GBIM(Gesture-Based Interaction map)

Overview

GBIM

Python 3.6 PaddleX License

手势交互地图 GBIM(Gesture-Based Interaction map),基于视觉深度神经网络的交互地图,通过电脑摄像头观察使用者的手势变化,进而控制地图进行简单的交互。网络使用PaddleX提供的轻量级模型PPYOLO Tiny以及MobileNet V3 small,使得整个模型大小约10MB左右,即使在CPU下也能快速定位和识别手势。

手势

手势 交互 手势 交互 手势 交互
向上滑动 向左滑动 地图放大
手势 交互 手势 交互 手势 交互
向下滑动 向右滑动 地图缩小

进度安排

基础

  • 确认用于交互的手势。
  • 使用det_acq.py采集一些电脑摄像头拍摄的人手姿势数据。
  • 数据标注,训练手的目标检测模型
  • 捕获目标手,使用clas_acq.py获取手部图像进行标注,并用于训练手势分类模型。
  • 交互手势的检测与识别组合验证。
  • 打开百度地图网页版,进行模拟按键交互。
  • 组合功能,验证基本功能。

进阶

  • 将图像分类改为序列图像分类,提高手势识别的流畅度和准确度。
  • 重新采集和标注数据,调参训练模型。
  • 搭建可用于参数调节的地图。
  • 界面整合,整理及美化。

数据集 & 模型

手势检测

  • 数据集使用来自联想小新笔记本摄像头采集的数据,使用labelImg标注为VOC格式,共1011张。该数据集场景、环境和人物单一,仅作为测试使用,不提供数据集下载。数据组织参考PaddelX下的PascalVOC数据组织方式。
  • 模型使用超轻量级PPYOLO Tiny,模型大小小于4MB,随便训练了100轮后保留best_model作为测试模型,由于数据集和未调参训练的原因,当前默认识别效果较差

手势分类

  • 数据集使用来自联想小新笔记本摄像头采集的数据,通过手势检测模型提出出手图像,人工分为7类,分别为6种交互手势以及“其他”,共1102张。该数据集数量较少,手型及手势单一,仅作为测试使用,不提供数据集下载。数据组织形式如下:
dataset
	├-- Images
	|     ├-- up
	┆     ┆    └-- xxx.jpg
	|     └-- other
	┆          └-- xxx.jpg
	├-- labels.txt
	├-- train_list.txt
	└-- val_list.txt
  • 模型使用超轻量级MobileNet V3 small,模型大小小于7MB,由于数据量很小,随便训练了20轮后保留best_model作为测试模型,当前识别分类效果较差

模型文件上传使用LFS,下拉时注意需要安装LFS,参考LFS文档。后续将重新采集和标注更加多样的大量数据集,并采用更好的调参方法获得更加准确的识别模型

演示

手势识别

地图交互

*未显示Capture界面

使用

  1. 克隆当前项目到本地,按照requirements.txt安装所依赖的包opencv、paddlex以及pynput。PaddleX对应请安装最新版的PaddlePaddle,由于模型轻量,CPU版本足矣,参考下面代码,细节参考官方网站
python -m pip install paddlepaddle -i https://mirror.baidu.com/pypi/simple
  1. 进入demo.py,将浏览器路径修改为自己使用的浏览器路径:
web_path = '"D:/Twinkstar/Twinkstar Browser/twinkstar.exe"'  # 自己的浏览器路径
  1. 运行demo.py启动程序:
cd GBIM
python demo.py

常见问题及解决

  1. Q: 拉项目时卡住不动

    A:首先确认按照文档安装LFS。如果已经安装那极大可能是网络问题,可以等待一段时间,或先跳过LFS文件,再单独拉取,参考下面git代码:

    // 开启跳过无法clone的LFS文件
    git lfs install --skip-smudge 
    // clone当前项目
    git clone "current project" 
    // 进入当前项目,单独拉取LFS文件
    cd "current project" 
    git lfs pull 
    // 恢复LFS设置
    git lfs install --force
  2. Q:按q或者手势交互无效

    A:请注意当前鼠标点击的焦点,焦点在Capture,则接受q退出;焦点在浏览器,则交互结果将驱动浏览器中的地图进行变换。

  3. Q:安装PaddleX时报错,关于MV C++

    A:若在Windows下安装coco tool时报错,则可能缺少Microsoft Visual C++,可在微软官方下载网页进行下载安装后重启,即可解决。

  4. Q:运行未报错,但没有保存数据到本地

    A:请检查路径是否有中文,cv2.imwrite保存图像时不能有中文路径。

参考

  1. 玩腻了小游戏?Paddle手势识别玩转游戏玩出新花样!
  2. https://github.com/PaddlePaddle/PaddleX

交流与反馈

Email:[email protected]

Hide screen when boss is approaching.

BossSensor Hide your screen when your boss is approaching. Demo The boss stands up. He is approaching. When he is approaching, the program fetches fac

Hiroki Nakayama 6.2k Jan 07, 2023
This is the official implementation of "One Question Answering Model for Many Languages with Cross-lingual Dense Passage Retrieval".

