Browse Source

Dec 04: [FIX] Bug Fixed 'face_recognized_attendance_login'

pull/301/merge
Cybrosys Technologies 7 months ago
parent
commit
bbbc8d0aa1
  1. 14
      face_recognized_attendance_login/__manifest__.py
  2. 6
      face_recognized_attendance_login/doc/RELEASE_NOTES.md
  3. 109
      face_recognized_attendance_login/models/hr_employee.py
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  14. 73
      face_recognized_attendance_login/static/description/index.html
  15. 26
      face_recognized_attendance_login/static/src/css/my_attendance.css
  16. 1
      face_recognized_attendance_login/static/src/js/face-api.min.js
  17. 196
      face_recognized_attendance_login/static/src/js/kiosk_confirm.js
  18. 205
      face_recognized_attendance_login/static/src/js/my_attendance.js
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  20. 618
      face_recognized_attendance_login/static/src/js/weights/age_gender_model-weights_manifest.json
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  33. 137
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      face_recognized_attendance_login/static/src/js/weights/tiny_face_detector_model-weights_manifest.json
  37. 50
      face_recognized_attendance_login/static/src/xml/attendance.xml
  38. 75
      face_recognized_attendance_login/static/src/xml/kiosk_confirm.xml
  39. 24
      face_recognized_attendance_login/views/login_templates.xml

14
face_recognized_attendance_login/__manifest__.py

@ -21,7 +21,7 @@
############################################################################# #############################################################################
{ {
'name': 'Face Recognized Attendance Login', 'name': 'Face Recognized Attendance Login',
'version': '16.0.1.0.0', 'version': '16.0.2.0.0',
'category': 'Human Resources', 'category': 'Human Resources',
'summary': """Mark the attendance of employee by recognizing their face""", 'summary': """Mark the attendance of employee by recognizing their face""",
'description': """This module introduces a face recognition system in the 'description': """This module introduces a face recognition system in the
@ -32,15 +32,19 @@
'maintainer': 'Cybrosys Techno Solutions', 'maintainer': 'Cybrosys Techno Solutions',
'website': "https://www.cybrosys.com", 'website': "https://www.cybrosys.com",
'depends': ['base', 'mail', 'hr', 'hr_attendance'], 'depends': ['base', 'mail', 'hr', 'hr_attendance'],
'data': [
],
'assets': { 'assets': {
'web.assets_backend': [ 'web.assets_backend': [
'face_recognized_attendance_login/static/src/js/my_attendance.js', 'face_recognized_attendance_login/static/src/js/my_attendance.js',
'face_recognized_attendance_login/static/src/js/face-api.min.js',
'face_recognized_attendance_login/static/src/xml/attendance.xml',
'face_recognized_attendance_login/static/src/css/my_attendance.css',
'face_recognized_attendance_login/static/src/xml/kiosk_confirm.xml',
'face_recognized_attendance_login/static/src/js/kiosk_confirm.js',
] ]
}, },
'external_dependencies': {
'python': ['cv2', 'face_recognition', 'cmake', 'dlib', 'PIL',
'numpy'],
},
'images': ['static/description/banner.jpg'], 'images': ['static/description/banner.jpg'],
'license': 'LGPL-3', 'license': 'LGPL-3',
'installable': True, 'installable': True,

6
face_recognized_attendance_login/doc/RELEASE_NOTES.md

@ -3,3 +3,9 @@
#### Version 16.0.1.0.0 #### Version 16.0.1.0.0
##### ADD ##### ADD
- Initial Commit for Face Recognized Attendance Login - Initial Commit for Face Recognized Attendance Login
## Module <face_recognized_attendance_login>
#### 02.12.2024
#### Version 16.0.2.0.0
##### ADD
- Update

