Nov 21: [FIX] Bug Fixed 'face_recognized_attendance_login'

face_recognized_attendance_login/README.rst

@@ -8,14 +8,7 @@ Face Recognized Attendance Login
 
 Configuration
 =============
-Opencv [version: 4.8.1.78]
+Please ensure the camera access.
-numpy  [version: 1.26.2]
-Pillow [version: 9.0.1]
-cmake  [version: 3.27.7]
-dlib [version: 19.24.2]
-face-recognition [version: 1.2.3]
-
-Please ensure the camera access also.
 
 Installation
 ============

face_recognized_attendance_login/__init__.py

@@ -20,4 +20,3 @@
 #
 #############################################################################
 from . import controllers
-

face_recognized_attendance_login/__manifest__.py

@@ -21,7 +21,7 @@
 #############################################################################
 {
     'name': 'Face Recognized Attendance Login',
-    'version': '17.0.1.0.0',
+    'version': '17.0.2.0.0',
     'category': 'Human Resources',
     'summary': """Mark the attendance of employee by recognizing their face""",
     'description': """This module introduces a face recognition system in the 
@@ -32,9 +32,12 @@
     'maintainer': 'Cybrosys Techno Solutions',
     'website': "https://www.cybrosys.com",
     'depends': ['base', 'mail', 'hr_attendance'],
-    'external_dependencies': {
+    'assets': {
-        'python': ['face-recognition', 'cmake', 'dlib', 'PIL',
+        'hr_attendance.assets_public_attendance': [
-                   'numpy', 'opencv-python'],
+            'face_recognized_attendance_login/static/src/js/face-api.min.js',
+            'face_recognized_attendance_login/static/src/xml/face_recognition_template.xml',
+            'face_recognized_attendance_login/static/src/js/face_recognition.js',
+        ]
     },
     'images': ['static/description/banner.jpg'],
     'license': 'LGPL-3',

face_recognized_attendance_login/controllers/main.py

@@ -19,21 +19,6 @@
 #    If not, see <http://www.gnu.org/licenses/>.
 #
 #############################################################################
-import base64
-
-import PIL
-import cmake
-import cv2
-import dlib
-import face_recognition
-from io import BytesIO
-
-import numpy
-import numpy as np
-import os
-from PIL import Image
-import time
-from odoo.exceptions import AccessError
 from odoo.http import request
 from odoo.addons.hr_attendance.controllers.main import HrAttendance
 from odoo import _, http
@@ -42,112 +27,8 @@ from odoo import _, http
 class HrAttendances(HrAttendance):
     """Controllers Overrides to add the Face detection feature"""
 
-    @http.route('/hr_attendance/attendance_employee_data', type="json",
+    @http.route('/get_image', type="json",
                 auth="public")
-    def employee_attendance_data(self, token, employee_id):
+    def get_image(self,employee_id):
-        """In this Code section the face detection is added to
+        image = request.env['hr.employee'].sudo().browse(employee_id).image_1920
-        employee_attendance_data"""
+        return image
-
-
-        company = self._get_company(token)
-        employee_pic = request.env['hr.employee'].sudo().browse(
-            employee_id).image_1920
-        sub_folder = os.path.abspath(os.path.dirname(__file__))
-        project_folder = os.path.abspath(os.path.join(sub_folder, os.pardir))
-        eye_cascade_path = os.path.join(project_folder, 'data',
-                                        'haarcascade_eye_tree_eyeglasses.xml')
-        face_cascade_path = os.path.join(project_folder, 'data',
-                                         'haarcascade_frontalface_default.xml')
-        face_cascade = cv2.CascadeClassifier(face_cascade_path)
-        eye_cascade = cv2.CascadeClassifier(eye_cascade_path)
-        binary_data = base64.b64decode(employee_pic)
-        image_bytes = BytesIO(binary_data)
-        pil_image = Image.open(image_bytes)
-        np_image = np.array(pil_image)
-        img = cv2.cvtColor(np_image, cv2.COLOR_BGR2RGB)
-        # Extract features from the referenced eye(s)
-        orb = cv2.ORB_create()
-        referenced_key_points, referenced_descriptors = orb.detectAndCompute(
-            img, None)
-        encoded_face = face_recognition.face_encodings(img)
-        start_time = time.time()
-
-        camera_time = 0
-        face_recognized = 0
-        eyes_match_fail_index = 0
-        eyes_match_index = 0
-        cap = cv2.VideoCapture(0)
-        ret, frame = cap.read()
-
-        while ret and camera_time < 9:
-            ret, frame = cap.read()
-            gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
-            gray = cv2.bilateralFilter(gray, 5, 1, 1)
-            faces = face_cascade.detectMultiScale(gray, 1.3, 5,
-                                                  minSize=(200, 200))
-
-            if len(faces) == 1:
-                for (x, y, w, h) in faces:
-                    frame = cv2.rectangle(frame, (x, y), (x + w, y + h),
-                                          (0, 255, 0), 2)
-                    eyes = eye_cascade.detectMultiScale(gray, scaleFactor=1.3,
-                                                        minNeighbors=5)
-                    current_key_points, current_descriptors = orb.detectAndCompute(
-                        gray, None)
-
-                    bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)
-                    matches = bf.match(referenced_descriptors,
-                                       current_descriptors)
-                    good_matches = [m for m in matches if m.distance < 70]
-
-                    if len(good_matches) >= 5:
-                        eyes_match_index += 1
-                    else:
-                        eyes_match_fail_index += 1
-
-                    if len(eyes) == 0:
-                        img_frame = cv2.resize(frame, (0, 0), None, 0.25, 0.25)
-                        img_frame = cv2.cvtColor(img_frame, cv2.COLOR_BGR2RGB)
-                        face_current_frame = face_recognition.face_locations(
-                            img_frame)
-                        encode_current_frame = face_recognition.face_encodings(
-                            img_frame, face_current_frame)
-
-                        for encode_face, face_loc in zip(encode_current_frame,
-                                                         face_current_frame):
-                            face_matches = face_recognition.compare_faces(
-                                encoded_face, encode_face)
-                            face_distance = face_recognition.face_distance(
-                                encoded_face, encode_face)
-                            match_index = np.argmin(face_distance)
-                            elapsed_time = time.time() - start_time
-
-                            if face_matches[
-                                match_index] and eyes_match_index > eyes_match_fail_index:
-                                face_recognized = 1
-                                if elapsed_time > 6:
-                                    time.sleep(1)
-                            else:
-                                face_recognized = 0
-            # cv2.imshow('frame', frame)
-            # the imshow is removed from here because it is not needed anymore
-            #  Also it is making error while running the code second time.
-                cv2.waitKey(0)
-            else:
-                # Reset the counters and related variables when no face is
-                # detected
-                camera_time += 1
-                eyes_match_index = 0
-                eyes_match_fail_index = 0
-        cap.release()
-        cv2.destroyAllWindows()
-        camera_time = 0
-        if company and face_recognized != 1:
-            raise AccessError(
-                _("Sorry, Can't recognize you. Please try again"))
-        else:
-            employee = request.env['hr.employee'].sudo().browse(employee_id)
-            if employee.company_id == company:
-                return self._get_employee_info_response(employee)
-        cv2.waitKey(0)
-        return {}

