FaceAPI: AI-powered Face Detection & Rotation Tracking, Face Description & Recognition, Age & Gender & Emotion Prediction for Browser and NodeJS using TensorFlow/JS

Overview

Git Version NPM Version Last Commit License GitHub Status Checks Vulnerabilities

FaceAPI

AI-powered Face Detection & Rotation Tracking, Face Description & Recognition, Age & Gender & Emotion Prediction for Browser and NodeJS using TensorFlow/JS


Live Demo: https://vladmandic.github.io/face-api/demo/webcam.html


Additional Documentation




Examples


Browser

Browser example that uses static images and showcases both models
as well as all of the extensions is included in /demo/index.html
Example can be accessed directly using Git pages using URL:
https://vladmandic.github.io/face-api/demo/index.html

Browser example that uses live webcam is included in /demo/webcam.html
Example can be accessed directly using Git pages using URL:
https://vladmandic.github.io/face-api/demo/webcam.html


Demo using FaceAPI to process images
Note: Photos shown below are taken by me

screenshot

Demo using FaceAPI to process live webcam

screenshot


NodeJS

Three NodeJS examples are:

  • /demo/node.js:
    Regular usage of FaceAPI from NodeJS
    Using TFJS native methods to load images without external dependencies
  • /demo/node-canvas.js:
    Regular usage of FaceAPI from NodeJS
    Using external canvas module to load images
    Which also allows for image drawing and saving inside NodeJS environment
  • /demo/node-multiprocess.js:
    Multiprocessing showcase that uses pool of worker processes
    (node-multiprocess-worker.js)
    Main starts fixed pool of worker processes with each worker having
    it's instance of FaceAPI
    Workers communicate with main when they are ready and main dispaches
    job to each ready worker until job queue is empty
2021-03-14 08:42:03 INFO:  @vladmandic/face-api version 1.0.2
2021-03-14 08:42:03 INFO:  User: vlado Platform: linux Arch: x64 Node: v15.7.0
2021-03-14 08:42:03 INFO:  FaceAPI multi-process test
2021-03-14 08:42:03 STATE:  Main: started worker: 1888019
2021-03-14 08:42:03 STATE:  Main: started worker: 1888025
2021-03-14 08:42:04 STATE:  Worker: PID: 1888025 TensorFlow/JS 3.3.0 FaceAPI 1.0.2 Backend: tensorflow
2021-03-14 08:42:04 STATE:  Worker: PID: 1888019 TensorFlow/JS 3.3.0 FaceAPI 1.0.2 Backend: tensorflow
2021-03-14 08:42:04 STATE:  Main: dispatching to worker: 1888019
2021-03-14 08:42:04 STATE:  Main: dispatching to worker: 1888025
2021-03-14 08:42:04 DATA:  Worker received message: 1888019 { image: 'demo/sample1.jpg' }
2021-03-14 08:42:04 DATA:  Worker received message: 1888025 { image: 'demo/sample2.jpg' }
2021-03-14 08:42:06 DATA:  Main: worker finished: 1888025 detected faces: 3
2021-03-14 08:42:06 STATE:  Main: dispatching to worker: 1888025
2021-03-14 08:42:06 DATA:  Worker received message: 1888025 { image: 'demo/sample3.jpg' }
2021-03-14 08:42:06 DATA:  Main: worker finished: 1888019 detected faces: 3
2021-03-14 08:42:06 STATE:  Main: dispatching to worker: 1888019
2021-03-14 08:42:06 DATA:  Worker received message: 1888019 { image: 'demo/sample4.jpg' }
2021-03-14 08:42:07 DATA:  Main: worker finished: 1888025 detected faces: 3
2021-03-14 08:42:07 STATE:  Main: dispatching to worker: 1888025
2021-03-14 08:42:07 DATA:  Worker received message: 1888025 { image: 'demo/sample5.jpg' }
2021-03-14 08:42:08 DATA:  Main: worker finished: 1888019 detected faces: 4
2021-03-14 08:42:08 STATE:  Main: dispatching to worker: 1888019
2021-03-14 08:42:08 DATA:  Worker received message: 1888019 { image: 'demo/sample6.jpg' }
2021-03-14 08:42:09 DATA:  Main: worker finished: 1888025 detected faces: 5
2021-03-14 08:42:09 STATE:  Main: worker exit: 1888025 0
2021-03-14 08:42:09 DATA:  Main: worker finished: 1888019 detected faces: 4
2021-03-14 08:42:09 INFO:  Processed 15 images in 5944 ms
2021-03-14 08:42:09 STATE:  Main: worker exit: 1888019 0

