BLUE PURPLE
8 months ago
264 changed files with 21682 additions and 56298 deletions
|
Before Width: | Height: | Size: 145 KiB After Width: | Height: | Size: 142 KiB |
|
Before Width: | Height: | Size: 89 KiB After Width: | Height: | Size: 121 KiB |
|
After Width: | Height: | Size: 85 KiB |
File diff suppressed because it is too large
File diff suppressed because it is too large
File diff suppressed because one or more lines are too long
@ -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(); |
|||
} |
|||
}, |
|||
}); |
|||
Binary file not shown.
@ -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" |
|||
] |
|||
} |
|||
] |
|||
Binary file not shown.
@ -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" |
|||
] |
|||
} |
|||
] |
|||
Binary file not shown.
@ -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" |
|||
] |
|||
} |
|||
] |
|||
Binary file not shown.
@ -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" |
|||
] |
|||
} |
|||
] |
|||
Binary file not shown.
File diff suppressed because one or more lines are too long
File diff suppressed because it is too large
Binary file not shown.
@ -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 |
|||
] |
|||
} |
|||
] |
|||
} |
|||
] |
|||
Binary file not shown.
File diff suppressed because one or more lines are too long
File diff suppressed because it is too large
Binary file not shown.
@ -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" |
|||
] |
|||
} |
|||
] |
|||
@ -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> |
|||
@ -0,0 +1,46 @@ |
|||
.. image:: https://img.shields.io/badge/licence-AGPL--3-blue.svg |
|||
:target: https://www.gnu.org/licenses/agpl-3.0-standalone.html |
|||
:alt: License: AGPL-3 |
|||
|
|||
Theme Voltro |
|||
============ |
|||
* Attractive and modern eCommerce Website theme for Odoo 17 |
|||
|
|||
Configuration |
|||
============= |
|||
* No need of additional configuration. |
|||
|
|||
License |
|||
------- |
|||
Affero General Public License, Version 3 (AGPL-3). |
|||
(https://www.gnu.org/licenses/agpl-3.0.en.html) |
|||
|
|||
Company |
|||
------- |
|||
* `Cybrosys Techno Solutions <https://cybrosys.com/>`__ |
|||
|
|||
Credits |
|||
======= |
|||
* Developer: (v17) Anfas Faisal K, Contact: odoo@cybrosys.com |
|||
|
|||
Contacts |
|||
-------- |
|||
* Mail Contact : odoo@cybrosys.com |
|||
* Website : https://cybrosys.com |
|||
|
|||
Bug Tracker |
|||
----------- |
|||
Bugs are tracked on GitHub Issues. In case of trouble, please check there if your issue has already been reported. |
|||
|
|||
Maintainer |
|||
========== |
|||
.. image:: https://cybrosys.com/images/logo.png |
|||
:target: https://cybrosys.com |
|||
|
|||
This module is maintained by Cybrosys Technologies. |
|||
|
|||
For support and more information, please visit `Our Website <https://cybrosys.com/>`__ |
|||
|
|||
Further information |
|||
=================== |
|||
HTML Description: `<static/description/index.html>`__ |
|||
@ -0,0 +1,23 @@ |
|||
# -*- coding: utf-8 -*- |
|||
################################################################################ |
|||
# |
|||
# Cybrosys Technologies Pvt. Ltd. |
|||
# |
|||
# Copyright (C) 2024-TODAY Cybrosys Technologies(<https://www.cybrosys.com>). |
|||
# Author: Anfas Faisal K (odoo@cybrosys.com) |
|||
# |
|||
# You can modify it under the terms of the GNU AFFERO |
|||
# GENERAL PUBLIC LICENSE (AGPL v3), Version 3. |
|||
# |
|||