109
face_recognized_attendance_login/models/hr_employee.py

@ -19,14 +19,14 @@
# If not, see <http://www.gnu.org/licenses/>. # If not, see <http://www.gnu.org/licenses/>.
# #
############################################################################# #############################################################################
import base64 # import base64
import cv2 # import cv2
import face_recognition # import face_recognition
import numpy as np # import numpy as np
import os # import os
import time # import time
from io import BytesIO # from io import BytesIO
from PIL import Image # from PIL import Image
from odoo import api, models from odoo import api, models
@ -44,84 +44,15 @@ class HrEmployee(models.Model):
to ensure that it's a human, not an image of employee""" to ensure that it's a human, not an image of employee"""
employee_pic = self.search( employee_pic = self.search(
[('user_id', '=', self.env.user.id)]).image_1920 [('user_id', '=', self.env.user.id)]).image_1920
sub_folder = os.path.abspath(os.path.dirname(__file__))
project_folder = os.path.abspath(os.path.join(sub_folder, os.pardir)) return employee_pic
eye_cascade_path = os.path.join(project_folder, 'data',
'haarcascade_eye_tree_eyeglasses.xml') @api.model
face_cascade_path = os.path.join(project_folder, 'data', def get_kiosk_image(self, id):
'haarcascade_frontalface_default.xml') """This function is used for attendance Check In and Check Out in kiosk mode.
face_cascade = cv2.CascadeClassifier(face_cascade_path) It works by compare the image of employee that already uploaded
eye_cascade = cv2.CascadeClassifier(eye_cascade_path) to the image that get currently from the webcam. This function
binary_data = base64.b64decode(employee_pic) also detect the blinking of eyes and calculate the eye match index,
image_bytes = BytesIO(binary_data) to ensure that it's a human, not an image of employee"""
pil_image = Image.open(image_bytes) employee_pic = self.browse(id).image_1920
np_image = np.array(pil_image) return employee_pic
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:
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 camera_time < 100:
camera_time = camera_time + 1
else:
break
cv2.putText(frame, "Please wait... your face is detecting",
(100, 100),
cv2.FONT_HERSHEY_PLAIN, 3, (0, 0, 255), 2)
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)
# Extract features from the eye(s) in the current frame
current_key_points, current_descriptors = orb.detectAndCompute(gray, None)
# Match the features of the current eye(s) to those in
# the reference eye(s)
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 < 50]
if len(good_matches) >= 10:
eyes_match_index = eyes_match_index + 1
else:
eyes_match_fail_index = 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)
if camera_time >= 100:
break
cv2.imshow('frame', frame)
cv2.waitKey(1)
cap.release()
cv2.destroyAllWindows()
return face_recognized

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73
face_recognized_attendance_login/static/description/index.html