Note that @tensorflow/tfjs-node or @tensorflow/tfjs-node-gpu
must be installed before using NodeJS example




Quick Start

Simply include latest version of FaceAPI directly from a CDN in your HTML:
(pick one, jsdelivr or unpkg)

">
<script src="https://cdn.jsdelivr.net/npm/@vladmandic/face-api/dist/face-api.js">script>
<script src="https://unpkg.dev/@vladmandic/face-api/dist/face-api.js">script>

Installation

FaceAPI ships with several pre-build versions of the library:

  • dist/face-api.js: IIFE format for client-side Browser execution
    with TFJS pre-bundled
  • dist/face-api.esm.js: ESM format for client-side Browser execution
    with TFJS pre-bundled
  • dist/face-api.esm-nobundle.js: ESM format for client-side Browser execution
    without TFJS pre-bundled
  • dist/face-api.node.js: CommonJS format for server-side NodeJS execution
    without TFJS pre-bundled
  • dist/face-api.node-gpu.js: CommonJS format for server-side NodeJS execution
    without TFJS pre-bundled and optimized for CUDA GPU acceleration

Defaults are:

{
  "main": "dist/face-api.node-js",
  "module": "dist/face-api.esm.js",
  "browser": "dist/face-api.esm.js",
}

Bundled TFJS can be used directly via export: faceapi.tf

Reason for additional nobundle version is if you want to
include a specific version of TFJS and not rely on pre-packaged one

FaceAPI is compatible with TFJS 2.0+ and TFJS 3.0+

All versions include sourcemap




There are several ways to use FaceAPI:

1. IIFE script

Recommened for quick tests and backward compatibility with older Browsers that do not support ESM such as IE

This is simplest way for usage within Browser
Simply download dist/face-api.js, include it in your HTML file & it's ready to use:

">
<script src="https://cdn.jsdelivr.net/npm/@vladmandic/face-api/dist/face-api.js">script>

IIFE script bundles TFJS and auto-registers global namespace faceapi within Window object which can be accessed directly from a

Comments
  • Migration @vladmandic/face-api to old face-api

    Migration @vladmandic/face-api to old face-api

    Hi, What are steps that need to be done ? 1.pacakge json for @vladmandic/face-api we used: "@tensorflow/tfjs-node": "^3.9.0", "@vladmandic/face-api": "^1.5.4", what are in old face-api ? 2.The project old face-api written in typescript, can I used it in js ? 3.What about modal they can be loaded in startup like in @vladmandic/face-api ? 4.const faceapi = require('@vladmandic/face-api'); in old api how is it in js? 5.Does the interface(methods of faceapi are same on both platform ? Thanks,

    opened by danies8 53
  • how to fully optimize processing to take advance of all available hardware

    how to fully optimize processing to take advance of all available hardware

    I run this function:

      async function analyzeFrame (frameData, index) {
        const tensor = await getTensorFromBuffer(frameData)
        const faces = await faceapi.detectAllFaces(tensor, optionsSSDMobileNet).withFaceLandmarks().withFaceDescriptors()
        tensor.dispose()
        faces.forEach(async (face) => {
          // console.log(face)
        })
      }
    

    for hundreds of frames of a video. When doing so, it takes about half the time as if it where using only tfjs-node. It fills the RAM of my two 1080s, however the only usage that changes when I start the script is GPU 1s copy utilization goes to about 15%.