# This program is distributed in the hope that it will be useful, |
|||
# but WITHOUT ANY WARRANTY; without even the implied warranty of |
|||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
|||
# GNU AFFERO GENERAL PUBLIC LICENSE (AGPL v3) for more details. |
|||
# |
|||
# You should have received a copy of the GNU AFFERO GENERAL PUBLIC LICENSE |
|||
# (AGPL v3) along with this program. |
|||
# If not, see <http://www.gnu.org/licenses/>. |
|||
# |
|||
################################################################################ |
|||
from . import controllers |
|||
from . import models |
|||
@ -0,0 +1,98 @@ |
|||
# -*- coding: utf-8 -*- |
|||
################################################################################ |
|||
# |
|||
# Cybrosys Technologies Pvt. Ltd. |
|||
# |
|||
# Copyright (C) 2024-TODAY Cybrosys Technologies(<https://www.cybrosys.com>). |
|||
# Author: Anfas Faisal K (odoo@cybrosys.com) |
|||
# |
|||
# You can modify it under the terms of the GNU AFFERO |
|||
# GENERAL PUBLIC LICENSE (AGPL v3), Version 3. |
|||
# |
|||
# This program is distributed in the hope that it will be useful, |
|||
# but WITHOUT ANY WARRANTY; without even the implied warranty of |
|||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
|||
# GNU AFFERO GENERAL PUBLIC LICENSE (AGPL v3) for more details. |
|||
# |
|||
# You should have received a copy of the GNU AFFERO GENERAL PUBLIC LICENSE |
|||
# (AGPL v3) along with this program. |
|||
# If not, see <http://www.gnu.org/licenses/>. |
|||
# |
|||
################################################################################ |
|||
{ |
|||
'name': "Theme Voltro", |
|||
'version': "17.0.1.0.0", |
|||
'category': 'Theme/Corporate', |
|||
'summary': 'Theme Voltro is an advanced eCommerce theme crafted for ' |
|||
'digital product marketplaces. It transforms your online ' |
|||
'store into a sophisticated, technology-focused platform' |
|||
' with a sleek dark mode interface and modern design.', |
|||
'description': 'Theme Voltro is an Advanced eCommerce Theme designed specifically' |
|||
' for Digital Product Marketplaces. This Theme transforms your ' |
|||
'online store into a sophisticated technology-focused platform ' |
|||
'with its sleek dark mode interface and modern aesthetics.', |
|||
'author': 'Cybrosys Techno Solutions', |
|||
'company': 'Cybrosys Techno Solutions', |
|||
'maintainer': 'Cybrosys Techno Solutions', |
|||
'website': 'https://www.cybrosys.com', |
|||
'depends': ['website', 'mail', 'website_sale_wishlist', |
|||
'website_sale_comparison'], |
|||
'data': [ |
|||
'data/website_menus.xml', |
|||
'views/home.xml', |
|||
'views/header.xml', |
|||
'views/footer.xml', |
|||
'views/contact_us.xml', |
|||
'views/about.xml', |
|||
'views/shop.xml', |
|||
'views/product_template_views.xml', |
|||
'views/product_view_template.xml', |
|||
'views/snippets/banner.xml', |
|||
'views/snippets/product_categories.xml', |
|||
'views/snippets/offer.xml', |
|||
'views/snippets/arrivals.xml', |
|||
'views/snippets/launches.xml', |
|||
'views/snippets/brands.xml', |
|||
'views/snippets/contact_us.xml', |
|||
'views/snippets/sub_banner.xml', |
|||
'views/snippets/services.xml', |
|||
'views/snippets/about_story.xml', |
|||
'views/snippets/achievements.xml', |
|||
'views/snippets/about_team.xml', |
|||
], |
|||
'assets': { |
|||
'web.assets_frontend': [ |
|||
"/theme_voltro/static/src/js/owl.carousel.js", |
