A Home Assistant custom component for Lobe. Lobe is an AI tool that can classify images.

Overview

Lobe

Lobe Logo
This is a Home Assistant custom component for Lobe. Lobe is an AI tool that can classify images. This component lets you easily use an exported model along with another server to classify a camera entity's feed with it.

Installation

Use HACS for the integration. You'll also need a seperate server. Steps to install on another server:

  • Install the Lobe library.
  • Install Flask.
  • Export a Tensorflow Lite model into a folder on the server.
  • Copy over app.py and change the folder location.
  • Run app.py.
  • You'll probably want to make it run on start.

Configuration

This is the configuration format:

image_processing:
  - platform: lobe
    entity_id: camera.front_door_livestream # Camera entity ID
    name: "Front Door Status" # Optional; Custom name
    server: "http://lobeserver.local:5623" # Server address
    scan_interval: 2 # Optional; How often to update

It will produce an entity something like this: image

You might also like...
A voice recognition assistant similar to amazon alexa, siri and google assistant.
A voice recognition assistant similar to amazon alexa, siri and google assistant.

kenyan-Siri Build an Artificial Assistant Full tutorial (video) To watch the tutorial, click on the image below Installation For windows users (run th

Voice assistant - Voice assistant with python

🌐 Python Voice Assistant 🌵 - User's greeting 🌵 - Writing tasks to todo-list ?

September-Assistant - Open-source Windows Voice Assistant
September-Assistant - Open-source Windows Voice Assistant

September - Windows Assistant September is an open-source Windows personal assis

Example-custom-ml-block-keras - Custom Keras ML block example for Edge Impulse

Custom Keras ML block example for Edge Impulse This repository is an example on

Classify bird species based on their songs using SIamese Networks and 1D dilated convolutions.
Classify bird species based on their songs using SIamese Networks and 1D dilated convolutions.

The goal is to classify different birds species based on their songs/calls. Spectrograms have been extracted from the audio samples and used as features for classification.

ML model to classify between cats and dogs

Cats-and-dogs-classifier This is my first ML model which can classify between cats and dogs. Here the accuracy is around 75%, however , the accuracy c

Learning Open-World Object Proposals without Learning to Classify
Learning Open-World Object Proposals without Learning to Classify

Learning Open-World Object Proposals without Learning to Classify Pytorch implementation for "Learning Open-World Object Proposals without Learning to

a dnn ai project to classify which food people are eating on audio recordings

Deep Learning - EAT Challenge About This project is part of an AI challenge of the DeepLearning course 2021 at the University of Augsburg. The objecti

Classify the disease status of a plant given an image of a passion fruit
Classify the disease status of a plant given an image of a passion fruit

Passion Fruit Disease Detection I tried to create an accurate machine learning models capable of localizing and identifying multiple Passion Fruits in

Releases(v0.1.0)
  • v0.1.0(May 1, 2021)

    First release of the Lobe component. Things I want to add in the future:

    • "Error" class handling that doesn't update the tag if the most likely prediction is "Error". You could use this feature if sometimes the camera malfunctions by creating an "Error" class.
    • A feature that requires a class to be predicted multiple times in order to be set, to account for the model sometimes being incorrect.
    • Post on reddit / HA forums
    Source code(tar.gz)
    Source code(zip)
Owner
Kendell R
Here to make stuff, do stuff, help out with stuff.
Kendell R
Reinforcement Learning for Portfolio Management

qtrader Reinforcement Learning for Portfolio Management Why Reinforcement Learning? Learns the optimal action, rather than models the market. Adaptive

Angelos Filos 406 Jan 01, 2023
Official Matlab Implementation for "Tiny Obstacle Discovery by Occlusion-aware Multilayer Regression", TIP 2020

Tiny Obstacle Discovery by Occlusion-aware Multilayer Regression Official Matlab Implementation for "Tiny Obstacle Discovery by Occlusion-aware Multil

Xuefeng 5 Jan 15, 2022
Quick program made to generate alpha and delta tables for Hidden Markov Models

HMM_Calc Functions for generating Alpha and Delta tables from a Hidden Markov Model. Parameters: a: Matrix of transition probabilities. a[i][j] = a_{i

Adem Odza 1 Dec 04, 2021
Repo for the paper Extrapolating from a Single Image to a Thousand Classes using Distillation

