The official repository for Deep Image Matting with Flexible Guidance Input

Overview

FGI-Matting

The official repository for Deep Image Matting with Flexible Guidance Input.

Paper: https://arxiv.org/abs/2110.10898

image

all

Requirements

  • easydict
  • numpy
  • opencv-python
  • Pillow
  • PyQt5
  • scikit-image
  • scipy
  • toml
  • torch>=1.5.0
  • torchvision

Models and supplementary data for DIM test set(Composition-1k) and Distinctions-646 test set

Google drive: https://drive.google.com/drive/folders/13qnlXUSKS5HfkfvzdMKAv7FvJ6YV_wPK?usp=sharing
百度网盘: https://pan.baidu.com/s/1ZYcbwyCIrL6G9t7pkCIBYw 提取码: zjtj

  • Weight_DIM.pth The model trained with Adobe matting dataset.

  • Weight_D646.pth The model trained with Distincions-646 dataset.

  • DIM_test_supp_data.zip Scribblemaps and Clickmaps for DIM test set.

  • D-646_test_supp_data.zip Scribblemaps and Clickmaps for Distinctions-646 test set.

Place Weight_DIM.pth and Weight_D646.pth in ./checkpoints.
Edit ./config/FGI_config to modify the path of the testset and choose the checkpoint name.

Test on DIM test set(Composition-1k)

Methods SAD MSE Grad Conn
Trimap test 30.19 0.0061 13.07 26.66
Scribblemap test 32.86 0.0090 14.18 29.09
Clickmap test 34.67 0.0112 15.45 30.96
No guidance test 36.36 0.0141 15.23 32.76

"checkpoint" in ./config/FGI_config.toml should be "Weight_DIM".
bash test.sh
Modify "guidancemap_phase" in ./config/FGI_config.toml to test on trimap, scribblemap, clickmap and No_guidance.
For further test, please use the code in ./DIM_evaluation_code and the predicted alpha mattes in ./alpha_pred.

Test on Distinctions-646 test set(Not appear in the paper)

Methods SAD MSE Grad Conn
Trimap test 28.90 0.0105 24.67 27.40
Scribblemap test 33.22 0.0131 26.93 31.38
Clickmap test 34.97 0.0146 27.60 33.11
No guidance test 36.83 0.0156 28.28 34.90

"checkpoint" in ./config/FGI_config.toml should be "Weight_D646".
bash test.sh
Modify "guidancemap_phase" in ./config/FGI_config.toml to test on trimap, scribblemap, clickmap and No_guidance.
For further test, please use the code in ./DIM_evaluation_code and the predicted alpha mattes in ./alpha_pred.

The QT Demo

Copy one of the pth file and rename it "Weight_qt_in_use.pth", also place it in ./checkpoints.
Run test_one_img_qt.py. Try images in ./testimg. It will use GPU if avaliable, otherwise it will use CPU.

demo

I recommend to use the one trained on DIM dataset.
Have fun :D

Acknowledgment

GCA-Matting: https://github.com/Yaoyi-Li/GCA-Matting

Owner
Hang Cheng
Hang Cheng
A library for uncertainty quantification based on PyTorch

Torchuq [logo here] TorchUQ is an extensive library for uncertainty quantification (UQ) based on pytorch. TorchUQ currently supports 10 representation

TorchUQ 96 Dec 12, 2022
Python package to add text to images, textures and different backgrounds

nider Python package for text images generation and watermarking Free software: MIT license Documentation: https://nider.readthedocs.io. nider is an a

Vladyslav Ovchynnykov 131 Dec 30, 2022
Experimental Python implementation of OpenVINO Inference Engine (very slow, limited functionality). All codes are written in Python. Easy to read and modify.

