="password")
+    if st.button('Login'):
+        try:
+            client = pymongo.MongoClient("mongodb+srv://admin:Admin123@aps.agcjjww.mongodb.net/?retryWrites=true&w=majority")
+            db = client["aps-db"]
+            users = db["users"]
+            user = users.find_one({"email": email})
+            if user:
+                if bcrypt.checkpw(password.encode(), user["password"]):
+                    st.success("Successfully logged in!")
+                    menu_choice = "Home"
+                    os.environ["email"] = email
+                    os.environ["user_id"] = str(user["_id"])
+                    os.environ["logged_in"] = "True"
+                else:
+                    st.error("Invalid password")
+            else:
+                st.error("Email not found")
+        except Exception as e:
+                st.error("An error occurred: {}".format(str(e)))
+
+if menu_choice == "Signup":
+    st.text('Signup')
+    email = st.text_input('Enter email')
+    password = st.text_input('Enter password', type="password")
+    if st.button('Signup'):
+        try:
+            client = pymongo.MongoClient("mongodb+srv://admin:Admin123@aps.agcjjww.mongodb.net/?retryWrites=true&w=majority")
+            db = client["aps-db"]
+            users = db["users"]
+            if users.find_one({"email": email}):
+                st.error("Email already exists")
+            else:
+                hashed_password = bcrypt.hashpw(password.encode(), bcrypt.gensalt())
+                users.insert_one({"email": email, "password": hashed_password})
+                st.success("Successfully signed up!")
+        except Exception as e:
+            st.error("An error occurred: {}".format(str(e)))
+        
+#phone number login
+account_sid = "AC97fd9a03c4637fe246adcecc613bb153"
+auth_token = os.environ["TWILIO_AUTH_TOKEN"]
+verify_sid = "VA629a29a82eedcde1e6c89e5f586fdbfd"
+
+if menu_choice == "OTP Login":
+    st.text("Please enter country code followed by phone number")
+    st.text("For example: +919255520023")
+    verified_number = st.text_input("Enter your phone number")
+
+    client = Client(account_sid, auth_token)
+    otp_sent = False
+    if st.button("Send OTP"):
+        verification = client.verify.v2.services(verify_sid) \
+        .verifications \
+        .create(to=verified_number, channel="sms")
+        if (verification.status == "pending" or verification.status == "started"):
+            st.success("OTP sent successfully to " + verified_number)
+            otp_sent = True
+        else:
+            st.error("Error sending OTP")
+
+    otp_code = st.text_input("Please enter the OTP:",type="password")
+    if st.button("Verify OTP"):
+        verification_check = client.verify.v2.services(verify_sid) \
+        .verification_checks \
+        .create(to=verified_number, code=otp_code)
+        if (verification_check.status == "approved"):
+            st.success("OTP Verified")
+            client = pymongo.MongoClient("mongodb+srv://admin:Admin123@aps.agcjjww.mongodb.net/?retryWrites=true&w=majority")
+            db = client["aps-db"]
+            users = db["users"]
+            users.insert_one({"phone": verified_number})
+        else:
+            st.error("OTP Verification Failed")
+            
+    
+hide_streamlit_style = """
+            <style>
+            #MainMenu {visibility: hidden;}
+            footer {visibility: hidden;}
+            </style>
+            """
+st.markdown(hide_streamlit_style, unsafe_allow_html=True)

audio_handling.py

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+import av
+import numpy as np
+from pydub import AudioSegment
+
+
+class AudioFrameHandler:
+    """To play/pass custom audio based on some event"""
+
+    def __init__(self, sound_file_path: str = ""):
+
+        self.custom_audio = AudioSegment.from_file(file=sound_file_path, format="wav")
+        self.custom_audio_len = len(self.custom_audio)
+
+        self.ms_per_audio_segment: int = 20
+        self.audio_segment_shape: tuple
+
+        self.play_state_tracker: dict = {"curr_segment": -1}  # Currently playing segment
+        self.audio_segments_created: bool = False
+        self.audio_segments: list = []
+
+    def prepare_audio(self, frame: av.AudioFrame):
+        raw_samples = frame.to_ndarray()
+        sound = AudioSegment(
+            data=raw_samples.tobytes(),
+            sample_width=frame.format.bytes,
+            frame_rate=frame.sample_rate,
+            channels=len(frame.layout.channels),
+        )
+
+        self.ms_per_audio_segment = len(sound)
+        self.audio_segment_shape = raw_samples.shape
+
+        self.custom_audio = self.custom_audio.set_channels(sound.channels)
+        self.custom_audio = self.custom_audio.set_frame_rate(sound.frame_rate)
+        self.custom_audio = self.custom_audio.set_sample_width(sound.sample_width)
+
+        self.audio_segments = [
+            self.custom_audio[i : i + self.ms_per_audio_segment]
+            for i in range(0, self.custom_audio_len - self.custom_audio_len % self.ms_per_audio_segment, self.ms_per_audio_segment)
+        ]
+        self.total_segments = len(self.audio_segments) - 1  # -1 because we start from 0.