face_recognized_attendance_login/doc/RELEASE_NOTES.md

@@ -3,3 +3,8 @@
 #### Version 17.0.1.0.0
 ##### ADD
 - Initial Commit for Face Recognized Attendance Login
+
+#### 19.11.2024
+#### Version 17.0.2.0.0
+##### ADD
+- Update

face_recognized_attendance_login/static/src/js/face_recognition.js

@@ -0,0 +1,209 @@
+/** @odoo-module **/
+import kiosk from "@hr_attendance/public_kiosk/public_kiosk_app";
+import { patch } from "@web/core/utils/patch";
+import { useService } from "@web/core/utils/hooks";
+import { useRef, useState } from "@odoo/owl";
+import { _t } from "@web/core/l10n/translation";
+const MODEL_URL = '/face_recognized_attendance_login/static/src/js/weights';
+faceapi.nets.ssdMobilenetv1.loadFromUri(MODEL_URL)
+faceapi.nets.faceLandmark68Net.loadFromUri(MODEL_URL)
+faceapi.nets.faceRecognitionNet.loadFromUri(MODEL_URL)
+faceapi.nets.tinyFaceDetector.load(MODEL_URL),
+faceapi.nets.faceLandmark68TinyNet.load(MODEL_URL),
+faceapi.nets.faceExpressionNet.load(MODEL_URL),
+faceapi.nets.ageGenderNet.load(MODEL_URL)
+
+patch(kiosk.kioskAttendanceApp.prototype, {
+    setup() {
+        super.setup(...arguments);
+        this.orm = useService("orm");
+        this.employee_image = useRef("employee_image");
+        this.video = useRef("video");
+        this.notification = useService("notification");
+        this.state.employee = false;
+        this.state.verifiedEmployeeId = null
+        this.isRecognitionActive = false;
+        this.currentStream = null;
+        this.faceMatcher = null;
+        this.noMatchCount = 0;
+    },
+
+    async loadImage(employeeId) {
+        var image = await this.rpc("/get_image", {
+            employee_id: employeeId
+        })
+        this.have_image = image
+        const employee_image = this.employee_image.el
+        employee_image.src = "data:image/jpeg;base64," + image
+        this.currentVerificationId = employeeId;
+    },
+
+    async startWebcam() {
+        const video = this.video.el;
+        if (video) {
+            video.srcObject = null;
+            video.style.display = 'block';
+        }
+        this.isRecognitionActive = true;
+        this.state.employee = false;
+        this.noMatchCount = 0; // Reset no match counter
+        this.faceMatcher = null; // Reset faceMatcher
+
+        try {
+            const stream = await navigator.mediaDevices.getUserMedia({
+                video: true,
+                audio: false
+            });
+            this.currentStream = stream;
+            video.srcObject = stream;
+            await new Promise(resolve => {
+                video.onloadedmetadata = resolve;
+            });
+            await this.faceRecognition(video);
+        } catch (error) {
+            console.error("Error starting webcam:", error);
+            this.isRecognitionActive = false;
+            this.notification.add(_t("Your browser does not support camera access. Please try a different browser."), {
+                title : "Access Denied !",
+                type: "danger",
+            });
+        }
+    },
+
+    async getLabeledFaceDescriptions() {
+        const employee_image = this.employee_image.el;
+        const detections = await faceapi
+            .detectSingleFace(employee_image)
+            .withFaceLandmarks()
+            .withFaceExpressions()
+            .withFaceDescriptor();
+        return detections;
+    },
+
+    stopRecognition(video, canvas) {
+        this.isRecognitionActive = false;
+        if (this.currentStream) {
+            this.currentStream.getTracks().forEach(track => track.stop());
+            this.currentStream = null;
+        }
+        if (video) {
+            video.srcObject = null;
+            video.style.display = 'none';
+        }
+        if (canvas && canvas.parentNode) {
+            canvas.remove();
+        }
+        const modal = document.getElementById('WebCamModal');
+        if (modal) {
+            modal.style.display = 'none';
+        }
+        this.faceMatcher = null;
+        this.noMatchCount = 0;
+    },
+
+    async faceRecognition(video) {
+        if (!this.isRecognitionActive) return;
+        if (!this.faceMatcher) {
+            const labeledFaceDescriptors = await this.getLabeledFaceDescriptions();
+            if (labeledFaceDescriptors && labeledFaceDescriptors.descriptor) {
+                this.faceMatcher = new faceapi.FaceMatcher([labeledFaceDescriptors.descriptor]);
+            } else {
+                console.error("Could not get face descriptor from reference image");
+                this.notification.add(_t("Failed to initialize face recognition, Please upload a new, properly formatted image."), {
+                    type: "danger",
+                    title: "Image detection failed!",
+                });
+                this.stopRecognition(video);
+                return;
+            }
+        }
+        const canvas = faceapi.createCanvasFromMedia(video);
+        document.body.append(canvas);
+        canvas.style.display = 'none'
+        const displaySize = { width: video.videoWidth, height: video.videoHeight };
+        faceapi.matchDimensions(canvas, displaySize);
+        const processFrame = async () => {
+            if (!this.isRecognitionActive) return;
+            try {
+                const detections = await faceapi
+                    .detectAllFaces(video)
+                    .withFaceLandmarks()
+                    .withFaceExpressions()
+                    .withFaceDescriptors();
+                if (detections.length === 0) {
+                    if (this.isRecognitionActive) {
+                        requestAnimationFrame(processFrame);
+                    }
+                    return;
+                }
+                for (const detection of detections) {
+                    const match = this.faceMatcher.findBestMatch(detection.descriptor);
+                    if (match._distance < 0.4) {
+                        this.state.employee = true;
+                        this.state.verifiedEmployeeId = this.currentVerificationId;
+                        this.stopRecognition(video, canvas);
+                        return;
+                    } else {
+                        this.noMatchCount++;
+                        if (this.noMatchCount >= 3) {
+                            this.notification.add(_t("Sorry, cannot recognize you"), {
+                                title:"Recognition Failed ! ",
+                                type: "danger",
+                            });
+                            this.stopRecognition(video, canvas);
+                            return;
+                        }
+                    }
+                }
+                if (this.isRecognitionActive) {
+                    requestAnimationFrame(processFrame);
+                }
+            } catch (error) {
+                console.error("Face recognition error:", error);
+                this.stopRecognition(video, canvas);
+            }
+        };
+        processFrame();
+    },
+
+    async onManualSelection(employeeId, enteredPin) {
+        if (this.isRecognitionActive) {
+            this.stopRecognition(this.video.el);
+        }
+        await this.loadImage(employeeId);
+        if (this.have_image) {
+            const modal = document.getElementById('WebCamModal');
+            if (modal) {
+                modal.style.display = 'block';
+            }
+            await this.startWebcam();
+            const checkInterval = setInterval(() => {
+                if (this.state.employee && this.state.verifiedEmployeeId === employeeId) {
+                    clearInterval(checkInterval);
+                    this.rpc("manual_selection", {
+                        token: this.props.token,
+                        employee_id: employeeId,
+                        pin_code: enteredPin,
+                    }).then(result => {
+                        if (result && result.attendance) {
+                            this.employeeData = result;
+                            this.switchDisplay("greet");
+                        } else {
+                            if (enteredPin) {
+                                this.notification.add(_t("Wrong Pin"), {
+                                    type: "danger",
+                                });
+                            }
+                        }
+                    });
+                }
+            }, 500);
+        } else {
+            await this.popup.add(ErrorPopup, {
+                title: _t("Authentication failed"),
+                body: _t("Selected cashier has no image."),
+            });
+            location.reload();
+        }
+    },
+});