    I want to take better advantage of my hardware and run this faster.

    Windows 10, cuda 10, TFJS 2.7.0

    question 
    opened by Nuzzlet 33
  •   return process.dlopen(module, path.toNamespacedPath(filename));

    return process.dlopen(module, path.toNamespacedPath(filename));

    hey! im using your package in my project for face recognition and it works fine. i copied the same project to different computer and im getting this error. tried all solutions available online, reinstalled node modules a number of times, tried all versions of node and tensorflow as well as your package, not sure where is the error coming from.

    here is the error stack:

    return process.dlopen(module, path.toNamespacedPath(filename)); ^

    Error: A dynamic link library (DLL) initialization routine failed. \?\C:\Users\User\Documents\digitallending_sql\[email protected]\tfjs-node\lib\napi-v5\tfjs_binding.node at Object.Module._extensions..node (internal/modules/cjs/loader.js:1206:18) at Module.load (internal/modules/cjs/loader.js:1000:32) at Function.Module._load (internal/modules/cjs/loader.js:899:14) at Module.require (internal/modules/cjs/loader.js:1042:19) at require (internal/modules/cjs/helpers.js:77:18) at Object. (C:\Users\User\Documents\digitallending_sql\[email protected]\tfjs-node\dist\index.js:58:16) at Module._compile (internal/modules/cjs/loader.js:1156:30) at Object.Module._extensions..js (internal/modules/cjs/loader.js:1176:10) at Module.load (internal/modules/cjs/loader.js:1000:32) at Function.Module._load (internal/modules/cjs/loader.js:899:14) at Module.require (internal/modules/cjs/loader.js:1042:19) at require (internal/modules/cjs/helpers.js:77:18) at Object. (C:\Users\User\Documents\digitallending_sql\functions\facedetection.js:2:1) at Module._compile (internal/modules/cjs/loader.js:1156:30) at Object.Module._extensions..js (internal/modules/cjs/loader.js:1176:10) at Module.load (internal/modules/cjs/loader.js:1000:32) at Function.Module._load (internal/modules/cjs/loader.js:899:14) at Module.require (internal/modules/cjs/loader.js:1042:19) at require (internal/modules/cjs/helpers.js:77:18) at Object. (C:\Users\User\Documents\digitallending_sql\controllers\applicationController.js:6:20) at Module._compile (internal/modules/cjs/loader.js:1156:30) at Object.Module._extensions..js (internal/modules/cjs/loader.js:1176:10) at Module.load (internal/modules/cjs/loader.js:1000:32) at Function.Module._load (internal/modules/cjs/loader.js:899:14) at Module.require (internal/modules/cjs/loader.js:1042:19) at require (internal/modules/cjs/helpers.js:77:18) at Object. (C:\Users\User\Documents\digitallending_sql\routes\applicationRouter.js:3:29) at Module._compile (internal/modules/cjs/loader.js:1156:30)


    im using windows 10, node 12.16.2

    wontfix 
    opened by Muhammad-Ehsan-Ul-Haq 28
  • Unable to use faceapi in a nexjs - react application

    Unable to use faceapi in a nexjs - react application "Module not found: Can't resolve 'fs'"

    Issue Description Getting the following error:

    error - ./node_modules/@vladmandic/face-api/dist/face-api.esm.js:8:25031 Module not found: Can't resolve 'fs'

    Steps to Reproduce create a nextjs application as given here:

    https://nextjs.org/learn/basics/create-nextjs-app/setup

    added face api packages (npm install). Including tensorflow Invoked the api to load the models: await faceapi.nets.ssdMobilenetv1.loadFromUri('/models')

    And got the error:

    Expected Behavior It should have loaded the models.

