✂️ EyeLipCropper is a Python tool to crop eyes and mouth ROIs of the given video.

Overview

EyeLipCropper

EyeLipCropper is a Python tool to crop eyes and mouth ROIs of the given video. The whole process consists of three parts: frame extraction, face alignment, and eye/mouth cropping. The cropped eye/mouth image size can be customized.

vis

Usage

Prerequisites

>>> pip install -r requirements.txt

1. Extract frames of a given video

>>> python frame_extract.py -h
usage: frame_extract.py [-h] [--video-path VIDEO_PATH] [--images-path IMAGES_PATH]

extract frames with opencv

optional arguments:
  -h, --help            show this help message and exit
  --video-path VIDEO_PATH
                        the input video path
  --images-path IMAGES_PATH
                        the output frames path
 
# default for test: this will generate frames of the video in `./test/images`
>>> python frame_extract.py

2. Align faces of the frames, with library face-alignment

>>> python face_align.py -h
usage: face_align.py [-h] [--images-path IMAGES_PATH] [--landmarks-path LANDMARKS_PATH] [--boxes-path BOXES_PATH] [--device DEVICE] [--log-path LOG_PATH]

align faces with `https://github.com/1adrianb/face-alignment`

optional arguments:
  -h, --help            show this help message and exit
  --images-path IMAGES_PATH
                        the input frames path
  --landmarks-path LANDMARKS_PATH
                        the output 68 landmarks path
  --boxes-path BOXES_PATH
                        the output bounding boxes path
  --device DEVICE       cpu or gpu cuda device
  --log-path LOG_PATH   logging when there are no faces detected
  
# default for test: this will generate landmarks and bounding boxes in
# `./test/landmarks` and `./test/boxes`
>>> python face_align.py

3. Crop left eye, right eye, mouth ROIs, with code modified from processing tools of [Eye] RT-GENE and [Mouth] LipForensics

>>> python eye_mouth_crop.py -h
usage: eye_mouth_crop.py [-h] [--images-path IMAGES_PATH] [--landmarks-path LANDMARKS_PATH] [--boxes-path BOXES_PATH] [--eye-width EYE_WIDTH] [--eye-height EYE_HEIGHT]
                         [--face-roi-width FACE_ROI_WIDTH] [--face-roi-height FACE_ROI_HEIGHT] [--left-eye-path LEFT_EYE_PATH] [--right-eye-path RIGHT_EYE_PATH]
                         [--mean-face MEAN_FACE] [--mouth-width MOUTH_WIDTH] [--mouth-height MOUTH_HEIGHT] [--start-idx START_IDX] [--stop-idx STOP_IDX]
                         [--window-margin WINDOW_MARGIN] [--mouth-path MOUTH_PATH]

crop eye and mouth regions

optional arguments:
  -h, --help            show this help message and exit
  --images-path IMAGES_PATH
                        [COMMON] the input frames path
  --landmarks-path LANDMARKS_PATH
                        [COMMON] the input 68 landmarks path
  --boxes-path BOXES_PATH
                        [EYE] the input bounding boxes path
  --eye-width EYE_WIDTH
                        [EYE] width of cropped eye ROIs
  --eye-height EYE_HEIGHT
                        [EYE] height of cropped eye ROIs
  --face-roi-width FACE_ROI_WIDTH
                        [EYE] maximize this argument until there is a warning message
  --face-roi-height FACE_ROI_HEIGHT
                        [EYE] maximize this argument until there is a warning message
  --left-eye-path LEFT_EYE_PATH
                        [EYE] the output left eye images path
  --right-eye-path RIGHT_EYE_PATH
                        [EYE] the output right eye images path
  --mean-face MEAN_FACE
                        [MOUTH] mean face pathname
  --mouth-width MOUTH_WIDTH
                        [MOUTH] width of cropped mouth ROIs
  --mouth-height MOUTH_HEIGHT
                        [MOUTH] height of cropped mouth ROIs
  --start-idx START_IDX
                        [MOUTH] start of landmark index for mouth
  --stop-idx STOP_IDX   [MOUTH] end of landmark index for mouth
  --window-margin WINDOW_MARGIN
                        [MOUTH] window margin for smoothed_landmarks
  --mouth-path MOUTH_PATH
                        [MOUTH] the output mouth images path

# default for test: this will generate the final cropped left eye,
# right eye, and mouth images in `./test/left_eye`, `./test/right_eye`
# , and `./test/mouth`
>>> python eye_mouth_crop.py
  • Note that the argument --face-roi-width and --face-roi-height should be maximized until there is a printed warning.