+
+        self.audio_segments_created = True
+
+    def process(self, frame: av.AudioFrame, play_sound: bool = False):
+
+        """
+        Takes in the current input audio frame and based on play_sound boolean value
+        either starts sending the custom audio frame or dampens the frame wave to emulate silence.
+
+        For eg. playing a notification based on some event.
+        """
+
+        if not self.audio_segments_created:
+            self.prepare_audio(frame)
+
+        raw_samples = frame.to_ndarray()
+        _curr_segment = self.play_state_tracker["curr_segment"]
+
+        if play_sound:
+            if _curr_segment < self.total_segments:
+                _curr_segment += 1
+            else:
+                _curr_segment = 0
+
+            sound = self.audio_segments[_curr_segment]
+
+        else:
+            if -1 < _curr_segment < self.total_segments:
+                _curr_segment += 1
+                sound = self.audio_segments[_curr_segment]
+            else:
+                _curr_segment = -1
+                sound = AudioSegment(
+                    data=raw_samples.tobytes(),
+                    sample_width=frame.format.bytes,
+                    frame_rate=frame.sample_rate,
+                    channels=len(frame.layout.channels),
+                )
+                sound = sound.apply_gain(-100)
+
+        self.play_state_tracker["curr_segment"] = _curr_segment
+
+        channel_sounds = sound.split_to_mono()
+        channel_samples = [s.get_array_of_samples() for s in channel_sounds]
+
+        new_samples = np.array(channel_samples).T
+
+        new_samples = new_samples.reshape(self.audio_segment_shape)
+        new_frame = av.AudioFrame.from_ndarray(new_samples, layout=frame.layout.name)
+        new_frame.sample_rate = frame.sample_rate
+
+        return new_frame

drowsy_detection.py

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+import os
+import time
+
+import cv2
+import dlib
+import mediapipe as mp
+import numpy as np
+import pymongo
+import pyrebase
+import streamlit as st
+from bson.objectid import ObjectId
+from imutils import face_utils
+from mediapipe.python.solutions.drawing_utils import \
+    _normalized_to_pixel_coordinates as denormalize_coordinates
+from scipy.spatial import distance as dist
+
+config = {"apiKey": "AIzaSyCNPBcskQFs2tn5UfdFbP8LzbnEMIarsWc",
+  "authDomain": "aps-csia.firebaseapp.com",
+  "databaseURL": "https://aps-csia-default-rtdb.asia-southeast1.firebasedatabase.app/",
+  "projectId": "aps-csia",
+  "storageBucket": "aps-csia.appspot.com",
+  "messagingSenderId": "1069559357849",
+  "appId": "1:1069559357849:web:39e9d0139d42a206973308",
+  "measurementId": "G-FVTG7XGLN7"}
+
+firebase = pyrebase.initialize_app(config)
+db = firebase.database()
+
+print("-> Loading the predictor and detector...")
+detector = cv2.CascadeClassifier("./haarcascade_frontalface_default.xml")    #Faster but less accurate
+predictor = dlib.shape_predictor('./shape_predictor_68_face_landmarks.dat')
+
+def get_mediapipe_app(
+    max_num_faces=1,
+    refine_landmarks=True,
+    min_detection_confidence=0.5,
+    min_tracking_confidence=0.5,
+):
+    """Initialize and return Mediapipe FaceMesh Solution Graph object"""
+    face_mesh = mp.solutions.face_mesh.FaceMesh(
+        max_num_faces=max_num_faces,
+        refine_landmarks=refine_landmarks,
+        min_detection_confidence=min_detection_confidence,
+        min_tracking_confidence=min_tracking_confidence,
+    )
+
+    return face_mesh
+
+def distance(point_1, point_2):
+    """Calculate l2-norm between two points"""
+    dist = sum([(i - j) ** 2 for i, j in zip(point_1, point_2)]) ** 0.5
+    return dist
+
+
+def get_ear(landmarks, refer_idxs, frame_width, frame_height):
+    """
+    Calculate Eye Aspect Ratio for one eye.