    **Environment Windows 10. Nodejs. React application. Using VS code editor. Browser is chrome/Edge.

    • Module version?
    • Built-in demo or custom code? - custom
    • Type of module used (e.g. js, esm, esm-nobundle)? js
    • Browser or NodeJS and version (e.g. NodeJS 14.15 or Chrome 89)? - Node v14.13.1, Chrome Version 89.0.4389.90 (Official Build) (64-bit)
    • OS and Hardware platform (e.g. Windows 10, Ubuntu Linux on x64, Android 10)? Windows 10
    • Packager (if any) (e.g, webpack, rollup, parcel, esbuild, etc.)? standard webpack

    Additional

    • For installation or startup issues include your package.json
    • For usage issues, it is recommended to post your code as gist
    question 
    opened by karthik-Gopalan 26
  • Can't use in a lerna/create-react app project

    Can't use in a lerna/create-react app project

    I am using the library in a TypeScript lerna module which is build with tsc and then bundled as part of a create-react-app. I had no issue with the original face-api but wanted the latest fdjs. I am using the npm module with npm install.

    If I only do:

    import * as faceapi from '@vladmandic/face-api'

    I get a compile error:

    Failed to compile ../face-detect-plugin/node_modules/@vladmandic/face-api/dist/face-api.js 344:47 Module parse failed: Unexpected token (344:47) File was processed with these loaders:

    • ./node_modules/babel-loader/lib/index.js You may need an additional loader to handle the result of these loaders. | } : T || {}; |
        var E = g(f(T.entropy ? [x, w(e)] : x ?? y(), 3), _),
    

    | F = new d(_), | D = function () {

    if I add:

    import * as tf from '@tensorflow/tfjs'

    before importing face-api then I get an error in the console:

    Uncaught SyntaxError: Unexpected token '!'

    If I look at the code I see this:

    class MathBackendCPU extends !(function webpackMissingModule() { var e = new Error("Cannot find module '@tensorflow/tfjs-core'"); e.code = 'MODULE_NOT_FOUND'; throw e; }()) { constructor() { super(); this.blockSize = 48; this.firstUse = true; this.data = new !(function webpackMissingModule() { var e = new Error("Cannot find module '@tensorflow/tfjs-core'"); e.code = 'MODULE_NOT_FOUND'; throw e; }())(this, !(function webpackMissingModule() { var e = new Error("Cannot find module '@tensorflow/tfjs-core'"); e.code = 'MODULE_NOT_FOUND'; throw e; }())()); }

    question 
    opened by ost12666 23
  • Implement head position angle of  (yaw, roll, pitch)

    Implement head position angle of (yaw, roll, pitch)

    HI do you have plan to implement Head position angle of (Yaw, Roll, Pitch)

    pose: {
      pitch_angle: {value: 11.102898}
      roll_angle: {value: -20.291693}
      yaw_angle: {value: 14.172521}
    }
    

    like face-api discuss here https://github.com/justadudewhohacks/face-api.js/issues/107

    enhancement 
    opened by tianyingchun 19
  • There is a leak memory: faceapi.extractFaceTensors and  faceapi.extractFaces

    There is a leak memory: faceapi.extractFaceTensors and faceapi.extractFaces

    faceapi.tf.setBackend('webgl');
    faceapi.tf.enableProdMode();
    faceapi.tf.ENV.set('DEBUG', false);
    faceapi.tf.ready();
    
    .......
    const videoTensor = await faceapi.tf.browser.fromPixels(video);
    const detections = await faceapi.detectAllFaces(videoTensor, new faceapi.SsdMobilenetv1Options({ minConfidence: minScore, maxResults }));
    const faceImages = await faceapi.extractFaceTensors(videoTensor, detections);
    
    await videoTensor.dispose();
    await faceImages[0].dispose();
    
    

    I follow my GPU memory. I detect a leak memory. Maybe we can use x.dispose(); I tried it, but this problem continue... I checked faceapi.detectAllFaces function. There is not any leak. I think faceapi.extractFaceTensors function. How can I fix it?

    question 
    opened by umitkacar 19
  • @vladmandic/face-api/dist/face-api.node.js requires ES module???