|||
"/theme_voltro/static/src/js/owl.carousel.min.js", |
|||
"/theme_voltro/static/src/js/product_tab.js", |
|||
"/theme_voltro/static/src/js/product_category.js", |
|||
"/theme_voltro/static/src/js/achievements_counter.js", |
|||
"/theme_voltro/static/src/js/zoom_image.js", |
|||
"/theme_voltro/static/src/xml/product_arrival_template.xml", |
|||
"/theme_voltro/static/src/js/brands.js", |
|||
"https://cdnjs.cloudflare.com/ajax/libs/gsap/3.12.0/gsap.min.js", |
|||
"https://cdnjs.cloudflare.com/ajax/libs/gsap/3.12.0/ScrollTrigger.min.js", |
|||
"https://cdn.jsdelivr.net/npm/gsap@3.12.5/dist/EasePack.min.js", |
|||
"https://cdn.jsdelivr.net/npm/gsap@3.12.5/dist/CustomEase.min.js", |
|||
"https://cdn.jsdelivr.net/npm/bootstrap@5.3.3/dist/css/bootstrap.min.css", |
|||
"https://cdnjs.cloudflare.com/ajax/libs/OwlCarousel2/2.3.4/assets/owl.theme.default.min.css", |
|||
"https://cdn.jsdelivr.net/npm/bootstrap-icons@1.11.3/font/bootstrap-icons.min.css", |
|||
"https://cdnjs.cloudflare.com/ajax/libs/OwlCarousel2/2.3.4/assets/owl.carousel.min.css", |
|||
"https://cdn.jsdelivr.net/npm/@splidejs/splide/dist/css/splide.min.css", |
|||
"https://cdn.jsdelivr.net/npm/@splidejs/splide/dist/js/splide.min.js", |
|||
"https://cdn.jsdelivr.net/npm/drift-zoom/dist/Drift.min.js", |
|||
"https://cdn.jsdelivr.net/npm/drift-zoom/dist/drift-basic.min.css", |
|||
"/theme_voltro/static/src/js/thumbnail.carousel.js", |
|||
"/theme_voltro/static/src/js/home_banner.js", |
|||
"/theme_voltro/static/src/css/style.css", |
|||
], |
|||
}, |
|||
"images": [ |
|||
"static/description/banner.jpg", |
|||
"static/description/theme_screenshot.jpg", |
|||
], |
|||
"license": "AGPL-3", |
|||
'installable': True, |
|||
'auto_install': False, |
|||
'application': False, |
|||
} |
|||
@ -0,0 +1,24 @@ |
|||
# -*- coding: utf-8 -*- |
|||
################################################################################ |
|||
# |
|||
# Cybrosys Technologies Pvt. Ltd. |
|||
# |
|||
# Copyright (C) 2024-TODAY Cybrosys Technologies(<https://www.cybrosys.com>). |
|||
# Author: Anfas Faisal K (odoo@cybrosys.com) |
|||
# |
|||
# You can modify it under the terms of the GNU AFFERO |
|||
# GENERAL PUBLIC LICENSE (AGPL v3), Version 3. |
|||
# |
|||
# This program is distributed in the hope that it will be useful, |
|||
# but WITHOUT ANY WARRANTY; without even the implied warranty of |
|||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
|||
# GNU AFFERO GENERAL PUBLIC LICENSE (AGPL v3) for more details. |
|||
# |
|||
# You should have received a copy of the GNU AFFERO GENERAL PUBLIC LICENSE |
|||
# (AGPL v3) along with this program. |
|||
# If not, see <http://www.gnu.org/licenses/>. |
|||
# |
|||
################################################################################ |
|||
from . import voltro |
|||
from . import custom_website_form |
|||
from . import product_snippets |
|||
@ -0,0 +1,43 @@ |
|||
# -*- coding: utf-8 -*- |
|||
################################################################################ |
|||
# |
|||
# Cybrosys Technologies Pvt. Ltd. |
|||
# |
|||
# Copyright (C) 2024-TODAY Cybrosys Technologies(<https://www.cybrosys.com>). |
|||
# Author: Anfas Faisal K (odoo@cybrosys.com) |
|||
# |
|||
# You can modify it under the terms of the GNU AFFERO |
|||
# GENERAL PUBLIC LICENSE (AGPL v3), Version 3. |
|||
# |
|||
# This program is distributed in the hope that it will be useful, |
|||