@ -116,45 +116,6 @@
</div> </div>
</div> </div>
<!-- END OF OVERVIEW SECTION --> <!-- END OF OVERVIEW SECTION -->
<!-- CONFIGURATION -->
<div class="d-flex align-items-center" style="border-bottom: 2px solid #714B67; padding: 15px 0px;" id="configuration">
<div class="d-flex justify-content-center align-items-center mr-2"
style="background-color: #F5F5F5; border-radius: 0px; width: 40px; height: 40px;">
<img src="assets/misc/features.png" />
</div>
<h2 class="mt-2" style="font-family: 'Montserrat', sans-serif; font-size: 24px; font-weight: bold;">Configuration
</h2>
</div>
</div>
<div class="row" style="font-family: 'Montserrat', sans-serif; font-weight: 400; font-size: 14px; line-height: 200%;">
<div class="col-sm-12 col-md-6">
<div class="d-flex align-items-center" style="margin-top: 40px; margin-bottom: 40px">
<img src="assets/misc/check-box.png" class="mr-2" />
<div class="row" style="font-family: 'Montserrat', sans-serif; font-weight: 400; font-size: 14px; line-height: 200%;">
<div class="col py-4">
For the proper working of this module, please ensure that the following are installed before the installation of this module
<li> <b><i>Opencv</i></b> -For ubuntu 20.04 you can download the Opencv from following link</br>
<a href="https://linuxize.com/post/how-to-install-opencv-on-ubuntu-20-04/">https://linuxize.com/post/how-to-install-opencv-on-ubuntu-20-04/</a>
or<br/> you can use the command - sudo apt install libopencv-dev python3-opencv</li>
<li><b><i>cmake</i></b> - pip install cmake</li>
<li><b><i>dlib</i></b> - pip install dlib</li>
<li><b><i>PIL</i></b> - pip install Pillow</li>
<li><b><i>numpy</i></b> - pip install numpy</li>
<li><b><i>face_recognition</i></b> - pip install face-recognition</li>
<li>Also, ensure that you provide the camera access</li>
</div>
</div>
</div>
</div>
<!-- END OF CONFIGURATION SECTION -->
<!-- FEATURES SECTION --> <!-- FEATURES SECTION -->
<div class="d-flex align-items-center" style="border-bottom: 2px solid #714B67; padding: 15px 0px;" id="features"> <div class="d-flex align-items-center" style="border-bottom: 2px solid #714B67; padding: 15px 0px;" id="features">
<div class="d-flex justify-content-center align-items-center mr-2" <div class="d-flex justify-content-center align-items-center mr-2"
@ -198,23 +159,47 @@
<div style="display: block; margin: 30px auto;"> <div style="display: block; margin: 30px auto;">
<h3 style="font-family: 'Montserrat', sans-serif; font-size: 18px; font-weight: bold;">From attendance page you can click CheckIn button</h3> <h3 style="font-family: 'Montserrat', sans-serif; font-size: 18px; font-weight: bold;">From attendance page you can click CheckIn button</h3>
<img src="assets/screenshots/fr_01.png" class="img-thumbnail"> <img src="assets/screenshots/img_5.png" class="img-thumbnail">
</div> </div>
<div style="display: block; margin: 30px auto;"> <div style="display: block; margin: 30px auto;">
<h3 style="font-family: 'Montserrat', sans-serif; font-size: 18px; font-weight: bold;">A wizard will open, that access the webcam of user</h3> <h3 style="font-family: 'Montserrat', sans-serif; font-size: 18px; font-weight: bold;">A wizard will open, that access the webcam of user</h3>
<img src="assets/screenshots/fr_02.png" class="img-thumbnail"> <img src="assets/screenshots/img_6.png" class="img-thumbnail" style="width:100%;">
</div> </div>
<div style="display: block; margin: 30px auto;"> <div style="display: block; margin: 30px auto;">
<h3 style="font-family: 'Montserrat', sans-serif; font-size: 18px; font-weight: bold;">If the face is recognized by the <h3 style="font-family: 'Montserrat', sans-serif; font-size: 18px; font-weight: bold;">If the face is recognized by the
system, the employee can CheckIn and later can CheckOut by clicking the CheckOut button</h3> system, the employee can CheckIn and later can CheckOut by clicking the CheckOut button</h3>
<img src="assets/screenshots/fr_03.png" class="img-thumbnail"> <img src="assets/screenshots/img_8.png" class="img-thumbnail">
<img src="assets/screenshots/img_9.png" class="img-thumbnail">
</div> </div>
<div style="display: block; margin: 30px auto;"> <div style="display: block; margin: 30px auto;">
<h3 style="font-family: 'Montserrat', sans-serif; font-size: 18px; font-weight: bold;">A wizard will open, that access the webcam of user <h3 style="font-family: 'Montserrat', sans-serif; font-size: 18px; font-weight: bold;">In the kiosk mode section also the face recognition step is added,
GO to Kiosk Mode, Click "Identify Manually".
</h3>
<img src="assets/screenshots/img.png" class="img-thumbnail">
</div>
<div style="display: block; margin: 30px auto;">
<h3 style="font-family: 'Montserrat', sans-serif; font-size: 18px; font-weight: bold;">We can see the list of employees
</h3>
<img src="assets/screenshots/img_1.png" class="img-thumbnail">
</div>
<div style="display: block; margin: 30px auto;">
<h3 style="font-family: 'Montserrat', sans-serif; font-size: 18px; font-weight: bold;">By choosing employee , we can see the Check in and Checkout option
</h3>
<img src="assets/screenshots/img_2.png" class="img-thumbnail">
</div>
<div style="display: block; margin: 30px auto;">
<h3 style="font-family: 'Montserrat', sans-serif; font-size: 18px; font-weight: bold;">By clicking Checkin/Checkout , the face recognition starts. If it is not a match , it will notify.
</h3>
<img src="assets/screenshots/img_3.png" class="img-thumbnail" style="width:100%;">
</div>
<div style="display: block; margin: 30px auto;">
<h3 style="font-family: 'Montserrat', sans-serif; font-size: 18px; font-weight: bold;">If it matches we can check in .
</h3> </h3>
<img src="assets/screenshots/fr_02.png" class="img-thumbnail"> <img src="assets/screenshots/img_5.png" class="img-thumbnail">
<img src="assets/screenshots/img_6.png" class="img-thumbnail" style="width:100%">
<img src="assets/screenshots/img_7.png" class="img-thumbnail" style="width:100%">
</div> </div>
<!-- END OF SCREENSHOTS SECTION --> <!-- END OF SCREENSHOTS SECTION -->