+
+    Args:
+        landmarks: (list) Detected landmarks list
+        refer_idxs: (list) Index positions of the chosen landmarks
+                            in order P1, P2, P3, P4, P5, P6
+        frame_width: (int) Width of captured frame
+        frame_height: (int) Height of captured frame
+
+    Returns:
+        ear: (float) Eye aspect ratio
+    """
+    try:
+        # Compute the euclidean distance between the horizontal
+        coords_points = []
+        for i in refer_idxs:
+            lm = landmarks[i]
+            coord = denormalize_coordinates(lm.x, lm.y, frame_width, frame_height)
+            coords_points.append(coord)
+
+        # Eye landmark (x, y)-coordinates
+        P1_P4 = dist.euclidean(coords_points[0], coords_points[3])
+        P2_P6 = dist.euclidean(coords_points[1], coords_points[5])
+        P3_P5 = dist.euclidean(coords_points[2], coords_points[4])
+
+        # Compute the eye aspect ratio
+        ear = (P2_P6 + P3_P5) / (2.0 * P1_P4)
+
+    except:
+        ear = 0.0
+        coords_points = None
+
+    return ear, coords_points
+
+
+def calculate_avg_ear(landmarks, left_eye_idxs, right_eye_idxs, image_w, image_h):
+    # Calculate Eye aspect ratio
+
+    left_ear, left_lm_coordinates = get_ear(landmarks, left_eye_idxs, image_w, image_h)
+    right_ear, right_lm_coordinates = get_ear(landmarks, right_eye_idxs, image_w, image_h)
+    Avg_EAR = (left_ear + right_ear) / 2.0
+
+    return Avg_EAR, (left_lm_coordinates, right_lm_coordinates)
+
+
+def plot_eye_landmarks(frame, left_lm_coordinates, right_lm_coordinates, color):
+    for lm_coordinates in [left_lm_coordinates, right_lm_coordinates]:
+        if lm_coordinates:
+            for coord in lm_coordinates:
+                cv2.circle(frame, coord, 2, color, -1)
+
+    return frame
+
+def lip_distance(shape):
+    top_lip = shape[50:53]
+    top_lip = np.concatenate((top_lip, shape[61:64]))
+
+    low_lip = shape[56:59]
+    low_lip = np.concatenate((low_lip, shape[65:68]))
+
+    top_mean = np.mean(top_lip, axis=0)
+    low_mean = np.mean(low_lip, axis=0)
+
+    distance = abs(top_mean[1] - low_mean[1])
+    return distance
+
+
+def plot_text(image, text, origin, color, font=cv2.FONT_HERSHEY_SIMPLEX, fntScale=0.8, thickness=2):
+    image = cv2.putText(image, text, origin, font, fntScale, color, thickness)
+    return image
+
+class VideoFrameHandler:
+    def __init__(self):
+        """
+        Initialize the necessary constants, mediapipe app
+        and tracker variables
+        """
+        # Left and right eye chosen landmarks.
+        self.count_drowsy = 0
+        self.count_yawn = 0
+        self.eye_idxs = {
+            "left": [362, 385, 387, 263, 373, 380],
+            "right": [33, 160, 158, 133, 153, 144],
+        }
+
+        # Used for coloring landmark points.
+        # Its value depends on the current EAR value.
+        self.RED = (0, 0, 255)  # BGR
+        self.GREEN = (0, 255, 0)  # BGR
+
+        # Initializing Mediapipe FaceMesh solution pipeline
+        self.facemesh_model = get_mediapipe_app()
+
+        # For tracking counters and sharing states in and out of callbacks.
+        self.state_tracker = {
+            "start_time": time.perf_counter(),
+            "DROWSY_TIME": 0.0,  # Holds the amount of time passed with EAR < EAR_THRESH
+            "COLOR": self.GREEN,
+            "play_alarm": False,
+        }
+
+        self.EAR_txt_pos = (10, 30)
+
+    def process(self, frame: np.array, thresholds: dict):
+        """
+        This function is used to implement our Drowsy detection algorithm
+
+        Args:
+            frame: (np.array) Input frame matrix.
+            thresholds: (dict) Contains the two threshold values
+                               WAIT_TIME and EAR_THRESH.
+
+        Returns:
+            The processed frame and a boolean flag to
+            indicate if the alarm should be played or not.
+        """
+
+        # To improve performance,
+        # mark the frame as not writeable to pass by reference.