PyOpenVINO - An Experimental Python Implementation of OpenVINO Inference Engine (minimum-set) Description The PyOpenVINO is a spin-off product from my

Yasunori Shimura 7 Oct 31, 2022
Clustering with variational Bayes and population Monte Carlo

pypmc pypmc is a python package focusing on adaptive importance sampling. It can be used for integration and sampling from a user-defined target densi

45 Feb 06, 2022
The Power of Scale for Parameter-Efficient Prompt Tuning

The Power of Scale for Parameter-Efficient Prompt Tuning Implementation of soft embeddings from https://arxiv.org/abs/2104.08691v1 using Pytorch and H

Kip Parker 208 Dec 30, 2022
Source code and data in paper "MDFEND: Multi-domain Fake News Detection (CIKM'21)"

MDFEND: Multi-domain Fake News Detection This is an official implementation for MDFEND: Multi-domain Fake News Detection which has been accepted by CI

Rich 40 Dec 18, 2022
Open-source Monocular Python HawkEye for Tennis

Tennis Tracking 🎾 Objectives Track the ball Detect court lines Detect the players To track the ball we used TrackNet - deep learning network for trac

ArtLabs 188 Jan 08, 2023
Official repository of "Investigating Tradeoffs in Real-World Video Super-Resolution"

RealBasicVSR [Paper] This is the official repository of "Investigating Tradeoffs in Real-World Video Super-Resolution, arXiv". This repository contain

Kelvin C.K. Chan 566 Dec 28, 2022
https://sites.google.com/cornell.edu/recsys2021tutorial

Counterfactual Learning and Evaluation for Recommender Systems (RecSys'21 Tutorial) Materials for "Counterfactual Learning and Evaluation for Recommen

yuta-saito 45 Nov 10, 2022
To Design and Implement Logistic Regression to Classify Between Benign and Malignant Cancer Types

To Design and Implement Logistic Regression to Classify Between Benign and Malignant Cancer Types, from a Database Taken From Dr. Wolberg reports his Clinic Cases.

Astitva Veer Garg 1 Jul 31, 2022
Using VapourSynth with super resolution models and speeding them up with TensorRT.

VSGAN-tensorrt-docker Using image super resolution models with vapoursynth and speeding them up with TensorRT. Using NVIDIA/Torch-TensorRT combined wi

111 Jan 05, 2023
Official MegEngine implementation of CREStereo(CVPR 2022 Oral).

[CVPR 2022] Practical Stereo Matching via Cascaded Recurrent Network with Adaptive Correlation This repository contains MegEngine implementation of ou

MEGVII Research 309 Dec 30, 2022
[NeurIPS-2021] Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data

MosaicKD Code for NeurIPS-21 paper "Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data" 1. Motivation Natural images share common l

ZJU-VIPA 37 Nov 10, 2022
SCU OlympicsRunning Baseline

Competition 1v1 running Environment check details in Jidi Competition RLChina2021智能体竞赛 做出的修改: 奖励重塑:修改了环境,重新设置了奖励的分配,使得奖励组成不只有零和博弈,还有探索环境的奖励。 算法微调:修改了官

ZiSeoi Wong 2 Nov 23, 2021
计算机视觉中用到的注意力模块和其他即插即用模块PyTorch Implementation Collection of Attention Module and Plug&Play Module

PyTorch实现多种计算机视觉中网络设计中用到的Attention机制,还收集了一些即插即用模块。由于能力有限精力有限,可能很多模块并没有包括进来,有任何的建议或者改进,可以提交issue或者进行PR。

PJDong 599 Dec 23, 2022
Patch SVDD for Image anomaly detection

Patch SVDD Patch SVDD for Image anomaly detection. Paper: https://arxiv.org/abs/2006.16067 (published in ACCV 2020). Original Code : https://github.co

Hong-Jeongmin 0 Dec 03, 2021
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

CatBoost 6.9k Jan 04, 2023
The official implementation of Equalization Loss for Long-Tailed Object Recognition (CVPR 2020) based on Detectron2

Equalization Loss for Long-Tailed Object Recognition Jingru Tan, Changbao Wang, Buyu Li, Quanquan Li, Wanli Ouyang, Changqing Yin, Junjie Yan ⚠️ We re

Jingru Tan 197 Dec 25, 2022
UDP++ (ECCVW 2020 Oral), (Winner of COCO 2020 Keypoint Challenge).

UDP-Pose This is the pytorch implementation for UDP++, which won the Fisrt place in COCO Keypoint Challenge at ECCV 2020 Workshop. Top-Down Results on

20 Jul 29, 2022
PyTorch implementation of Lip to Speech Synthesis with Visual Context Attentional GAN (NeurIPS2021)

Lip to Speech Synthesis with Visual Context Attentional GAN This repository contains the PyTorch implementation of the following paper: Lip to Speech

6 Nov 02, 2022