26
face_recognized_attendance_login/static/src/css/my_attendance.css

@ -0,0 +1,26 @@
.qr_video {
display: block; /* Initially visible */
}
.qr_video.hidden {
display: none; /* Will hide the QR scanner when the close button is clicked */
}
#close_qr_scanner {
cursor: pointer;
color: red;
font-weight: bold;
}
.qr_video_kiosk {
display: block; /* Initially visible */
}
.qr_video_kiosk.hidden {
display: none; /* Will hide the QR scanner when the close button is clicked */
}
#close_qr_scanner_kiosk {
cursor: pointer;
color: red;
font-weight: bold;
}

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face_recognized_attendance_login/static/src/js/face-api.min.js

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196
face_recognized_attendance_login/static/src/js/kiosk_confirm.js

@ -0,0 +1,196 @@
/** @odoo-module **/
import { patch } from "@web/core/utils/patch";
const KioskConfirm = require("hr_attendance.kiosk_confirm")
const session = require('web.session');
var rpc = require('web.rpc');
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(KioskConfirm.prototype,'face_recognized_attendance_login.kiosk',{
events: {
"click .o_hr_attendance_back_button": function () { this.do_action(this.next_action, {clear_breadcrumbs: true}); },
"click .o_hr_attendance_sign_in_out_icon": _.debounce(async function () {
await this.startWebcam();
}, 200, true),
},
// -------To start the camera-------
async startWebcam() {
const video = this.el.querySelector('#video');
try {
const video = this.el.querySelector('#video');
if (!navigator.mediaDevices || !navigator.mediaDevices.getUserMedia) {
throw new Error('getUserMedia is not supported in this browser.');
}
const stream = await navigator.mediaDevices.getUserMedia({ video: true, audio: false });
video.srcObject = stream;
video.onloadedmetadata = () => {
video.play();
};
this.faceRecognition(video);
} catch (error) {
console.error('An error occurred while accessing the camera:', error);
this.__parentedParent.notifications.add(
'Unable to access webcam. Please check your device permissions or use a supported browser.', {
title: 'Webcam Error',
type: 'danger',
sticky: true,
className: "p-4"
}
);
}
},
// -----To start the face recognition-----------
async faceRecognition(video) {
const labeledFaceDescriptors = await this.getLabeledFaceDescriptions(video);
if (!labeledFaceDescriptors) {
console.error('No labeled face descriptors available.');
this.stopWebcamAndDetection();
return;
}
if (!this.faceMatcher) {
const labeledFaceDescriptors = await this.getLabeledFaceDescriptions();
this.faceMatcher = new faceapi.FaceMatcher([labeledFaceDescriptors]);
if (labeledFaceDescriptors && labeledFaceDescriptors.descriptor) {
this.faceMatcher = new faceapi.FaceMatcher([labeledFaceDescriptors.descriptor]);
} else {
console.error("Could not get face descriptor from reference image");
this.__parentedParent.notification.add("Failed to initialize face recognition, Please upload a new, properly formatted image.", {
type: "danger",
title: "Image detection failed!",
});
this.stopRecognition(video);
return;
}
}
let attendanceMarked = false;
let notificationSent = false;
this.faceRecognitionInterval = setInterval(async () => {
try {
const detections = await faceapi
.detectAllFaces(video)
.withFaceLandmarks()
.withFaceDescriptors();
if (detections.length === 0) {
if (!notificationSent) {
this.__parentedParent.notifications.add(
'No face detected.', {
title: 'Detection Failed!',
type: 'danger',
sticky: false,
className: "p-4"
}
);
notificationSent = true;
}
this.stopWebcamAndDetection();
return;
}
detections.forEach((detection) => {
const match = this.faceMatcher.findBestMatch(detection.descriptor);
if (match._distance < 0.4 && !attendanceMarked) {
const modal = this.el.querySelector('#video');
if (modal) {
modal.style.display = 'none';
}
attendanceMarked = true;
notificationSent = false;
this.markAttendance();
clearInterval(this.faceRecognitionInterval);
this.stopWebcamAndDetection();
}
});
if (!attendanceMarked && !notificationSent) {
this.__parentedParent.notifications.add(
'Face is not recognized.', {
title: 'No Match!',
type: 'danger',
sticky: false,
className: "p-4"
}
);
notificationSent = true;
this.stopWebcamAndDetection();
}
} catch (error) {
console.error('Error during face recognition:', error);
this.stopWebcamAndDetection();
}
}, 100);
},
// ---------Fetch labeled face descriptions (employee's face data)------
async getLabeledFaceDescriptions(video) {
const employee_image_base64 = await rpc.query({
model: 'hr.employee',
method: 'get_kiosk_image',
args: [this.employee_id]
});
if (employee_image_base64) {
const employee_image = new Image();
employee_image.src = "data:image/jpeg;base64," + employee_image_base64;
try {
const detections = await faceapi
.detectSingleFace(employee_image)
.withFaceLandmarks()
.withFaceExpressions()
.withFaceDescriptor();
if (!detections) {
console.error('No face detected in the image.');
this.__parentedParent.notifications.add(
'No face detected in the image.Please upload a new, properly formatted image in the profile.', {
title: 'Image detection failed!',
type: 'danger',
sticky: false,
className: "p-4"
}
);
return;
}
return detections;
} catch (error) {
console.error('Error during face detection:', error);
}
} else {
console.error('No image data found for the employee.');
}
},
// ----------Function to stop webcam and face detection-----
stopWebcamAndDetection() {
const video = this.el.querySelector('#video');
if (video.srcObject) {
const stream = video.srcObject;
const tracks = stream.getTracks();
tracks.forEach(track => track.stop());
video.srcObject = null; //
}
if (this.faceRecognitionInterval) {
clearInterval(this.faceRecognitionInterval);
this.faceRecognitionInterval = null;
}
this.faceMatcher = null;
},
// ------------Redirecting to welcome/checkout page ----------------------------------
markAttendance() {
const self = this;
this._rpc({
model: 'hr.employee',
method: 'attendance_manual',
args: [[this.employee_id], 'hr_attendance.hr_attendance_action_my_attendances']
}).then((result) => {
if (result.action) {
self.do_action(result.action);
} else if (result.warning) {
self.do_warn(result.warning);
}
}).catch((error) => {
console.error('Error marking attendance:', error);
});
},
})