face_recognized_attendance_login/static/src/js/weights/age_gender_model-weights_manifest.json

@@ -0,0 +1,618 @@
+[
+  {
+    "weights": [
+      {
+        "name": "entry_flow/conv_in/filters",
+        "shape": [
+          3,
+          3,
+          3,
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.005431825039433498,
+          "min": -0.7441600304023892
+        }
+      },
+      {
+        "name": "entry_flow/conv_in/bias",
+        "shape": [
+          32
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "entry_flow/reduction_block_0/separable_conv0/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          32,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.005691980614381678,
+          "min": -0.6090419257388395
+        }
+      },
+      {
+        "name": "entry_flow/reduction_block_0/separable_conv0/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          32,
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.009089225881239947,
+          "min": -1.1179747833925135
+        }
+      },
+      {
+        "name": "entry_flow/reduction_block_0/separable_conv0/bias",
+        "shape": [
+          64
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "entry_flow/reduction_block_0/separable_conv1/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          64,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.00683894624897078,
+          "min": -0.8138346036275228
+        }
+      },
+      {
+        "name": "entry_flow/reduction_block_0/separable_conv1/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          64,
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.011632566358528886,
+          "min": -1.3028474321552352
+        }
+      },
+      {
+        "name": "entry_flow/reduction_block_0/separable_conv1/bias",
+        "shape": [
+          64
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "entry_flow/reduction_block_0/expansion_conv/filters",
+        "shape": [
+          1,
+          1,
+          32,
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.010254812240600587,
+          "min": -0.9229331016540528
+        }
+      },
+      {
+        "name": "entry_flow/reduction_block_0/expansion_conv/bias",
+        "shape": [
+          64
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "entry_flow/reduction_block_1/separable_conv0/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          64,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0052509616403018725,
+          "min": -0.6406173201168285
+        }
+      },
+      {
+        "name": "entry_flow/reduction_block_1/separable_conv0/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          64,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.010788509424994973,
+          "min": -1.4564487723743214
+        }
+      },
+      {
+        "name": "entry_flow/reduction_block_1/separable_conv0/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "entry_flow/reduction_block_1/separable_conv1/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.00553213918910307,
+          "min": -0.7025816770160899
+        }
+      },
+      {
+        "name": "entry_flow/reduction_block_1/separable_conv1/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.013602388606351965,
+          "min": -1.6186842441558837
+        }
+      },
+      {
+        "name": "entry_flow/reduction_block_1/separable_conv1/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "entry_flow/reduction_block_1/expansion_conv/filters",
+        "shape": [
+          1,
+          1,
+          64,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.007571851038465313,
+          "min": -1.158493208885193
+        }
+      },
+      {
+        "name": "entry_flow/reduction_block_1/expansion_conv/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "middle_flow/main_block_0/separable_conv0/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.005766328409606335,
+          "min": -0.6688940955143349
+        }
+      },
+      {
+        "name": "middle_flow/main_block_0/separable_conv0/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.012136116214826995,
+          "min": -1.5776951079275094
+        }
+      },
+      {
+        "name": "middle_flow/main_block_0/separable_conv0/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "middle_flow/main_block_0/separable_conv1/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.004314773222979377,
+          "min": -0.5652352922102984
+        }
+      },
+      {
+        "name": "middle_flow/main_block_0/separable_conv1/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.01107162026798024,
+          "min": -1.2400214700137868
+        }
+      },
+      {
+        "name": "middle_flow/main_block_0/separable_conv1/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "middle_flow/main_block_0/separable_conv2/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0036451735917259667,
+          "min": -0.4848080876995536
+        }
+      },
+      {
+        "name": "middle_flow/main_block_0/separable_conv2/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.008791744942758598,
+          "min": -1.134135097615859
+        }
+      },
+      {
+        "name": "middle_flow/main_block_0/separable_conv2/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "middle_flow/main_block_1/separable_conv0/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.004915751896652521,
+          "min": -0.6095532351849126
+        }
+      },
+      {
+        "name": "middle_flow/main_block_1/separable_conv0/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.010868691463096469,
+          "min": -1.3368490499608656
+        }
+      },
+      {
+        "name": "middle_flow/main_block_1/separable_conv0/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "middle_flow/main_block_1/separable_conv1/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.005010117269029804,
+          "min": -0.6012140722835765
+        }
+      },
+      {
+        "name": "middle_flow/main_block_1/separable_conv1/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.010311148213405235,
+          "min": -1.3816938605963016
+        }
+      },
+      {
+        "name": "middle_flow/main_block_1/separable_conv1/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "middle_flow/main_block_1/separable_conv2/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.004911523706772748,
+          "min": -0.7367285560159123
+        }
+      },
+      {
+        "name": "middle_flow/main_block_1/separable_conv2/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.008976466047997568,
+          "min": -1.2207993825276693
+        }
+      },
+      {
+        "name": "middle_flow/main_block_1/separable_conv2/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "exit_flow/reduction_block/separable_conv0/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.005074804436926748,
+          "min": -0.7104726211697447
+        }
+      },
+      {
+        "name": "exit_flow/reduction_block/separable_conv0/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          256
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.011453078307357489,
+          "min": -1.4545409450344011
+        }
+      },
+      {
+        "name": "exit_flow/reduction_block/separable_conv0/bias",
+        "shape": [
+          256
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "exit_flow/reduction_block/separable_conv1/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          256,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.007741751390344957,
+          "min": -1.1380374543807086
+        }
+      },
+      {
+        "name": "exit_flow/reduction_block/separable_conv1/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          256,
+          256
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.011347713189966538,
+          "min": -1.497898141075583
+        }
+      },
+      {
+        "name": "exit_flow/reduction_block/separable_conv1/bias",
+        "shape": [
+          256
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "exit_flow/reduction_block/expansion_conv/filters",
+        "shape": [
+          1,
+          1,
+          128,
+          256
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.006717281014311547,
+          "min": -0.8329428457746318
+        }
+      },
+      {
+        "name": "exit_flow/reduction_block/expansion_conv/bias",
+        "shape": [
+          256
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "exit_flow/separable_conv/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          256,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0027201742518181892,
+          "min": -0.3237007359663645
+        }
+      },
+      {
+        "name": "exit_flow/separable_conv/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          256,
+          512
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.010076364348916447,
+          "min": -1.330080094056971
+        }
+      },
+      {
+        "name": "exit_flow/separable_conv/bias",
+        "shape": [
+          512
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "fc/age/weights",
+        "shape": [
+          512,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.008674054987290326,
+          "min": -1.2664120281443876
+        }
+      },
+      {
+        "name": "fc/age/bias",
+        "shape": [
+          1
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "fc/gender/weights",
+        "shape": [
+          512,
+          2
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0029948226377075793,
+          "min": -0.34140978069866407
+        }
+      },
+      {
+        "name": "fc/gender/bias",
+        "shape": [
+          2
+        ],
+        "dtype": "float32"
+      }
+    ],
+    "paths": [
+      "age_gender_model-shard1"
+    ]
+  }
+]

face_recognized_attendance_login/static/src/js/weights/face_expression_model-weights_manifest.json