Extrapolating from a Single Image to a Thousand Classes using Distillation by Yuki M. Asano* and Aaqib Saeed* (*Equal Contribution) Extrapolating from

Yuki M. Asano 16 Nov 04, 2022
Secure Distributed Training at Scale

Secure Distributed Training at Scale This repository contains the implementation of experiments from the paper "Secure Distributed Training at Scale"

Yandex Research 9 Jul 11, 2022
Office source code of paper UniFuse: Unidirectional Fusion for 360$^\circ$ Panorama Depth Estimation

UniFuse (RAL+ICRA2021) Office source code of paper UniFuse: Unidirectional Fusion for 360$^\circ$ Panorama Depth Estimation, arXiv, Demo Preparation I

Alibaba 47 Dec 26, 2022
DABO: Data Augmentation with Bilevel Optimization

DABO: Data Augmentation with Bilevel Optimization [Paper] The goal is to automatically learn an efficient data augmentation regime for image classific

ElementAI 24 Aug 12, 2022
BARF: Bundle-Adjusting Neural Radiance Fields 🤮 (ICCV 2021 oral)

BARF 🤮 : Bundle-Adjusting Neural Radiance Fields Chen-Hsuan Lin, Wei-Chiu Ma, Antonio Torralba, and Simon Lucey IEEE International Conference on Comp

Chen-Hsuan Lin 539 Dec 28, 2022
Trainable PyTorch reproduction of AlphaFold 2

OpenFold A faithful PyTorch reproduction of DeepMind's AlphaFold 2. Features OpenFold carefully reproduces (almost) all of the features of the origina

AQ Laboratory 1.7k Dec 29, 2022
GAN-based 3D human pose estimation model for 3DV'17 paper

Tensorflow implementation for 3DV 2017 conference paper "Adversarially Parameterized Optimization for 3D Human Pose Estimation". @inproceedings{jack20

Dominic Jack 15 Feb 27, 2021
Unsupervised 3D Human Mesh Recovery from Noisy Point Clouds

Unsupervised 3D Human Mesh Recovery from Noisy Point Clouds Xinxin Zuo, Sen Wang, Minglun Gong, Li Cheng Prerequisites We have tested the code on Ubun

41 Dec 12, 2022
PyTorch implementation of ICLR 2022 paper PiCO: Contrastive Label Disambiguation for Partial Label Learning

PiCO: Contrastive Label Disambiguation for Partial Label Learning This is a PyTorch implementation of ICLR 2022 paper PiCO: Contrastive Label Disambig

王皓波 147 Jan 07, 2023
The implementation of 'Image synthesis via semantic composition'.

Image synthesis via semantic synthesis [Project Page] by Yi Wang, Lu Qi, Ying-Cong Chen, Xiangyu Zhang, Jiaya Jia. Introduction This repository gives

DV Lab 71 Jan 06, 2023
NeRViS: Neural Re-rendering for Full-frame Video Stabilization

Neural Re-rendering for Full-frame Video Stabilization

Yu-Lun Liu 9 Jun 17, 2022
The toolkit to generate auto labeled datasets

Ozeu Ozeu is the toolkit to autolabal dataset for instance segmentation. You can generate datasets labaled with segmentation mask and bounding box fro

Xiong Jie 28 Mar 28, 2022
Using contrastive learning and OpenAI's CLIP to find good embeddings for images with lossy transformations

Creating Robust Representations from Pre-Trained Image Encoders using Contrastive Learning Sriram Ravula, Georgios Smyrnis This is the code for our pr

Sriram Ravula 26 Dec 10, 2022
2021-AIAC-QQ-Browser-Hyperparameter-Optimization-Rank6

2021-AIAC-QQ-Browser-Hyperparameter-Optimization-Rank6

Aigege 8 Mar 31, 2022
The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".

Block Modeling-Guided Graph Convolutional Neural Networks This repository contains the demo code of the paper: Block Modeling-Guided Graph Convolution

22 Dec 08, 2022
Implementation of CSRL from the AAAI2022 paper: Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning

CSRL Implementation of CSRL from the AAAI2022 paper: Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning Python: 3

4 Apr 14, 2022
Pytorch Implementation of Spiking Neural Networks Calibration, ICML 2021

SNN_Calibration Pytorch Implementation of Spiking Neural Networks Calibration, ICML 2021 Feature Comparison of SNN calibration: Features SNN Direct Tr

Yuhang Li 60 Dec 27, 2022