205
face_recognized_attendance_login/static/src/js/my_attendance.js

@ -1,42 +1,205 @@
odoo.define('face_recognized_attendance_login.my_attendance', function(require) { odoo.define('face_recognized_attendance_login.my_attendance', function(require) {
"use strict"; "use strict";
/** // Required Odoo dependencies
* This file inherit the class MyAttendances, and added the functionality, that
the login/logout is possible only after the face detection
*/
var core = require('web.core'); var core = require('web.core');
var Widget = require('web.Widget'); var Widget = require('web.Widget');
var rpc = require('web.rpc'); var rpc = require('web.rpc');
var MyAttendances = require('hr_attendance.my_attendances'); var MyAttendances = require('hr_attendance.my_attendances');
var login = 0 var _t = core._t;
// Login made possible, if and only if the captured image and face of the var login = 0;
// employee matched const MODEL_URL = '/face_recognized_attendance_login/static/src/js/weights';
// Load face-api.js models
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);
// Extend MyAttendances widget
MyAttendances.include({ MyAttendances.include({
events: _.extend({}, MyAttendances.prototype.events, {
'click #close_qr_scanner': 'stopWebcamAndDetection',
}),
update_attendance: async function() { update_attendance: async function() {
await rpc.query({ this.faceMatcher = null;
this.el.querySelector('.close_button').classList.remove('d-none'); // Show the close button
await this.startWebcam();
},
//--------------------------------------------------------------------
async startWebcam() {
const video = this.el.querySelector('#video');
console.log("navigator",navigator)
try {
if (!navigator.mediaDevices || !navigator.mediaDevices.getUserMedia) {
throw new Error('Webcam access is not supported or allowed in this browser.');
}
const stream = await navigator.mediaDevices.getUserMedia({ video: true, audio: false });
video.srcObject = stream;
video.onloadedmetadata = () => {
video.play();
};
this.faceRecognition(video);
} catch (error) {
this.el.querySelector('.close_button').classList.add('d-none');
this.__parentedParent.notifications.add(
'Unable to access webcam. Please check your device permissions or use a supported browser.', {
title: 'Webcam Error',
type: 'danger',
sticky: true,
className: "p-4"
}
);
}
},
// --------------------Function to stop webcam and face detection------------
stopWebcamAndDetection() {
const video = this.el.querySelector('#video');
this.el.querySelector('.close_button').classList.add('d-none');
if (video.srcObject) {
const stream = video.srcObject;
const tracks = stream.getTracks();
tracks.forEach(track => track.stop());
video.srcObject = null; //
}
if (this.faceRecognitionInterval) {
clearInterval(this.faceRecognitionInterval);
this.faceRecognitionInterval = null;
}
this.faceMatcher = null;
console.log('Camera and detection stopped.');
},
//------------------ Fetch labeled face descriptions (employee's face data)------
async getLabeledFaceDescriptions(video) {
const employee_image_base64 = await rpc.query({
model: 'hr.employee', model: 'hr.employee',
method:'get_login_screen' method: 'get_login_screen',
}).then(function (data) {
login = data
}); });
if (login==1){ if (employee_image_base64) {
var self = this; const employee_image = new Image();
employee_image.src = "data:image/jpeg;base64," + employee_image_base64;
try {
const detections = await faceapi
.detectSingleFace(employee_image)
.withFaceLandmarks()
.withFaceExpressions()
.withFaceDescriptor();
console.log(detections)
if (!detections) {
console.error('No face detected in the image.');