# but WITHOUT ANY WARRANTY; without even the implied warranty of |
|||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
|||
# GNU AFFERO GENERAL PUBLIC LICENSE (AGPL v3) for more details. |
|||
# |
|||
# You should have received a copy of the GNU AFFERO GENERAL PUBLIC LICENSE |
|||
# (AGPL v3) along with this program. |
|||
# If not, see <http://www.gnu.org/licenses/>. |
|||
# |
|||
################################################################################ |
|||
from odoo import http |
|||
from odoo.addons.website.controllers.form import WebsiteForm |
|||
|
|||
class CustomWebsiteForm(WebsiteForm): |
|||
""" |
|||
This class extends the WebsiteForm controller in Odoo to allow custom handling |
|||
of form submissions from the website. Specifically, it modifies form submissions |
|||
for the 'mail.mail' model to concatenate the 'name' and 'second_name' fields |
|||
into a single 'name' field before processing the form. |
|||
""" |
|||
@http.route('/website/form/<string:model_name>', type='http', |
|||
auth="public", methods=['POST'], website=True) |
|||
def website_form(self, model_name, **kwargs): |
|||
""" |
|||
If the model is 'mail.mail' and the fields 'name' and 'second_name' are |
|||
provided, it concatenates these two fields into the 'name' field. |
|||
""" |
|||
if model_name == 'mail.mail': |
|||
if 'name' in kwargs and 'second_name' in kwargs: |
|||
kwargs['name'] = f"{kwargs['name']} {kwargs['second_name']}" |
|||
kwargs.pop('second_name', None) |
|||
return super(CustomWebsiteForm, self).website_form(model_name, **kwargs) |
|||
@ -0,0 +1,57 @@ |
|||
# -*- coding: utf-8 -*- |
|||
################################################################################ |
|||
# |
|||
# Cybrosys Technologies Pvt. Ltd. |
|||
# |
|||
# Copyright (C) 2024-TODAY Cybrosys Technologies(<https://www.cybrosys.com>). |
|||
# Author: Anfas Faisal K (odoo@cybrosys.com) |
|||
# |
|||
# You can modify it under the terms of the GNU AFFERO |
|||
# GENERAL PUBLIC LICENSE (AGPL v3), Version 3. |
|||
# |
|||
# This program is distributed in the hope that it will be useful, |
|||
# but WITHOUT ANY WARRANTY; without even the implied warranty of |
|||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
|||
# GNU AFFERO GENERAL PUBLIC LICENSE (AGPL v3) for more details. |
|||
# |
|||
# You should have received a copy of the GNU AFFERO GENERAL PUBLIC LICENSE |
|||
# (AGPL v3) along with this program. |
|||
# If not, see <http://www.gnu.org/licenses/>. |
|||
# |
|||
################################################################################ |
|||
from odoo import http |
|||
from odoo.http import request |
|||
|
|||
|
|||
class WebsiteProduct(http.Controller): |
|||
@http.route('/get_product_arrivals', auth="public", type='json', website=True) |
|||
def get_product_arrivals(self): |
|||
"""Get the website arrival products for snippet""" |
|||
new_arrivals = request.env['product.template'].sudo().search_read( |
|||
[('website_published', '=', True)], |
|||
order='create_date desc', limit=4) |
|||
values = { |
|||
'new_arrivals': new_arrivals, |
|||
'symbol': request.env.user.company_id.currency_id.symbol |
|||
} |
|||
response = http.Response(template='theme_voltro.arrival_product_show', |
|||
qcontext=values) |
|||
return response.render() |
|||
|
|||
@http.route('/get_product_categories', auth="public", type='json', website=True) |
|||
def get_product_category(self): |
|||