@@ -0,0 +1,606 @@
+[
+  {
+    "weights": [
+      {
+        "name": "dense0/conv0/filters",
+        "shape": [
+          3,
+          3,
+          3,
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0057930146946626555,
+          "min": -0.7125408074435067
+        }
+      },
+      {
+        "name": "dense0/conv0/bias",
+        "shape": [
+          32
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "dense0/conv1/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          32,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.006473719839956246,
+          "min": -0.6408982641556684
+        }
+      },
+      {
+        "name": "dense0/conv1/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          32,
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.010509579321917366,
+          "min": -1.408283629136927
+        }
+      },
+      {
+        "name": "dense0/conv1/bias",
+        "shape": [
+          32
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "dense0/conv2/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          32,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.005666389652326995,
+          "min": -0.7252978754978554
+        }
+      },
+      {
+        "name": "dense0/conv2/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          32,
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.010316079270605948,
+          "min": -1.1760330368490781
+        }
+      },
+      {
+        "name": "dense0/conv2/bias",
+        "shape": [
+          32
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "dense0/conv3/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          32,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0063220320963392074,
+          "min": -0.853474333005793
+        }
+      },
+      {
+        "name": "dense0/conv3/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          32,
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.010322785377502442,
+          "min": -1.4658355236053466
+        }
+      },
+      {
+        "name": "dense0/conv3/bias",
+        "shape": [
+          32
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "dense1/conv0/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          32,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0042531527724920535,
+          "min": -0.5741756242864272
+        }
+      },
+      {
+        "name": "dense1/conv0/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          32,
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.010653339647779278,
+          "min": -1.1825207009035
+        }
+      },
+      {
+        "name": "dense1/conv0/bias",
+        "shape": [
+          64
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "dense1/conv1/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          64,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.005166931012097527,
+          "min": -0.6355325144879957
+        }
+      },
+      {
+        "name": "dense1/conv1/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          64,
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.011478300188101974,
+          "min": -1.3888743227603388
+        }
+      },
+      {
+        "name": "dense1/conv1/bias",
+        "shape": [
+          64
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "dense1/conv2/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          64,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.006144821410085641,
+          "min": -0.8479853545918185
+        }
+      },
+      {
+        "name": "dense1/conv2/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          64,
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.010541967317169788,
+          "min": -1.3809977185492421
+        }
+      },
+      {
+        "name": "dense1/conv2/bias",
+        "shape": [
+          64
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "dense1/conv3/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          64,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.005769844849904378,
+          "min": -0.686611537138621
+        }
+      },
+      {
+        "name": "dense1/conv3/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          64,
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.010939095534530341,
+          "min": -1.2689350820055196
+        }
+      },
+      {
+        "name": "dense1/conv3/bias",
+        "shape": [
+          64
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "dense2/conv0/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          64,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0037769308277204924,
+          "min": -0.40790852939381317
+        }
+      },
+      {
+        "name": "dense2/conv0/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          64,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.01188667194516051,
+          "min": -1.4382873053644218
+        }
+      },
+      {
+        "name": "dense2/conv0/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "dense2/conv1/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.006497045825509464,
+          "min": -0.8381189114907208
+        }
+      },
+      {
+        "name": "dense2/conv1/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.011632198913424622,
+          "min": -1.3377028750438316
+        }
+      },
+      {
+        "name": "dense2/conv1/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "dense2/conv2/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.005947182225246056,
+          "min": -0.7969224181829715
+        }
+      },
+      {
+        "name": "dense2/conv2/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.011436844339557722,
+          "min": -1.4524792311238306
+        }
+      },
+      {
+        "name": "dense2/conv2/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "dense2/conv3/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.006665432686899222,
+          "min": -0.8998334127313949
+        }
+      },
+      {
+        "name": "dense2/conv3/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.01283421422920975,
+          "min": -1.642779421338848
+        }
+      },
+      {
+        "name": "dense2/conv3/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "dense3/conv0/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.004711699953266218,
+          "min": -0.6737730933170692
+        }
+      },
+      {
+        "name": "dense3/conv0/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          256
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.010955964817720302,
+          "min": -1.3914075318504784
+        }
+      },
+      {
+        "name": "dense3/conv0/bias",
+        "shape": [
+          256
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "dense3/conv1/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          256,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.00554193468654857,
+          "min": -0.7149095745647656
+        }
+      },
+      {
+        "name": "dense3/conv1/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          256,
+          256
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.016790372250126858,
+          "min": -2.484975093018775
+        }
+      },
+      {
+        "name": "dense3/conv1/bias",
+        "shape": [
+          256
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "dense3/conv2/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          256,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.006361540626077091,
+          "min": -0.8142772001378676
+        }
+      },
+      {
+        "name": "dense3/conv2/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          256,
+          256
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.01777329678628959,
+          "min": -1.7062364914838006
+        }
+      },
+      {
+        "name": "dense3/conv2/bias",
+        "shape": [
+          256
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "dense3/conv3/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          256,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.006900275922289082,
+          "min": -0.8625344902861353
+        }
+      },
+      {
+        "name": "dense3/conv3/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          256,
+          256
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.015449936717164282,
+          "min": -1.9003422162112067
+        }
+      },
+      {
+        "name": "dense3/conv3/bias",
+        "shape": [
+          256
+        ],
+        "dtype": "float32"
+      },
+      {
+        "name": "fc/weights",
+        "shape": [
+          256,
+          7
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.004834276554631252,
+          "min": -0.7203072066400565
+        }
+      },
+      {
+        "name": "fc/bias",
+        "shape": [
+          7
+        ],
+        "dtype": "float32"
+      }
+    ],
+    "paths": [
+      "face_expression_model-shard1"
+    ]
+  }
+]

face_recognized_attendance_login/static/src/js/weights/face_landmark_68_model-weights_manifest.json