    @vladmandic/face-api/dist/face-api.node.js requires ES module???

    trying to migrate to your fork of face-api

    Using:

    let faceapi   = require('@vladmandic/face-api/dist/face-api.node.js');
    

    I get:

    Error [ERR_REQUIRE_ESM]: Must use import to load ES Module: /home/meeki/node-red-contrib-facial-recognition/node_modules/@vladmandic/face-api/dist/face-api.node.js
    require() of ES modules is not supported.
    require() of /home/meeki/node-red-contrib-facial-recognition/node_modules/@vladmandic/face-api/dist/face-api.node.js from /home/meeki/node-red-contrib-facial-recognition/facial-recognition.js is an ES module file as it is a .js file whose nearest parent package.json contains "type": "module" which defines all .js files in that package scope as ES modules.
    Instead rename face-api.node.js to end in .cjs, change the requiring code to use import(), or remove "type": "module" from /home/meeki/node-red-contrib-facial-recognition/node_modules/@vladmandic/face-api/package.json.
    

    interesting

    bug help wanted 
    opened by meeki007 17
  • How does detectAllFaces function will handle fake image photo by mobile

    How does detectAllFaces function will handle fake image photo by mobile

    Hi, I used this code that detect all faces, I want to avoid that user will photo himself by cellular and show the cellular photo to camera , how I avoid by code ? For know fake image by cellular also work. I saw this link in history issue and there is no option do install through npm ? https://github.com/vladmandic/anti-spoofing

     const ssdOptions = { minConfidence: 0.1, maxResults: 10 };
          const optionsSSDMobileNet = new faceapi.SsdMobilenetv1Options(ssdOptions);
          const faces = await faceapi
            .detectAllFaces(tensor, optionsSSDMobileNet)
            .withFaceLandmarks()
            .withFaceExpressions()
            .withFaceDescriptors()
            .withAgeAndGender();
    
    
    opened by danies8 15
  • Resource load failed

    Resource load failed

    Issue Description Vue2 builds a demo, loadFromUri loads tinyFaceDetector, and loads loadFaceLandmarkModel, PC loads resources successfully, but Apple mobile safari fails to load

    Expected Behavior Resources can be loaded on both PC and mobile

    **Environment window 10 + chrome 98.0.4758.102(PC) + safari(mobile)

    • Module version? "@vladmandic/face-api": "^1.6.5" "vue": "^2.5.2"

    • Built-in demo or custom code? https://busyshadow.github.io/#/

    • Type of module used (e.g. js, esm, esm-nobundle)? js

    • Packager (if any) (e.g, webpack, rollup, parcel, esbuild, etc.)? webpack

    • For installation or startup issues include your package.json

    {
      "name": "faceDemo",
      "version": "1.0.0",
      "description": "A Vue.js project",
      "author": "",
      "private": true,
      "scripts": {
        "dev": "vue-cli-service serve",
        "build": "vue-cli-service build"
      },
      "dependencies": {
        "@vladmandic/face-api": "^1.6.5",
        "uglifyjs-webpack-plugin": "^2.2.0",
        "vconsole": "^3.12.0",
        "vue": "^2.5.2",
        "vue-router": "^3.1.6"
      },
      "devDependencies": {
        "@vue/cli-plugin-babel": "~4.3.1",
        "@vue/cli-plugin-router": "~4.3.1",
        "@vue/cli-service": "~4.3.1",
        "vue-template-compiler": "^2.6.11"
      },
      "engines": {
        "node": ">= 6.0.0",
        "npm": ">= 3.0.0"
      },
      "browserslist": [
        "> 1%",
        "last 2 versions",
        "not ie <= 8"
      ]
    }
    