"""Get the website arrival products for snippet""" |
|||
public_categ_id = request.env[ |
|||
'product.public.category'].sudo().search_read( |
|||
[('parent_id', '=', False)], fields=['name', 'image_1920','id']) |
|||
|
|||
values = { |
|||
'categories': public_categ_id, |
|||
} |
|||
response = http.Response(template='theme_voltro.product_categories_show', |
|||
qcontext=values) |
|||
return response.render() |
|||
|
|||
|
|||
|
|||
|
|||
@ -0,0 +1,42 @@ |
|||
# -*- coding: utf-8 -*- |
|||
################################################################################ |
|||
# |
|||
# Cybrosys Technologies Pvt. Ltd. |
|||
# |
|||
# Copyright (C) 2024-TODAY Cybrosys Technologies(<https://www.cybrosys.com>). |
|||
# Author: Anfas Faisal K (odoo@cybrosys.com) |
|||
# |
|||
# You can modify it under the terms of the GNU AFFERO |
|||
# GENERAL PUBLIC LICENSE (AGPL v3), Version 3. |
|||
# |
|||
# This program is distributed in the hope that it will be useful, |
|||
# but WITHOUT ANY WARRANTY; without even the implied warranty of |
|||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
|||
# GNU AFFERO GENERAL PUBLIC LICENSE (AGPL v3) for more details. |
|||
# |
|||
# You should have received a copy of the GNU AFFERO GENERAL PUBLIC LICENSE |
|||
# (AGPL v3) along with this program. |
|||
# If not, see <http://www.gnu.org/licenses/>. |
|||
# |
|||
################################################################################ |
|||
import logging |
|||
from odoo import http |
|||
from odoo.http import request |
|||
|
|||
_logger = logging.getLogger(__name__) |
|||
|
|||
class MenuController(http.Controller): |
|||
""" |
|||
Controller for handling redirections to various pages based on menu clicks. |
|||
|
|||
This class defines several routes that redirect users to different pages |
|||
in the website based on the menus clicked. Each method corresponds to a specific |
|||
page in the 'theme_voltro' theme. |
|||
|
|||
""" |
|||
|
|||
@http.route('/about', website=True, type='http', auth='public',csrf=False) |
|||
def home_page(self): |
|||
"""Redirect to the about page.""" |
|||
return request.render('theme_voltro.about_page') |
|||
|
|||
@ -0,0 +1,12 @@ |
|||
<?xml version="1.0" encoding="UTF-8" ?> |
|||
<odoo> |
|||
<data> |
|||
<!-- Menu for pages --> |
|||
<record id="menu_about" model="website.menu"> |
|||
<field name="name">About</field> |
|||
<field name="url">/about</field> |
|||
<field name="parent_id" ref="website.main_menu"/> |
|||
<field name="sequence" type="int">15</field> |
|||
</record> |
|||
</data> |
|||
</odoo> |
|||
@ -0,0 +1,6 @@ |
|||
## Module <theme_voltro> |
|||
|
|||
#### 14.11.2024 |
|||
#### Version 17.0.1.0.0 |
|||
#### ADD |
|||
- Initial commit for Theme Voltro |
|||
@ -0,0 +1,22 @@ |
|||
# -*- coding: utf-8 -*- |
|||
################################################################################ |
|||
# |
|||
# Cybrosys Technologies Pvt. Ltd. |
|||
# |
|||
# Copyright (C) 2024-TODAY Cybrosys Technologies(<https://www.cybrosys.com>). |
|||
# Author: Anfas Faisal K (odoo@cybrosys.com) |
|||
# |
|||
# You can modify it under the terms of the GNU AFFERO |
|||
# GENERAL PUBLIC LICENSE (AGPL v3), Version 3. |
|||
# |
|||
# This program is distributed in the hope that it will be useful, |
|||
# but WITHOUT ANY WARRANTY; without even the implied warranty of |
|||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
|||