@@ -0,0 +1,691 @@
+[
+  {
+    "weights": [
+      {
+        "name": "dense0/conv0/filters",
+        "shape": [
+          3,
+          3,
+          3,
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.004853619781194949,
+          "min": -0.5872879935245888
+        }
+      },
+      {
+        "name": "dense0/conv0/bias",
+        "shape": [
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.004396426443960153,
+          "min": -0.7298067896973853
+        }
+      },
+      {
+        "name": "dense0/conv1/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          32,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.00635151559231328,
+          "min": -0.5589333721235686
+        }
+      },
+      {
+        "name": "dense0/conv1/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          32,
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.009354315552057004,
+          "min": -1.2628325995276957
+        }
+      },
+      {
+        "name": "dense0/conv1/bias",
+        "shape": [
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0029380727048013726,
+          "min": -0.5846764682554731
+        }
+      },
+      {
+        "name": "dense0/conv2/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          32,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0049374802439820535,
+          "min": -0.6171850304977566
+        }
+      },
+      {
+        "name": "dense0/conv2/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          32,
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.009941946758943446,
+          "min": -1.3421628124573652
+        }
+      },
+      {
+        "name": "dense0/conv2/bias",
+        "shape": [
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0030300481062309416,
+          "min": -0.5272283704841838
+        }
+      },
+      {
+        "name": "dense0/conv3/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          32,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.005672684837790097,
+          "min": -0.7431217137505026
+        }
+      },
+      {
+        "name": "dense0/conv3/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          32,
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.010712201455060173,
+          "min": -1.5639814124387852
+        }
+      },
+      {
+        "name": "dense0/conv3/bias",
+        "shape": [
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0030966934035806097,
+          "min": -0.3839899820439956
+        }
+      },
+      {
+        "name": "dense1/conv0/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          32,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0039155554537679636,
+          "min": -0.48161332081345953
+        }
+      },
+      {
+        "name": "dense1/conv0/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          32,
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.01023082966898002,
+          "min": -1.094698774580862
+        }
+      },
+      {
+        "name": "dense1/conv0/bias",
+        "shape": [
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0027264176630506327,
+          "min": -0.3871513081531898
+        }
+      },
+      {
+        "name": "dense1/conv1/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          64,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.004583378632863362,
+          "min": -0.5454220573107401
+        }
+      },
+      {
+        "name": "dense1/conv1/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          64,
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.00915846403907327,
+          "min": -1.117332612766939
+        }
+      },
+      {
+        "name": "dense1/conv1/bias",
+        "shape": [
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.003091680419211294,
+          "min": -0.5966943209077797
+        }
+      },
+      {
+        "name": "dense1/conv2/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          64,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.005407439727409214,
+          "min": -0.708374604290607
+        }
+      },
+      {
+        "name": "dense1/conv2/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          64,
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.00946493943532308,
+          "min": -1.2399070660273235
+        }
+      },
+      {
+        "name": "dense1/conv2/bias",
+        "shape": [
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.004409168514550901,
+          "min": -0.9788354102303
+        }
+      },
+      {
+        "name": "dense1/conv3/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          64,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.004478132958505668,
+          "min": -0.6493292789833219
+        }
+      },
+      {
+        "name": "dense1/conv3/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          64,
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.011063695888893277,
+          "min": -1.2501976354449402
+        }
+      },
+      {
+        "name": "dense1/conv3/bias",
+        "shape": [
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.003909627596537272,
+          "min": -0.6646366914113363
+        }
+      },
+      {
+        "name": "dense2/conv0/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          64,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.003213915404151468,
+          "min": -0.3374611174359041
+        }
+      },
+      {
+        "name": "dense2/conv0/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          64,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.010917326048308728,
+          "min": -1.4520043644250609
+        }
+      },
+      {
+        "name": "dense2/conv0/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.002800439152063108,
+          "min": -0.38085972468058266
+        }
+      },
+      {
+        "name": "dense2/conv1/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0050568851770139206,
+          "min": -0.6927932692509071
+        }
+      },
+      {
+        "name": "dense2/conv1/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.01074961213504567,
+          "min": -1.3222022926106174
+        }
+      },
+      {
+        "name": "dense2/conv1/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0030654204242369708,
+          "min": -0.5487102559384177
+        }
+      },
+      {
+        "name": "dense2/conv2/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.00591809165244009,
+          "min": -0.917304206128214
+        }
+      },
+      {
+        "name": "dense2/conv2/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.01092823346455892,
+          "min": -1.366029183069865
+        }
+      },
+      {
+        "name": "dense2/conv2/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.002681120470458386,
+          "min": -0.36463238398234055
+        }
+      },
+      {
+        "name": "dense2/conv3/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0048311497650894465,
+          "min": -0.5797379718107336
+        }
+      },
+      {
+        "name": "dense2/conv3/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.011227761062921263,
+          "min": -1.4483811771168429
+        }
+      },
+      {
+        "name": "dense2/conv3/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0034643323982463162,
+          "min": -0.3360402426298927
+        }
+      },
+      {
+        "name": "dense3/conv0/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.003394978887894574,
+          "min": -0.49227193874471326
+        }
+      },
+      {
+        "name": "dense3/conv0/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          256
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.010051267287310432,
+          "min": -1.2765109454884247
+        }
+      },
+      {
+        "name": "dense3/conv0/bias",
+        "shape": [
+          256
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.003142924752889895,
+          "min": -0.4588670139219247
+        }
+      },
+      {
+        "name": "dense3/conv1/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          256,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.00448304671867221,
+          "min": -0.5872791201460595
+        }
+      },
+      {
+        "name": "dense3/conv1/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          256,
+          256
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.016063522357566685,
+          "min": -2.3613377865623026
+        }
+      },
+      {
+        "name": "dense3/conv1/bias",
+        "shape": [
+          256
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.00287135781026354,
+          "min": -0.47664539650374765
+        }
+      },
+      {
+        "name": "dense3/conv2/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          256,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.006002906724518421,
+          "min": -0.7923836876364315
+        }
+      },
+      {
+        "name": "dense3/conv2/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          256,
+          256
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.017087187019048954,
+          "min": -1.6061955797906016
+        }
+      },
+      {
+        "name": "dense3/conv2/bias",
+        "shape": [
+          256
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.003124481205846749,
+          "min": -0.46242321846531886
+        }
+      },
+      {
+        "name": "dense3/conv3/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          256,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.006576311588287353,
+          "min": -1.0193282961845398
+        }
+      },
+      {
+        "name": "dense3/conv3/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          256,
+          256
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.015590153955945782,
+          "min": -1.99553970636106
+        }
+      },
+      {
+        "name": "dense3/conv3/bias",
+        "shape": [
+          256
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.004453541601405424,
+          "min": -0.6546706154065973
+        }
+      },
+      {
+        "name": "fc/weights",
+        "shape": [
+          256,
+          136
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.010417488509533453,
+          "min": -1.500118345372817
+        }
+      },
+      {
+        "name": "fc/bias",
+        "shape": [
+          136
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0025084222648658005,
+          "min": 0.07683877646923065
+        }
+      }
+    ],
+    "paths": [
+      "face_landmark_68_model-shard1"
+    ]
+  }
+]

face_recognized_attendance_login/static/src/js/weights/face_landmark_68_tiny_model-weights_manifest.json