    index.vue

    <template>
        <div>
            <div>err1:{{err1}}</div>
            <div>err2:{{err2}}</div>
        </div>
    </template>
    <script>
        import * as faceapi from '@vladmandic/face-api';
        // import * as faceapi from "face-api.js";
        import vconsole from 'vconsole';
        let _this;
        export default {
            data(){
                return {
                    err1:"",
                    err2:"",
                }
            },
            created(){
                new vconsole();
            },
            mounted(){
                _this = this;
                this.$nextTick(() => {
                    this.fnInit();
                });
            },
            methods:{
                async fnInit(){
                    try {
                        await faceapi.nets['tinyFaceDetector'].loadFromUri("https://busyshadow.github.io/models");
                    }catch(e){
                        this.err1 = e;
                    }
                    try {
                        await faceapi.loadFaceLandmarkModel("https://busyshadow.github.io/models");
                    } catch(e){
                        this.err2 = e;
                    }
    
                    _this.options = new faceapi.TinyFaceDetectorOptions({
                        inputSize: 224, // 160 224 320 416 512 608
                        scoreThreshold: 0.3, // 0.1 ~ 0.9
                    });
                }
            }
        }
    </script>
    

    success success

    error error

    opened by busyShadow 14
  • faceapi is working for me on desktop but not on mobile

    faceapi is working for me on desktop but not on mobile

    faceapi is working for me on desktop but not on mobile.

    I am using wasm, as recommended to me and it worked perfect for a long time, both on desktop and mobil.

    import * as faceapi from "@vladmandic/face-api/dist/face-api.esm.js";

    async start() { /**el face api solo se necesita para el selfie */ if (this.type == "selfie") { await this.backendWasm(); await this.setupFaceAPI(); } } async setupFaceAPI() { await faceapi.nets.tinyFaceDetector.loadFromUri("/statics/models"); },

    async backendWasm() {
      await faceapi.tf.setWasmPaths("../statics/");
      await faceapi.tf.setBackend("wasm");
    },
    

    for a couple of days it stopped working on mobile, will it be a question of versions of the libraries?

    tensorflow face api ?? Captura de Pantalla 2021-06-28 a la(s) 1 33 21 p  m Captura de Pantalla 2021-06-28 a la(s) 12 57 45 p  m Captura de Pantalla 2021-06-28 a la(s) 12 57 50 p  m

    if you look at the first image they don't load all the wasm files, that's in mobile.

    but in the other two images, if you see if they load all the files, that's on desktop

    uso chrome.

    "@tensorflow/tfjs": "^3.3.0", "@tensorflow/tfjs-backend-wasm": "^3.3.0", "@vladmandic/face-api": "^1.1.12",

    Captura de Pantalla 2021-06-28 a la(s) 1 29 27 p  m
    opened by deylyn 14
Releases(1.7.1)
This is a collection of our NAS and Vision Transformer work.

This is a collection of our NAS and Vision Transformer work.

Microsoft 828 Dec 28, 2022
Project repo for the paper SILT: Self-supervised Lighting Transfer Using Implicit Image Decomposition

SILT: Self-supervised Lighting Transfer Using Implicit Image Decomposition (BMVC 2021) Project repo for the paper SILT: Self-supervised Lighting Trans

6 Dec 04, 2022
PyTorch implementation of ARM-Net: Adaptive Relation Modeling Network for Structured Data.

A ready-to-use framework of latest models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, and etc.

48 Nov 30, 2022
Code of the paper "Multi-Task Meta-Learning Modification with Stochastic Approximation".

Multi-Task Meta-Learning Modification with Stochastic Approximation This repository contains the code for the paper "Multi-Task Meta-Learning Modifica

Andrew 3 Jan 05, 2022
PyTorch implementation of "Conformer: Convolution-augmented Transformer for Speech Recognition" (INTERSPEECH 2020)

PyTorch implementation of Conformer: Convolution-augmented Transformer for Speech Recognition. Transformer models are good at capturing content-based

Soohwan Kim 565 Jan 04, 2023
torchsummaryDynamic: support real FLOPs calculation of dynamic network or user-custom PyTorch ops

torchsummaryDynamic Improved tool of torchsummaryX. torchsummaryDynamic support real FLOPs calculation of dynamic network or user-custom PyTorch ops.