CORA This is the official implementation of the following paper: Akari Asai, Xinyan Yu, Jungo Kasai and Hannaneh Hajishirzi. One Question Answering Mo

Akari Asai 59 Dec 28, 2022
Invert and perturb GAN images for test-time ensembling

GAN Ensembling Project Page | Paper | Bibtex Ensembling with Deep Generative Views. Lucy Chai, Jun-Yan Zhu, Eli Shechtman, Phillip Isola, Richard Zhan

Lucy Chai 93 Dec 08, 2022
This project provides the code and datasets for 'CapSal: Leveraging Captioning to Boost Semantics for Salient Object Detection', CVPR 2019.

Code-and-Dataset-for-CapSal This project provides the code and datasets for 'CapSal: Leveraging Captioning to Boost Semantics for Salient Object Detec

lu zhang 48 Aug 19, 2022
DeepFaceEditing: Deep Face Generation and Editing with Disentangled Geometry and Appearance Control

DeepFaceEditing: Deep Face Generation and Editing with Disentangled Geometry and Appearance Control One version of our system is implemented using the

260 Nov 28, 2022
Demystifying How Self-Supervised Features Improve Training from Noisy Labels

Demystifying How Self-Supervised Features Improve Training from Noisy Labels This code is a PyTorch implementation of the paper "[Demystifying How Sel

<a href=[email protected]"> 4 Oct 14, 2022
Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression

Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression YOLOv5 with alpha-IoU losses implemented in PyTorch. Example r

Jacobi(Jiabo He) 147 Dec 05, 2022
An self sufficient AI that crawls the web to learn how to generate art from keywords

Roxx-IO - The Smart Artist AI! TO DO / IDEAS Implement Web-Scraping Functionality Figure out a less annoying (and an off button for it) text to speech

Tatz 5 Mar 21, 2022
Introducing neural networks to predict stock prices

IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o

Vivek Palaniappan 637 Jan 04, 2023
3rd Place Solution of the Traffic4Cast Core Challenge @ NeurIPS 2021

3rd Place Solution of Traffic4Cast 2021 Core Challenge This is the code for our solution to the NeurIPS 2021 Traffic4Cast Core Challenge. Paper Our so

7 Jul 25, 2022
Multi-Task Learning as a Bargaining Game

Nash-MTL Official implementation of "Multi-Task Learning as a Bargaining Game". Setup environment conda create -n nashmtl python=3.9.7 conda activate

Aviv Navon 87 Dec 26, 2022
Code release for "Transferable Semantic Augmentation for Domain Adaptation" (CVPR 2021)

Transferable Semantic Augmentation for Domain Adaptation Code release for "Transferable Semantic Augmentation for Domain Adaptation" (CVPR 2021) Paper

66 Dec 16, 2022
Key information extraction from invoice document with Graph Convolution Network

Key Information Extraction from Scanned Invoices Key information extraction from invoice document with Graph Convolution Network Related blog post fro

Phan Hoang 39 Dec 16, 2022
Implementation of "Scaled-YOLOv4: Scaling Cross Stage Partial Network" using PyTorch framwork.

YOLOv4-large This is the implementation of "Scaled-YOLOv4: Scaling Cross Stage Partial Network" using PyTorch framwork. YOLOv4-CSP YOLOv4-tiny YOLOv4-

Kin-Yiu, Wong 2k Jan 02, 2023
Implementation of ReSeg using PyTorch

Implementation of ReSeg using PyTorch ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation Pascal-Part Annotations Pascal VOC 2010

Onur Kaplan 46 Nov 23, 2022
A medical imaging framework for Pytorch

Welcome to MedicalTorch MedicalTorch is an open-source framework for PyTorch, implementing an extensive set of loaders, pre-processors and datasets fo

Christian S. Perone 799 Jan 03, 2023
Confidence Propagation Cluster aims to replace NMS-based methods as a better box fusion framework in 2D/3D Object detection

CP-Cluster Confidence Propagation Cluster aims to replace NMS-based methods as a better box fusion framework in 2D/3D Object detection, Instance Segme

Yichun Shen 41 Dec 08, 2022
Jupyter Dock is a set of Jupyter Notebooks for performing molecular docking protocols interactively, as well as visualizing, converting file formats and analyzing the results.

Molecular Docking integrated in Jupyter Notebooks Description | Citation | Installation | Examples | Limitations | License Table of content Descriptio

Angel J. Ruiz Moreno 173 Dec 25, 2022
Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch

Segformer - Pytorch Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch. Install $ pip install segformer-pytorch

Phil Wang 208 Dec 25, 2022
[ICML 2021] A fast algorithm for fitting robust decision trees.

GROOT: Growing Robust Trees Growing Robust Trees (GROOT) is an algorithm that fits binary classification decision trees such that they are robust agai

Cyber Analytics Lab 17 Nov 21, 2022