# GNU AFFERO GENERAL PUBLIC LICENSE (AGPL v3) for more details. |
|||
# |
|||
# You should have received a copy of the GNU AFFERO GENERAL PUBLIC LICENSE |
|||
# (AGPL v3) along with this program. |
|||
# If not, see <http://www.gnu.org/licenses/>. |
|||
# |
|||
################################################################################ |
|||
from . import product_template |
|||
@ -0,0 +1,32 @@ |
|||
# -*- coding: utf-8 -*- |
|||
################################################################################ |
|||
# |
|||
# Cybrosys Technologies Pvt. Ltd. |
|||
# |
|||
# Copyright (C) 2024-TODAY Cybrosys Technologies(<https://www.cybrosys.com>). |
|||
# Author: Anfas Faisal K (odoo@cybrosys.com) |
|||
# |
|||
# You can modify it under the terms of the GNU AFFERO |
|||
# GENERAL PUBLIC LICENSE (AGPL v3), Version 3. |
|||
# |
|||
# This program is distributed in the hope that it will be useful, |
|||
# but WITHOUT ANY WARRANTY; without even the implied warranty of |
|||
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
|||
# GNU AFFERO GENERAL PUBLIC LICENSE (AGPL v3) for more details. |
|||
# |
|||
# You should have received a copy of the GNU AFFERO GENERAL PUBLIC LICENSE |
|||
# (AGPL v3) along with this program. |
|||
# If not, see <http://www.gnu.org/licenses/>. |
|||
# |
|||
################################################################################ |
|||
from odoo import models, fields |
|||
|
|||
class ProductTemplate(models.Model): |
|||
""" |
|||
Inherits the 'product.template' model to add a new field for product |
|||
highlights. |
|||
""" |
|||
_inherit = 'product.template' |
|||
|
|||
product_highlights = fields.Text(string="Product Highlights", |
|||
help="Key highlights or features of the product.") |
|||
|
After Width: | Height: | Size: 431 KiB |
|
After Width: | Height: | Size: 135 KiB |
|
After Width: | Height: | Size: 327 KiB |
|
After Width: | Height: | Size: 192 KiB |
|
After Width: | Height: | Size: 138 KiB |
|
After Width: | Height: | Size: 104 KiB |
|
After Width: | Height: | Size: 70 KiB |
|
After Width: | Height: | Size: 142 KiB |
|
After Width: | Height: | Size: 193 KiB |
|
After Width: | Height: | Size: 210 KiB |
|
After Width: | Height: | Size: 140 KiB |
|
After Width: | Height: | Size: 755 KiB |
|
After Width: | Height: | Size: 629 KiB |
|
After Width: | Height: | Size: 44 KiB |
|
After Width: | Height: | Size: 26 KiB |
|
After Width: | Height: | Size: 311 KiB |
|
After Width: | Height: | Size: 163 KiB |
|
After Width: | Height: | Size: 142 KiB |
|
After Width: | Height: | Size: 4.8 MiB |
|
After Width: | Height: | Size: 24 MiB |
|
After Width: | Height: | Size: 30 KiB |
|
After Width: | Height: | Size: 784 KiB |
|
After Width: | Height: | Size: 1.1 KiB |
|
After Width: | Height: | Size: 17 KiB |
|
After Width: | Height: | Size: 431 KiB |
|
After Width: | Height: | Size: 1.2 MiB |
|
After Width: | Height: | Size: 1.2 KiB |
|
After Width: | Height: | Size: 249 KiB |
|
After Width: | Height: | Size: 1.4 KiB |
|
After Width: | Height: | Size: 1.7 KiB |
|
After Width: | Height: | Size: 2.2 KiB |
|
After Width: | Height: | Size: 3.4 MiB |
|
After Width: | Height: | Size: 1.3 KiB |
|
After Width: | Height: | Size: 24 MiB |
|
After Width: | Height: | Size: 2.1 KiB |
|
After Width: | Height: | Size: 929 B |
|
After Width: | Height: | Size: 23 KiB |
Some files were not shown because too many files changed in this diff
Loading…
Reference in new issue