@@ -0,0 +1,397 @@
+[
+  {
+    "weights": [
+      {
+        "name": "dense0/conv0/filters",
+        "shape": [
+          3,
+          3,
+          3,
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.008194216092427571,
+          "min": -0.9423348506291708
+        }
+      },
+      {
+        "name": "dense0/conv0/bias",
+        "shape": [
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.006839508168837603,
+          "min": -0.8412595047670252
+        }
+      },
+      {
+        "name": "dense0/conv1/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          32,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.009194007106855804,
+          "min": -1.2779669878529567
+        }
+      },
+      {
+        "name": "dense0/conv1/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          32,
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0036026100317637128,
+          "min": -0.3170296827952067
+        }
+      },
+      {
+        "name": "dense0/conv1/bias",
+        "shape": [
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.000740380117706224,
+          "min": -0.06367269012273527
+        }
+      },
+      {
+        "name": "dense0/conv2/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          32,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 1,
+          "min": 0
+        }
+      },
+      {
+        "name": "dense0/conv2/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          32,
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 1,
+          "min": 0
+        }
+      },
+      {
+        "name": "dense0/conv2/bias",
+        "shape": [
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0037702228508743585,
+          "min": -0.6220867703942692
+        }
+      },
+      {
+        "name": "dense1/conv0/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          32,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0033707996209462483,
+          "min": -0.421349952618281
+        }
+      },
+      {
+        "name": "dense1/conv0/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          32,
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.014611541991140328,
+          "min": -1.8556658328748217
+        }
+      },
+      {
+        "name": "dense1/conv0/bias",
+        "shape": [
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.002832523046755323,
+          "min": -0.30307996600281956
+        }
+      },
+      {
+        "name": "dense1/conv1/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          64,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.006593170586754294,
+          "min": -0.6329443763284123
+        }
+      },
+      {
+        "name": "dense1/conv1/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          64,
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.012215249211180444,
+          "min": -1.6001976466646382
+        }
+      },
+      {
+        "name": "dense1/conv1/bias",
+        "shape": [
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.002384825547536214,
+          "min": -0.3028728445370992
+        }
+      },
+      {
+        "name": "dense1/conv2/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          64,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.005859645441466687,
+          "min": -0.7617539073906693
+        }
+      },
+      {
+        "name": "dense1/conv2/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          64,
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.013121426806730382,
+          "min": -1.7845140457153321
+        }
+      },
+      {
+        "name": "dense1/conv2/bias",
+        "shape": [
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0032247188044529336,
+          "min": -0.46435950784122243
+        }
+      },
+      {
+        "name": "dense2/conv0/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          64,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.002659512618008782,
+          "min": -0.32977956463308894
+        }
+      },
+      {
+        "name": "dense2/conv0/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          64,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.015499923743453681,
+          "min": -1.9839902391620712
+        }
+      },
+      {
+        "name": "dense2/conv0/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0032450980999890497,
+          "min": -0.522460794098237
+        }
+      },
+      {
+        "name": "dense2/conv1/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.005911862382701799,
+          "min": -0.792189559282041
+        }
+      },
+      {
+        "name": "dense2/conv1/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.021025861478319356,
+          "min": -2.2077154552235325
+        }
+      },
+      {
+        "name": "dense2/conv1/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.00349616945958605,
+          "min": -0.46149436866535865
+        }
+      },
+      {
+        "name": "dense2/conv2/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.008104994250278847,
+          "min": -1.013124281284856
+        }
+      },
+      {
+        "name": "dense2/conv2/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.029337059282789044,
+          "min": -3.5791212325002633
+        }
+      },
+      {
+        "name": "dense2/conv2/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0038808938334969913,
+          "min": -0.4230174278511721
+        }
+      },
+      {
+        "name": "fc/weights",
+        "shape": [
+          128,
+          136
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.014016061670639936,
+          "min": -1.8921683255363912
+        }
+      },
+      {
+        "name": "fc/bias",
+        "shape": [
+          136
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0029505149698724935,
+          "min": 0.088760145008564
+        }
+      }
+    ],
+    "paths": [
+      "face_landmark_68_tiny_model-shard1"
+    ]
+  }
+]

face_recognized_attendance_login/static/src/js/weights/mtcnn_model-weights_manifest.json