+        frame = cv2.flip(frame,1)
+        frame.flags.writeable = False
+        frame_h, frame_w, _ = frame.shape
+
+        DROWSY_TIME_txt_pos = (10, int(frame_h // 2 * 1.7))
+        ALM_txt_pos = (10, int(frame_h // 2 * 1.85))
+
+        #frame = cv2.flip(frame, 1)
+        results = self.facemesh_model.process(frame)
+        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        rects = detector.detectMultiScale(gray, scaleFactor=1.1, 
+        minNeighbors=5, minSize=(30, 30),
+        flags=cv2.CASCADE_SCALE_IMAGE)
+        for (x, y, w, h) in rects:
+            rect = dlib.rectangle(int(x), int(y), int(x + w),int(y + h))
+                    
+            shape = predictor(gray, rect)
+            shape = face_utils.shape_to_np(shape) 
+                    
+            distance = lip_distance(shape) 
+            lip = shape[48:60]
+            cv2.drawContours(frame, [lip], -1, (0, 255, 0), 1)
+            if (distance > thresholds["LIP_THRESH"]):
+                plot_text(frame, "Yawn Alert", (460, 440), (0, 0, 255))
+                time.sleep(1)
+                self.count_yawn += 1
+                if os.environ.get("logged_in") == "True":
+                    user_id = os.environ.get("user_id")
+                    email = os.environ.get("email")
+                    client = pymongo.MongoClient("mongodb+srv://admin:Admin123@aps.agcjjww.mongodb.net/?retryWrites=true&w=majority")
+                    db = client["aps-db"]
+                    users = db["count"]
+                    user = users.find_one({"_id": ObjectId(user_id)})
+                    if user:
+                        users.update_one({"_id": ObjectId(user_id)}, {"$set": {"count_yawn": self.count_yawn, "email": email}})
+                    else:
+                        users.insert_one({"_id": ObjectId(user_id), "count_yawn": self.count_yawn, "email": email})
+                else:
+                    st.error("Not logged in")
+        frame = plot_text(frame, f"Yawn count: {self.count_yawn}",(420,410), color=(0, 255, 0), thickness=2)
+
+        if results.multi_face_landmarks:
+            landmarks = results.multi_face_landmarks[0].landmark
+            EAR, coordinates = calculate_avg_ear(landmarks, self.eye_idxs["left"], self.eye_idxs["right"], frame_w, frame_h)
+            frame = plot_eye_landmarks(frame, coordinates[0], coordinates[1], self.state_tracker["COLOR"])
+            
+            if EAR < thresholds["EAR_THRESH"]:
+
+                # Increase DROWSY_TIME to track the time period with EAR less than the threshold
+                # and reset the start_time for the next iteration.
+                end_time = time.perf_counter()
+
+                self.state_tracker["DROWSY_TIME"] += end_time - self.state_tracker["start_time"]
+                self.state_tracker["start_time"] = end_time
+                self.state_tracker["COLOR"] = self.RED              
+
+                if self.state_tracker["DROWSY_TIME"] >= thresholds["WAIT_TIME"]:
+                    self.state_tracker["play_alarm"] = True
+                    plot_text(frame, "WAKE UP! WAKE UP", ALM_txt_pos, self.state_tracker["COLOR"])
+                    time.sleep(1)
+                    self.count_drowsy += 1
+                    if os.environ.get("logged_in") == "True":
+                        user_id = os.environ.get("user_id")
+                        email = os.environ.get("email")