this.__parentedParent.notifications.add(
'No face detected in the image.Please upload a new, properly formatted image in the profile.', {
title: 'Image detection failed!',
type: 'danger',
sticky: false,
className: "p-4"
}
);
return;
}
return detections;
} catch (error) {
console.error('Error during face detection:', error);
}
} else {
console.error('No image data found for the employee.');
}
},
//----------------------------- Face recognition logic---------------
async faceRecognition(video) {
const labeledFaceDescriptors = await this.getLabeledFaceDescriptions(video);
if (!labeledFaceDescriptors) {
console.error('No labeled face descriptors available.');
this.stopWebcamAndDetection();
return;
}
if (!this.faceMatcher) {
const labeledFaceDescriptors = await this.getLabeledFaceDescriptions();
this.faceMatcher = new faceapi.FaceMatcher([labeledFaceDescriptors]);
if (labeledFaceDescriptors && labeledFaceDescriptors.descriptor) {
this.faceMatcher = new faceapi.FaceMatcher([labeledFaceDescriptors.descriptor]);
} else {
console.error("Could not get face descriptor from reference image");
this.__parentedParent.notification.add("Failed to initialize face recognition, Please upload a new, properly formatted image.", {
type: "danger",
title: "Image detection failed!",
});
this.stopRecognition(video);
return;
}
}
let attendanceMarked = false;
let notificationSent = false;
this.faceRecognitionInterval = setInterval(async () => {
try {
const detections = await faceapi
.detectAllFaces(video)
.withFaceLandmarks()
.withFaceDescriptors();
if (detections.length === 0) {
if (!notificationSent) {
this.__parentedParent.notifications.add(
'No face detected.', {
title: 'Detection Failed!',
type: 'danger',
sticky: false,
className: "p-4"
}
);
notificationSent = true; // Prevent duplicate notifications
}
this.stopWebcamAndDetection();
return;
}
detections.forEach((detection) => {
const match = this.faceMatcher.findBestMatch(detection.descriptor);
if (match._distance < 0.4 && !attendanceMarked) {
const modal = this.el.querySelector('#video');
if (modal) {
modal.style.display = 'none';
}
attendanceMarked = true; // Set flag to prevent re-matching
notificationSent = false; // Reset notification flag
this.markAttendance();
clearInterval(this.faceRecognitionInterval);
this.stopWebcamAndDetection(); // Stop webcam and detection
}
});
if (!attendanceMarked && !notificationSent) {
this.__parentedParent.notifications.add(
'Face is not recognized.', {
title: 'No Match!',
type: 'danger',
sticky: false,
className: "p-4"
}
);
notificationSent = true;
this.stopWebcamAndDetection();
}
} catch (error) {
console.error('Error during face recognition:', error);
this.stopWebcamAndDetection();
}
}, 100);
},
// ------------Redirecting to welcome/checkout page ----------------------------------
markAttendance() {
const self = this;
this._rpc({ this._rpc({
model: 'hr.employee', model: 'hr.employee',
method: 'attendance_manual', method: 'attendance_manual',
args: [[self.employee.id], 'hr_attendance.hr_attendance_action_my_attendances'], args: [[self.employee.id], 'hr_attendance.hr_attendance_action_my_attendances']
}) }).then((result) => {
.then(function(result) {
if (result.action) { if (result.action) {
self.do_action(result.action); self.do_action(result.action);
} else if (result.warning) { } else if (result.warning) {
self.do_warn(result.warning); self.do_warn(result.warning);
} }
}).catch((error) => {
console.error('Error marking attendance:', error);
}); });
} },
else{
window.alert("Failed to recognize the face. Please try again....")
}
}
}); });
}); });