@@ -0,0 +1,402 @@
+[
+  {
+    "paths": [
+      "mtcnn_model-shard1"
+    ],
+    "weights": [
+      {
+        "dtype": "float32",
+        "name": "pnet/conv1/weights",
+        "shape": [
+          3,
+          3,
+          3,
+          10
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "pnet/conv1/bias",
+        "shape": [
+          10
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "pnet/prelu1_alpha",
+        "shape": [
+          10
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "pnet/conv2/weights",
+        "shape": [
+          3,
+          3,
+          10,
+          16
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "pnet/conv2/bias",
+        "shape": [
+          16
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "pnet/prelu2_alpha",
+        "shape": [
+          16
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "pnet/conv3/weights",
+        "shape": [
+          3,
+          3,
+          16,
+          32
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "pnet/conv3/bias",
+        "shape": [
+          32
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "pnet/prelu3_alpha",
+        "shape": [
+          32
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "pnet/conv4_1/weights",
+        "shape": [
+          1,
+          1,
+          32,
+          2
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "pnet/conv4_1/bias",
+        "shape": [
+          2
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "pnet/conv4_2/weights",
+        "shape": [
+          1,
+          1,
+          32,
+          4
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "pnet/conv4_2/bias",
+        "shape": [
+          4
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "rnet/conv1/weights",
+        "shape": [
+          3,
+          3,
+          3,
+          28
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "rnet/conv1/bias",
+        "shape": [
+          28
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "rnet/prelu1_alpha",
+        "shape": [
+          28
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "rnet/conv2/weights",
+        "shape": [
+          3,
+          3,
+          28,
+          48
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "rnet/conv2/bias",
+        "shape": [
+          48
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "rnet/prelu2_alpha",
+        "shape": [
+          48
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "rnet/conv3/weights",
+        "shape": [
+          2,
+          2,
+          48,
+          64
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "rnet/conv3/bias",
+        "shape": [
+          64
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "rnet/prelu3_alpha",
+        "shape": [
+          64
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "rnet/fc1/weights",
+        "shape": [
+          576,
+          128
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "rnet/fc1/bias",
+        "shape": [
+          128
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "rnet/prelu4_alpha",
+        "shape": [
+          128
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "rnet/fc2_1/weights",
+        "shape": [
+          128,
+          2
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "rnet/fc2_1/bias",
+        "shape": [
+          2
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "rnet/fc2_2/weights",
+        "shape": [
+          128,
+          4
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "rnet/fc2_2/bias",
+        "shape": [
+          4
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/conv1/weights",
+        "shape": [
+          3,
+          3,
+          3,
+          32
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/conv1/bias",
+        "shape": [
+          32
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/prelu1_alpha",
+        "shape": [
+          32
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/conv2/weights",
+        "shape": [
+          3,
+          3,
+          32,
+          64
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/conv2/bias",
+        "shape": [
+          64
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/prelu2_alpha",
+        "shape": [
+          64
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/conv3/weights",
+        "shape": [
+          3,
+          3,
+          64,
+          64
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/conv3/bias",
+        "shape": [
+          64
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/prelu3_alpha",
+        "shape": [
+          64
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/conv4/weights",
+        "shape": [
+          2,
+          2,
+          64,
+          128
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/conv4/bias",
+        "shape": [
+          128
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/prelu4_alpha",
+        "shape": [
+          128
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/fc1/weights",
+        "shape": [
+          1152,
+          256
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/fc1/bias",
+        "shape": [
+          256
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/prelu5_alpha",
+        "shape": [
+          256
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/fc2_1/weights",
+        "shape": [
+          256,
+          2
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/fc2_1/bias",
+        "shape": [
+          2
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/fc2_2/weights",
+        "shape": [
+          256,
+          4
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/fc2_2/bias",
+        "shape": [
+          4
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/fc2_3/weights",
+        "shape": [
+          256,
+          10
+        ]
+      },
+      {
+        "dtype": "float32",
+        "name": "onet/fc2_3/bias",
+        "shape": [
+          10
+        ]
+      }
+    ]
+  }
+]