+                        client = pymongo.MongoClient("mongodb+srv://admin:Admin123@aps.agcjjww.mongodb.net/?retryWrites=true&w=majority")
+                        db = client["aps-db"]
+                        users = db["count"]
+                        user = users.find_one({"_id": ObjectId(user_id)})
+                        if user:
+                            users.update_one({"_id": ObjectId(user_id)}, {"$set": {"count_drowsy": self.count_drowsy, "email": email}})
+                        else:
+                            users.insert_one({"_id": ObjectId(user_id), "count_drowsy": self.count_drowsy, "email": email})
+            else:
+                self.state_tracker["start_time"] = time.perf_counter()
+                self.state_tracker["DROWSY_TIME"] = 0.0
+                self.state_tracker["COLOR"] = self.GREEN
+                self.state_tracker["play_alarm"] = False
+
+            EAR_txt = f"EAR: {round(EAR, 2)}"
+            DROWSY_TIME_txt = f"DROWSY: {round(self.state_tracker['DROWSY_TIME'], 3)} Secs"
+            plot_text(frame, EAR_txt, self.EAR_txt_pos, self.state_tracker["COLOR"])
+            plot_text(frame, DROWSY_TIME_txt, DROWSY_TIME_txt_pos, self.state_tracker["COLOR"])
+            frame = plot_text(frame, f"Drowsy count: {self.count_drowsy}",(400,30), color=(0, 255, 0), thickness=2)
+
+        else:
+            self.state_tracker["start_time"] = time.perf_counter()
+            self.state_tracker["DROWSY_TIME"] = 0.0
+            self.state_tracker["COLOR"] = self.GREEN
+            self.state_tracker["play_alarm"] = False
+        
+        return frame, self.state_tracker["play_alarm"]

environment.yml

@@ -0,0 +1,129 @@
+name: CSIA_APS
+channels:
+  - anaconda
+  - conda-forge
+  - defaults
+dependencies:
+  - bzip2=1.0.8=he774522_0
+  - ca-certificates=2022.12.7=h5b45459_0
+  - certifi=2022.12.7=pyhd8ed1ab_0
+  - cmake=3.22.1=h9ad04ae_0
+  - console_shortcut=0.1.1=4
+  - dlib=19.24.0=py310he5227f5_0
+  - intel-openmp=2023.0.0=h57928b3_25922
+  - jpeg=9e=h8ffe710_2
+  - libblas=3.9.0=8_mkl
+  - libcblas=3.9.0=8_mkl
+  - libffi=3.4.2=hd77b12b_6
+  - liblapack=3.9.0=8_mkl
+  - libpng=1.6.37=h2a8f88b_0
+  - libuv=1.40.0=he774522_0
+  - lz4-c=1.9.3=h2bbff1b_1
+  - mkl=2020.4=hb70f87d_311
+  - openssl=1.1.1s=h2bbff1b_0
+  - pip=22.3.1=py310haa95532_0
+  - python=3.10.9=h966fe2a_0
+  - python_abi=3.10=2_cp310
+  - setuptools=65.6.3=py310haa95532_0
+  - sqlite=3.40.1=h2bbff1b_0
+  - tk=8.6.12=h2bbff1b_0
+  - vc=14.2=h21ff451_1
+  - vs2015_runtime=14.27.29016=h5e58377_2
+  - wheel=0.37.1=pyhd3eb1b0_0
+  - wincertstore=0.2=py310haa95532_2
+  - xz=5.2.10=h8cc25b3_1
+  - zlib=1.2.13=h8cc25b3_0
+  - zstd=1.5.2=h19a0ad4_0
+  - pip:
+    - absl-py==1.4.0
+    - aioice==0.7.6
+    - aiortc==1.4.0
+    - altair==4.2.2
+    - attrs==22.2.0
+    - av==10.0.0
+    - blinker==1.5
+    - cachetools==5.3.0
+    - cffi==1.15.1
+    - charset-normalizer==3.0.1
+    - click==8.1.3
+    - colorama==0.4.6
+    - contourpy==1.0.7
+    - cryptography==38.0.4
+    - cycler==0.11.0
+    - decorator==5.1.1
+    - deprecated==1.2.13
+    - dnspython==2.3.0
+    - entrypoints==0.4
+    - flatbuffers==23.1.21
+    - fonttools==4.38.0
+    - gcloud==0.18.3
+    - gitdb==4.0.10
+    - gitpython==3.1.30
+    - google-crc32c==1.5.0
+    - googleapis-common-protos==1.58.0
+    - httplib2==0.21.0
+    - idna==3.4