BIN
face_recognized_attendance_login/static/src/js/weights/age_gender_model-shard1

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618
face_recognized_attendance_login/static/src/js/weights/age_gender_model-weights_manifest.json

@ -0,0 +1,618 @@
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]

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face_recognized_attendance_login/static/src/js/weights/face_expression_model-shard1

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

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"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"
]
}
]

50
face_recognized_attendance_login/static/src/xml/attendance.xml

@ -0,0 +1,50 @@
<?xml version="1.0" encoding="UTF-8"?>
<templates xml:space="preserve">
<t t-inherit="hr_attendance.HrAttendanceMyMainMenu"
t-inherit-mode="extension">
<xpath expr="//t[@t-set='bodyContent']" position="replace">
<t t-set="bodyContent">
<div class="justify-content-between mt-2 d-flex small oe_qr_login" style="position:absolute;">
<div class="qr_video_kiosk">
<div class="close_button d-none position-absolute"
t-ref="close_button">
<button id="close_qr_scanner_kiosk" t-on-click="stopWebcamAndDetection"
style="position: absolute; right: 5px; z-index: 111;top:-15px;">
X
</button>
<div class="video-container">
<video id="video" width="" height="" autoplay="true"
style="margin-left:-150px;margin-top:-24px;"/>
</div>
</div>
</div>
</div>
<t t-if="widget.employee">
<t t-set="checked_in"
t-value="widget.employee.attendance_state == 'checked_in'"/>
<!-- Custom Badge Section -->
<t t-call="HrAttendanceUserBadge">
<t t-set="userId" t-value="widget.employee.id"/>
<t t-set="userName" t-value="widget.employee.name"/></t>
<div class="flex-grow-1">
<h1 class="mt-5" t-esc="widget.employee.name"/>
<h3>
<t t-if="!checked_in">Welcome!</t>
<t t-else="">Want to check out?</t>
</h3>
<h4 class="mt0 mb0 text-muted" t-if="checked_in">Today's work hours:
<span
t-esc="widget.hours_today"/>
</h4>
</div>
<t t-call="HrAttendanceCheckInOutButtons"/></t>
<div class="alert alert-warning" t-else="">
<b>Warning</b>: Your user should be linked to an employee to
use attendance.
<br/>
Please contact your administrator.
</div>
</t>
</xpath>
</t>
</templates>