face_recognized_attendance_login/static/src/js/weights/tiny_face_detector_model-weights_manifest.json

@@ -0,0 +1,273 @@
+[
+  {
+    "weights": [
+      {
+        "name": "conv0/filters",
+        "shape": [
+          3,
+          3,
+          3,
+          16
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.009007044399485869,
+          "min": -1.2069439495311063
+        }
+      },
+      {
+        "name": "conv0/bias",
+        "shape": [
+          16
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.005263455241334205,
+          "min": -0.9211046672334858
+        }
+      },
+      {
+        "name": "conv1/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          16,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.004001977630690033,
+          "min": -0.5042491814669441
+        }
+      },
+      {
+        "name": "conv1/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          16,
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.013836609615999109,
+          "min": -1.411334180831909
+        }
+      },
+      {
+        "name": "conv1/bias",
+        "shape": [
+          32
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0015159862590771096,
+          "min": -0.30926119685173037
+        }
+      },
+      {
+        "name": "conv2/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          32,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.002666276225856706,
+          "min": -0.317286870876948
+        }
+      },
+      {
+        "name": "conv2/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          32,
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.015265831292844286,
+          "min": -1.6792414422128714
+        }
+      },
+      {
+        "name": "conv2/bias",
+        "shape": [
+          64
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0020280554598453,
+          "min": -0.37113414915168985
+        }
+      },
+      {
+        "name": "conv3/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          64,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.006100742489683862,
+          "min": -0.8907084034938438
+        }
+      },
+      {
+        "name": "conv3/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          64,
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.016276211832083907,
+          "min": -2.0508026908425725
+        }
+      },
+      {
+        "name": "conv3/bias",
+        "shape": [
+          128
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.003394414279975143,
+          "min": -0.7637432129944072
+        }
+      },
+      {
+        "name": "conv4/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          128,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.006716050119961009,
+          "min": -0.8059260143953211
+        }
+      },
+      {
+        "name": "conv4/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          128,
+          256
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.021875603993733724,
+          "min": -2.8875797271728514
+        }
+      },
+      {
+        "name": "conv4/bias",
+        "shape": [
+          256
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.0041141652009066415,
+          "min": -0.8187188749804216
+        }
+      },
+      {
+        "name": "conv5/depthwise_filter",
+        "shape": [
+          3,
+          3,
+          256,
+          1
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.008423839597141042,
+          "min": -0.9013508368940915
+        }
+      },
+      {
+        "name": "conv5/pointwise_filter",
+        "shape": [
+          1,
+          1,
+          256,
+          512
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.030007277283014035,
+          "min": -3.8709387695088107
+        }
+      },
+      {
+        "name": "conv5/bias",
+        "shape": [
+          512
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.008402082966823203,
+          "min": -1.4871686851277068
+        }
+      },
+      {
+        "name": "conv8/filters",
+        "shape": [
+          1,
+          1,
+          512,
+          25
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.028336129469030042,
+          "min": -4.675461362389957
+        }
+      },
+      {
+        "name": "conv8/bias",
+        "shape": [
+          25
+        ],
+        "dtype": "float32",
+        "quantization": {
+          "dtype": "uint8",
+          "scale": 0.002268134028303857,
+          "min": -0.41053225912299807
+        }
+      }
+    ],
+    "paths": [
+      "tiny_face_detector_model-shard1"
+    ]
+  }
+]

face_recognized_attendance_login/static/src/xml/face_recognition_template.xml

@@ -0,0 +1,18 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<templates xml:space="preserve">
+    <t t-inherit="hr_attendance.public_kiosk_app" t-inherit-mode="extension">
+        <xpath expr="." position="inside">
+           <div id="WebCamModal"
+                style="display: block;pointer-events: none; position: fixed; z-index: 9999; top: 50%; left: 30%; transform: translate(-50%, -50%); width: 50px; background-color: transparent">
+                <div class="container">
+                    <video id="video" width="500" height="500" autoplay=""
+                           t-ref="video"
+                           muted=""
+                           style="display: block;margin-top: 213px; margin-left: 150px;"/>
+                    <img id="employee_image" style="visibility:hidden;height:400px;width:400px"
+                         t-ref="employee_image"/>
+                </div>
+            </div>
+        </xpath>
+    </t>
+</templates>