License

GPL-3.0 License

Reference

[1] Bulat, Adrian, and Georgios Tzimiropoulos. "How far are we from solving the 2d & 3d face alignment problem?(and a dataset of 230,000 3d facial landmarks)." Proceedings of the IEEE International Conference on Computer Vision (ICCV). 2017. GitHub: https://github.com/1adrianb/face-alignment

[2] Fischer, Tobias, Hyung Jin Chang, and Yiannis Demiris. "Rt-gene: Real-time eye gaze estimation in natural environments." Proceedings of the European Conference on Computer Vision (ECCV). 2018. GitHub: https://github.com/Tobias-Fischer/rt_gene

[3] Haliassos, Alexandros, et al. "Lips Don't Lie: A Generalisable and Robust Approach To Face Forgery Detection." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 2021. GitHub: https://github.com/ahaliassos/LipForensics/

Owner
Zi-Han Liu
Senior @ SJTU
Zi-Han Liu
Udacity Suse Cloud Native Foundations Scholarship Course Walkthrough

SUSE Cloud Native Foundations Scholarship Udacity is collaborating with SUSE, a global leader in true open source solutions, to empower developers and

Shivansh Srivastava 34 Oct 18, 2022
Code for the AAAI 2022 paper "Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-Sentence Dependency Graph".

multilingual-mrc-isdg Code for the AAAI 2022 paper "Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-Sentence Dependency Graph". This r

Liyan 5 Dec 07, 2022
A python module for configuration of block devices

Blivet is a python module for system storage configuration. CI status Licence See COPYING Installation From Fedora repositories Blivet is available in

78 Dec 14, 2022
A certifiable defense against adversarial examples by training neural networks to be provably robust

DiffAI v3 DiffAI is a system for training neural networks to be provably robust and for proving that they are robust. The system was developed for the

SRI Lab, ETH Zurich 202 Dec 13, 2022
[ICCV 2021 Oral] SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer

This repository contains the source code for the paper SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer (ICCV 2021 Oral). The project page is here.

AllenXiang 65 Dec 26, 2022
Official implementation of "UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspective with Transformer"

[AAAI2022] UCTransNet This repo is the official implementation of "UCTransNet: Rethinking the Skip Connections in U-Net from a Channel-wise Perspectiv

Haonan Wang 199 Jan 03, 2023
Code for the paper Task Agnostic Morphology Evolution.

Task-Agnostic Morphology Optimization This repository contains code for the paper Task-Agnostic Morphology Evolution by Donald (Joey) Hejna, Pieter Ab

Joey Hejna 18 Aug 04, 2022
PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".

Sharpness-aware Quantization for Deep Neural Networks This is the official repository for our paper: Sharpness-aware Quantization for Deep Neural Netw

Zhuang AI Group 30 Dec 19, 2022
Efficient 6-DoF Grasp Generation in Cluttered Scenes

Contact-GraspNet Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenes Martin Sundermeyer, Arsalan Mousavian, Rudolph Triebel, Dieter

NVIDIA Research Projects 148 Dec 28, 2022
True per-item rarity for Loot

True-Rarity True per-item rarity for Loot (For Adventurers) and More Loot A.K.A mLoot each out/true_rarity_{item_type}.json file contains probabilitie

Dan R. 3 Jul 26, 2022
🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.

English | 简体中文 | 繁體中文 State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained mo

Hugging Face 77.2k Jan 02, 2023
Official Keras Implementation for UNet++ in IEEE Transactions on Medical Imaging and DLMIA 2018

UNet++: A Nested U-Net Architecture for Medical Image Segmentation UNet++ is a new general purpose image segmentation architecture for more accurate i

Zongwei Zhou 1.8k Dec 27, 2022
Code & Data for Enhancing Photorealism Enhancement

Enhancing Photorealism Enhancement Stephan R. Richter, Hassan Abu AlHaija, Vladlen Koltun Paper | Website (with side-by-side comparisons) | Video (Pap

Intelligent Systems Lab Org 1.1k Dec 31, 2022
Style-based Point Generator with Adversarial Rendering for Point Cloud Completion (CVPR 2021)

Style-based Point Generator with Adversarial Rendering for Point Cloud Completion (CVPR 2021) An efficient PyTorch library for Point Cloud Completion.

Microsoft 119 Jan 02, 2023
Automatically download the cwru data set, and then divide it into training data set and test data set

Automatically download the cwru data set, and then divide it into training data set and test data set.自动下载cwru数据集,然后分训练数据集和测试数据集

6 Jun 27, 2022
IA for recognising Traffic Signs using Keras [Tensorflow]

Traffic Signs Recognition ⚠️ 🚦 Fundamentals of Intelligent Systems Introduction 📄 Development of a neural network capable of recognizing nine differ

Sebastián Fernández García 2 Dec 19, 2022
Train CNNs for the fruits360 data set in NTOU CS「Machine Vision」class.

CNNs fruits360 Train CNNs for the fruits360 data set in NTOU CS「Machine Vision」class. CNN on a pretrained model Build a CNN on a pretrained model, Res

Ricky Chuang 1 Mar 07, 2022
Code for the Convolutional Vision Transformer (ConViT)

ConViT : Vision Transformers with Convolutional Inductive Biases This repository contains PyTorch code for ConViT. It builds on code from the Data-Eff

Facebook Research 418 Jan 06, 2023
Official source code of paper 'IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo'

IterMVS official source code of paper 'IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo' Introduction IterMVS is a novel lear

Fangjinhua Wang 127 Jan 04, 2023
Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation

deeptime Releases: Installation via conda recommended. conda install -c conda-forge deeptime pip install deeptime Documentation: deeptime-ml.github.io

495 Dec 28, 2022