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This is the official Discord of faceswap. | 27355 members.
Swapping demo. Official Discord demo for InsightFace face swapping. InsightFace: an open source 2D&3D deep face analysis library.
- Overview
- License
- Top News
- Introduction
- Quick Start
- Projects
- Face Recognition
- Face Detection
- Face Alignment
- Citation
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InsightFace project is mainly maintained By Jia Guo and Jiankang Deng.
For all main contributors, please check contributing.
The code of InsightFace is released under the MIT License. There is no limitation for both academic and commercial usage.
The training data containing the annotation (and the models trained with these data) are available for non-commercial research purposes only.
2023-08-08: We released the implementation of Generalizing Gaze Estimation with Weak-Supervision from Synthetic Views at reconstruction/gaze.
2023-05-03: We have launched the ongoing version of wild face anti-spoofing challenge. See details here.
2023-04-01: We move the swapping demo to Discord bot, which support editing on Midjourney generated images, see detail at web-demos/swapping_discord.
2023-02-13: We launch a large scale in the wild face anti-spoofing challenge on CVPR23 Workshop, see details at challenges/cvpr23-fas-wild.
2022-11-28: Single line code for facial identity swapping in our python packge ver 0.7, please check the example here.
2022-10-28: MFR-Ongoing website is refactored, please create issues if there's any bug.
InsightFace is an open source 2D&3D deep face analysis toolbox, mainly based on PyTorch and MXNet.
Please check our website for detail.
The master branch works with PyTorch 1.6+ and/or MXNet=1.6-1.8, with Python 3.x.
InsightFace efficiently implements a rich variety of state of the art algorithms of face recognition, face detection and face alignment, which optimized for both training and deployment.
ArcFace Video Demo
Please click the image to watch the Youtube video. For Bilibili users, click here.
The page on InsightFace website also describes all supported projects in InsightFace.
You may also interested in some challenges hold by InsightFace.
Introduction
In this module, we provide training data, network settings and loss designs for deep face recognition. The supported methods are as follows: •ArcFace_mxnet (CVPR'2019) •ArcFace_torch (CVPR'2019) •SubCenter ArcFace (ECCV'2020) •PartialFC_mxnet (CVPR'2022) •PartialFC_torch (CVPR'2022) •VPL (CVPR'2021) •Arcface_oneflow •ArcFace_Paddle (CVPR'2019) Commonly used network backbones are included in most of the methods, such as IResNet, MobilefaceNet, MobileNet, InceptionResNet_v2, DenseNet, etc..
Datasets
The training data includes, but not limited to the cleaned MS1M, VGG2 and CASIA-Webface datasets, which were already packed in MXNet binary format. Please dataset page for detail.
Evaluation
We provide standard IJB and Megaface evaluation pipelines in evaluation
Introduction
In this module, we provide training data with annotation, network settings and loss designs for face detection training, evaluation and inference. The supported methods are as follows: •RetinaFace (CVPR'2020) •SCRFD (Arxiv'2021) •blazeface_paddle RetinaFace is a practical single-stage face detector which is accepted by CVPR 2020. We provide training code, training dataset, pretrained models and evaluation scripts. SCRFD is an efficient high accuracy face detection approach which is initialy described in Arxiv. We provide an easy-to-use pipeline to train high efficiency face detectors with NAS supporting.
Introduction
In this module, we provide datasets and training/inference pipelines for face alignment. Supported methods: •SDUNets (BMVC'2018) •SimpleRegression SDUNets is a heatmap based method which accepted on BMVC. SimpleRegression provides very lightweight facial landmark models with fast coordinate regression. The input of these models is loose cropped face image while the output is the direct landmark coordinates.
If you find InsightFace useful in your research, please consider to cite the following related papers:
InsightFace is an open source toolbox for face recognition, detection and alignment, based on PyTorch and MXNet. It also provides a Discord bot for facial identity swapping and other web demos.
Sep 9, 2023 · Step-by-step guide: Refer to this link to register Discord app, create a new chat room, and invite the Midjourney bot to the chat room. Invite the InsightFaceSwap bot to the chat room by this link: https://discord.com/api/oauth2/authorize?client_id=1090660574196674713&permissions=274877945856&scope=bot. 3.
Learn the commands for InsightFace's FACE SWAP plugin for Discord (Use your own face in Photos, Ai Art or Midjourney). You have a tonne of options and I go ...
- 7 min
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- Wade McMaster - Creator Impact
Feb 13, 2023 · InsightFace is an open source toolbox for face recognition, detection and alignment, based on PyTorch and MXNet. It supports various state of the art methods, datasets, evaluation pipelines and pretrained models.
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May 22, 2023 · In this tech video I will show you how to easily swap faces in images using the Discord bot called InsightFace. This powerful tool allows you to replace faces in images with your own face or...
- 2 min
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- Zabist
