use machine learning to recognize gesture on raspberrypi

Last update: Dec 10, 2021

Overview

Raspberrypi_Gesture-Recognition

use machine learning to recognize gesture on raspberrypi

說明

利用 tensorflow lite 訓練手部辨識模型
分辨 "剪刀"、"石頭"、"布" 之手勢
再將訓練模型匯入 Raspberry pi
透過相機模組進行即時手勢判斷

測試結果

布 => 紅燈 (上面那顆)
剪刀 => 黃燈 (下面那顆)
石頭 => 綠燈 (中間那顆)

demo 影片 => https://www.youtube.com/watch?v=6-rEq0tAKrw

結果分析

在光源不足的地方辨識度會下降
背景複雜辨識度下降
石頭辨識度不高(需要特定角度)

Owner

GitHub Repository

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use machine learning to recognize gesture on raspberrypi

Related tags

Overview

Raspberrypi_Gesture-Recognition

說明

測試結果

結果分析

Owner

PyContinual (An Easy and Extendible Framework for Continual Learning)

A CNN model to detect hand gestures.

Official implementation of GraphMask as presented in our paper Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking.

LightningFSL: Pytorch-Lightning implementations of Few-Shot Learning models.

U-Net Implementation: Convolutional Networks for Biomedical Image Segmentation" using the Carvana Image Masking Dataset in PyTorch

The Deep Learning with Julia book, using Flux.jl.

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Omnidirectional Scene Text Detection with Sequential-free Box Discretization (IJCAI 2019). Including competition model, online demo, etc.

MG-GCN: Scalable Multi-GPU GCN Training Framework

DR-GAN: Automatic Radial Distortion Rectification Using Conditional GAN in Real-Time

A PyTorch based deep learning library for drug pair scoring.

Modeling Category-Selective Cortical Regions with Topographic Variational Autoencoders

SAS: Self-Augmentation Strategy for Language Model Pre-training

Face and other object detection using OpenCV and ML Yolo

NeuPy is a Tensorflow based python library for prototyping and building neural networks

Implementation of fast algorithms for Maximum Spanning Tree (MST) parsing that includes fast ArcMax+Reweighting+Tarjan algorithm for single-root dependency parsing.

Tensorflow-Project-Template - A best practice for tensorflow project template architecture.

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