75
face_recognized_attendance_login/static/src/xml/kiosk_confirm.xml

@ -0,0 +1,75 @@
<?xml version="1.0" encoding="UTF-8"?>
<templates xml:space="preserve">
<t t-inherit="hr_attendance.HrAttendanceKioskConfirm"
t-inherit-mode="extension">
<xpath expr="//t[@t-set='bodyContent']" position="replace">
<t t-set="bodyContent">
<div class="justify-content-between mt-2 d-flex small oe_qr_login" style="position:absolute; display:block !important;pointer-events: none">
<div class="qr_video">
<!-- <div class="close_button d-none position-absolute"-->
<!-- t-ref="close_button" style="display:block !important;">-->
<!-- <button id="close_qr_scanner" t-on-click="stopWebcamAndDetection"-->
<!-- style="position: absolute; right: 5px; z-index: 111;top:-15px;">-->
<!-- X-->
<!-- </button>-->
<!-- </div>-->
<div class="video-container">
<video id="video" width="" height="" autoplay="true"
style="margin-left:-150px;margin-top:-24px;"/>
</div>
</div>
</div>
<t t-set="checked_in" t-value="widget.employee_state=='checked_in'"/>
<button class="o_hr_attendance_back_button btn btn-block btn-secondary btn-lg d-block d-md-none py-5">
<i class="fa fa-chevron-left me-2"/> Go back
</button>
<t t-if="widget.employee_id" t-call="HrAttendanceUserBadge">
<t t-set="userId" t-value="widget.employee_id"/>
<t t-set="userName" t-value="widget.employee_name"/>
</t>
<button class="o_hr_attendance_back_button o_hr_attendance_back_button_md btn btn-secondary d-none d-md-inline-flex align-items-center position-absolute top-0 start-0 rounded-circle">
<i class="fa fa-2x fa-fw fa-chevron-left me-1" role="img" aria-label="Go back" title="Go back"/>
</button>
<div t-if="widget.employee_id" class="flex-grow-1">
<h1 class="mt-5 mb8"><t t-esc="widget.employee_name"/></h1>
<h3 class="mt8 mb24"><t t-if="!checked_in">Welcome!</t><t t-else="">Want to check out?</t></h3>
<h4 class="mt0 mb0 text-muted" t-if="checked_in">Today's work hours: <span t-esc="widget.employee_hours_today"/></h4>
<t t-if="!widget.use_pin" t-call="HrAttendanceCheckInOutButtons"/>
<t t-else="">
<h3 class="mt-4 mb0 text-muted">Please enter your PIN to <b t-if="checked_in">check out</b><b t-else="">check in</b></h3>
<div class="row">
<div class="col-md-8 offset-md-2 o_hr_attendance_pin_pad">
<div class="row g-0" >
<div class="col-12 mb8 mt8">
<input class="o_hr_attendance_PINbox border-0 bg-white fs-1 text-center" type="password" disabled="true"/>
</div>
</div>
<div class="row g-0">
<t t-foreach="['1', '2', '3', '4', '5', '6', '7', '8', '9', ['C', 'btn-warning'], '0', ['ok', 'btn-primary']]" t-as="btn_name">
<div class="col-4 p-1">
<a href="#" t-attf-class="o_hr_attendance_PINbox_button btn {{btn_name[1]? btn_name[1] : 'btn-secondary border'}} btn-block btn-lg {{ 'o_hr_attendance_pin_pad_button_' + btn_name[0] }} d-flex align-items-center justify-content-center">
<t t-esc="btn_name[0]"/>
</a>
</div>
</t>
</div>
</div>
</div>
</t>
</div>
<div t-else="" class="alert alert-danger mx-3" role="alert">
<h4 class="alert-heading">Error: could not find corresponding employee.</h4>
<p>Please return to the main menu.</p>
</div>
<a role="button" class="oe_attendance_sign_in_out" aria-label="Sign out" title="Sign out"/>
</t>
</xpath>
</t>
</templates>

24
face_recognized_attendance_login/views/login_templates.xml

@ -0,0 +1,24 @@
<?xml version="1.0" encoding="UTF-8" ?>
<odoo>
<!--Calling the controller of scanner from login page-->
<template id="qr_login" inherit_id="web.login" name="QR scanner">
<xpath expr="//div[hasclass('o_login_auth')]" position="before">
<div class="justify-content-between mt-2 d-flex small oe_qr_login">
<a href="#" id="login_click" t-on-click='_onLoginClick'>Login With QR</a>
<div class="qr_video">
<div class="close_button d-none position-absolute" t-ref="close_button">
<button id="close_qr_scanner" style="position: absolute; right: 0px; z-index: 111">
X
</button>
<div class="video-container">
<video id="video" width="" height="" autoplay="true"/>
</div>
</div>
</div>
</div>
</xpath>
</template>
</odoo>
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