+    - importlib-metadata==6.0.0
+    - imutils==0.5.4
+    - jinja2==3.1.2
+    - jsonschema==4.17.3
+    - jwcrypto==1.4.2
+    - kiwisolver==1.4.4
+    - markdown-it-py==2.1.0
+    - markupsafe==2.1.2
+    - matplotlib==3.6.3
+    - mdurl==0.1.2
+    - mediapipe==0.9.1.0
+    - netifaces==0.11.0
+    - numpy==1.24.1
+    - oauth2client==4.1.3
+    - opencv-contrib-python==4.7.0.68
+    - opencv-python==4.7.0.68
+    - packaging==23.0
+    - pandas==1.5.3
+    - pillow==9.4.0
+    - protobuf==3.20.3
+    - pyarrow==11.0.0
+    - pyasn1==0.4.8
+    - pyasn1-modules==0.2.8
+    - pycparser==2.21
+    - pycryptodome==3.17
+    - pydeck==0.8.0
+    - pydub==0.25.1
+    - pyee==9.0.4
+    - pygments==2.14.0
+    - pylibsrtp==0.8.0
+    - pymongo==4.3.3
+    - pympler==1.0.1
+    - pyopenssl==23.0.0
+    - pyparsing==3.0.9
+    - pyrebase4==4.6.0
+    - pyrsistent==0.19.3
+    - python-dateutil==2.8.2
+    - python-jwt==4.0.0
+    - pytz==2022.7.1
+    - pytz-deprecation-shim==0.1.0.post0
+    - requests==2.28.2
+    - requests-toolbelt==0.10.1
+    - rich==13.3.1
+    - rsa==4.9
+    - scipy==1.10.0
+    - semver==2.13.0
+    - six==1.16.0
+    - smmap==5.0.0
+    - streamlit==1.17.0
+    - streamlit-nested-layout==0.1.1
+    - streamlit-option-menu==0.3.2
+    - streamlit-webrtc==0.44.2
+    - toml==0.10.2
+    - toolz==0.12.0
+    - tornado==6.2
+    - typing-extensions==4.4.0
+    - tzdata==2022.7
+    - tzlocal==4.2
+    - urllib3==1.26.14
+    - validators==0.20.0
+    - watchdog==2.2.1
+    - wrapt==1.14.1
+    - zipp==3.12.0
+prefix: C:\ProgramData\Anaconda3\envs\CSIA_APS

packages.txt

@@ -0,0 +1 @@
+cmake

requirements.txt

@@ -0,0 +1,94 @@
+absl-py==1.4.0
+aioice==0.7.6
+aiortc==1.4.0
+altair==4.2.2
+attrs==22.2.0
+av==10.0.0
+blinker==1.5
+cachetools==5.3.0
+certifi==2022.12.7
+cffi==1.15.1
+charset-normalizer==3.0.1
+click==8.1.3
+colorama==0.4.6
+contourpy==1.0.7
+cryptography==38.0.4
+cycler==0.11.0
+decorator==5.1.1
+Deprecated==1.2.13
+dlib
+dnspython==2.3.0
+entrypoints==0.4
+flatbuffers==23.1.21
+fonttools==4.38.0
+gcloud==0.18.3
+gitdb==4.0.10
+GitPython==3.1.30
+google-crc32c==1.5.0
+googleapis-common-protos==1.58.0
+httplib2==0.21.0
+idna==3.4
+importlib-metadata==6.0.0
+imutils==0.5.4
+Jinja2==3.1.2
+jsonschema==4.17.3
+jwcrypto==1.4.2
+kiwisolver==1.4.4
+markdown-it-py==2.1.0
+MarkupSafe==2.1.2
+matplotlib==3.6.3
+mdurl==0.1.2
+mediapipe==0.9.1.0
+netifaces==0.11.0
+numpy==1.24.1
+oauth2client==4.1.3
+opencv-contrib-python==4.7.0.68
+opencv-python==4.7.0.68
+packaging==23.0
+pandas==1.5.3
+Pillow==9.4.0
+protobuf==3.20.3
+pyarrow==11.0.0
+pyasn1==0.4.8
+pyasn1-modules==0.2.8
+pycparser==2.21
+pycryptodome==3.17
+pydeck==0.8.0
+pydub==0.25.1
+pyee==9.0.4
+Pygments==2.14.0
+pylibsrtp==0.8.0
+pymongo==4.3.3
+Pympler==1.0.1
+pyOpenSSL==23.0.0
+pyparsing==3.0.9
+Pyrebase4==4.6.0
+pyrsistent==0.19.3
+python-dateutil==2.8.2
+python-jwt==4.0.0
+pytz==2022.7.1
+pytz-deprecation-shim==0.1.0.post0
+requests==2.28.2
+requests-toolbelt==0.10.1
+rich==13.3.1
+rsa==4.9
+scipy==1.10.0
+semver==2.13.0
+six==1.16.0
+smmap==5.0.0
+streamlit==1.17.0
+streamlit-nested-layout==0.1.1
+streamlit-option-menu==0.3.2
+streamlit-webrtc==0.44.2
+toml==0.10.2
+toolz==0.12.0
+tornado==6.2
+typing_extensions==4.4.0
+tzdata==2022.7
+tzlocal==4.2
+urllib3==1.26.14
+validators==0.20.0
+watchdog==2.2.1
+wincertstore==0.2
+wrapt==1.14.1
+zipp==3.12.0