Bohong Chen 1 Jan 07, 2022
This library contains a Tensorflow implementation of the paper Stability Analysis of Unfolded WMMSE for Power Allocation

UWMMSE-stability Tensorflow implementation of Stability Analysis of UWMMSE Overview This library contains a Tensorflow implementation of the paper Sta

Arindam Chowdhury 1 Nov 16, 2022
MASS (Mueen's Algorithm for Similarity Search) - a python 2 and 3 compatible library used for searching time series sub-sequences under z-normalized Euclidean distance for similarity.

Introduction MASS allows you to search a time series for a subquery resulting in an array of distances. These array of distances enable you to identif

Matrix Profile Foundation 79 Dec 31, 2022
A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis

A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis Figure: Shape-Accurate 3D-Aware Image Synthesis. A Shading-Guid

Xingang Pan 115 Dec 18, 2022
using yolox+deepsort for object-tracker

YOLOX_deepsort_tracker yolox+deepsort实现目标跟踪 最新的yolox尝尝鲜~~(yolox正处在频繁更新阶段,因此直接链接yolox仓库作为子模块) Install Clone the repository recursively: git clone --rec

245 Dec 26, 2022
Hierarchical Time Series Forecasting with a familiar API

scikit-hts Hierarchical Time Series with a familiar API. This is the result from not having found any good implementations of HTS on-line, and my work

Carlo Mazzaferro 204 Dec 17, 2022
NLMpy - A Python package to create neutral landscape models

NLMpy is a Python package for the creation of neutral landscape models that are widely used by landscape ecologists to model ecological patterns

Manaaki Whenua – Landcare Research 1 Oct 08, 2022
Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

François Chollet 16.2k Dec 30, 2022
Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation

SimplePose Code and pre-trained models for our paper, “Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation”, a

Jia Li 256 Dec 24, 2022
StyleGAN-Human: A Data-Centric Odyssey of Human Generation

StyleGAN-Human: A Data-Centric Odyssey of Human Generation Abstract: Unconditional human image generation is an important task in vision and graphics,

stylegan-human 762 Jan 08, 2023
This is a repo of basic Machine Learning!

Basic Machine Learning This repository contains a topic-wise curated list of Machine Learning and Deep Learning tutorials, articles and other resource

Ekram Asif 53 Dec 31, 2022
[SIGGRAPH 2021 Asia] DeepVecFont: Synthesizing High-quality Vector Fonts via Dual-modality Learning

DeepVecFont This is the official Pytorch implementation of the paper: Yizhi Wang and Zhouhui Lian. DeepVecFont: Synthesizing High-quality Vector Fonts

Yizhi Wang 146 Dec 18, 2022
clDice - a Novel Topology-Preserving Loss Function for Tubular Structure Segmentation

README clDice - a Novel Topology-Preserving Loss Function for Tubular Structure Segmentation CVPR 2021 Authors: Suprosanna Shit and Johannes C. Paetzo

110 Dec 29, 2022
tensorflow implementation of 'YOLO : Real-Time Object Detection'

YOLO_tensorflow (Version 0.3, Last updated :2017.02.21) 1.Introduction This is tensorflow implementation of the YOLO:Real-Time Object Detection It can

Jinyoung Choi 1.7k Nov 21, 2022
This repo implements several applications of the proposed generalized Bures-Wasserstein (GBW) geometry on symmetric positive definite matrices.

GBW This repo implements several applications of the proposed generalized Bures-Wasserstein (GBW) geometry on symmetric positive definite matrices. Ap

Andi Han 0 Oct 22, 2021