After Width: | Height: | Size: 628 KiB |
After Width: | Height: | Size: 295 KiB |
After Width: | Height: | Size: 664 KiB |
After Width: | Height: | Size: 1.0 MiB |
After Width: | Height: | Size: 1.0 MiB |
After Width: | Height: | Size: 673 KiB |
After Width: | Height: | Size: 877 KiB |
After Width: | Height: | Size: 661 KiB |
After Width: | Height: | Size: 654 KiB |
After Width: | Height: | Size: 661 KiB |
@ -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; |
|||
} |
@ -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); |
|||
}); |
|||
}, |
|||
}) |
|||
|
@ -1,42 +1,205 @@ |
|||
odoo.define('face_recognized_attendance_login.my_attendance', function(require){ |
|||
"use strict"; |
|||
/** |
|||
* 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 Widget = require('web.Widget'); |
|||
var rpc = require('web.rpc'); |
|||
var MyAttendances = require('hr_attendance.my_attendances'); |
|||
var login = 0 |
|||
// Login made possible, if and only if the captured image and face of the
|
|||
// employee matched
|
|||
MyAttendances.include({ |
|||
update_attendance: async function () { |
|||
await rpc.query({ |
|||
model:'hr.employee', |
|||
method:'get_login_screen' |
|||
}).then(function (data) { |
|||
login = data |
|||
}); |
|||
if (login==1){ |
|||
var self = this; |
|||
this._rpc({ |
|||
odoo.define('face_recognized_attendance_login.my_attendance', function(require) { |
|||
"use strict"; |
|||
// Required Odoo dependencies
|
|||
var core = require('web.core'); |
|||
var Widget = require('web.Widget'); |
|||
var rpc = require('web.rpc'); |
|||
var MyAttendances = require('hr_attendance.my_attendances'); |
|||
var _t = core._t; |
|||
var login = 0; |
|||
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({ |
|||
events: _.extend({}, MyAttendances.prototype.events, { |
|||
'click #close_qr_scanner': 'stopWebcamAndDetection', |
|||
}), |
|||
update_attendance: async function() { |
|||
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', |
|||
method: 'get_login_screen', |
|||
}); |
|||
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(); |
|||
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({ |
|||
model: 'hr.employee', |
|||
method: 'attendance_manual', |
|||
args: [[self.employee.id], 'hr_attendance.hr_attendance_action_my_attendances'], |
|||
}) |
|||
.then(function(result) { |
|||
args: [[self.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); |
|||
}); |
|||
} |
|||
else{ |
|||
window.alert("Failed to recognize the face. Please try again....") |
|||
} |
|||
} |
|||
}); |
|||
}, |
|||
}); |
|||
}); |
|||
|
@ -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": [ |
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@ -0,0 +1,606 @@ |
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@ -0,0 +1,397 @@ |
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@ -0,0 +1,273 @@ |
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|||
}, |
|||
{ |
|||
"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" |
|||
] |
|||
} |
|||
] |
@ -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> |
@ -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> |
@ -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> |
|||
|
|||
|