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https://github.com/t0mer/deepstack-trainer

deepstack trainer is a Flask powerd, easy to use web app, hepls us to train and test Deepstack AI
https://github.com/t0mer/deepstack-trainer

deepstack docker face-detection face-recognition fastapi home-assistant home-automation machine-learning object-detection python

Last synced: about 1 month ago
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deepstack trainer is a Flask powerd, easy to use web app, hepls us to train and test Deepstack AI

Host: GitHub
URL: https://github.com/t0mer/deepstack-trainer
Owner: t0mer
License: gpl-3.0
Created: 2021-04-30T20:27:15.000Z (over 3 years ago)
Default Branch: main
Last Pushed: 2023-12-27T17:26:07.000Z (9 months ago)
Last Synced: 2024-04-16T13:17:33.300Z (5 months ago)
Topics: deepstack, docker, face-detection, face-recognition, fastapi, home-assistant, home-automation, machine-learning, object-detection, python
Language: Python
Homepage:
Size: 2.6 MB
Stars: 24
Watchers: 2
Forks: 3
Open Issues: 4
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

awesome-opensource-israel - Deepstack Trainer - Simple web application for training & Testing [Deepstack](https://deepstack.cc/). ![GitHub last commit](https://img.shields.io/github/last-commit/t0mer/deepstack-trainer?style=flat-square) ![GitHub top language](https://img.shields.io/github/languages/top/t0mer/deepstack-trainer?style=flat-square "GitHub top language") (Projects by main language / python)

README

*Please :star: this repo if you find it useful*

# DeepStack Trainer
[DeepStack](https://deepstack.cc/) is an AI server that empowers every developer in the world to easily build state-of-the-art AI systems both on premise and in the cloud. The promises of Artificial Intelligence are huge but becoming a machine learning engineer is hard. DeepStack is device and language agnostic. You can run it on Windows, Mac OS, Linux, Raspberry PI and use it with any programming language.

DeepStack’s source code is available on GitHub via [https://github.com/johnolafenwa/DeepStack](https://github.com/johnolafenwa/DeepStack/)

[DeepStack Trainer](https://github.com/t0mer/deepstack-trainer) is a [FastAPI](https://fastapi.tiangolo.co) powerd web application that helps us train and test Deepstack AI easelly as possible.

## Features
- Face Registring.
- Test face recognition.
- Test scene recognition.
- Test object detection.
- Gallery page, display all uploaded images (For traning only).

## Components used in Deepstack Trainer
- [FastAPI](https://fastapi.tiangolo.com/) - For running web server
- [materializecss](https://materializecss.com/) - For web forms
- [sweetalert2](https://sweetalert2.github.io/) - For alerts and messages

# Installation
#### Deepstack Installation
In order to use Deepstack Trainer we need to install Deepstack.
We can do that by running the following command:

```docker run -e VISION-FACE=True -v localstorage:/datastore -p 80:5000 deepquestai/deepstack```

Basic Parameters:
* -e VISION-FACE=True This enables the face recognition APIs.
* -v localstorage:/datastore This specifies the local volume where deepstack will store all data.
* -p 80:5000 This makes deepstack accessible via port 80 of the machine.

We can also install Deepstack using docker-compose:
```
version: "3.7"
services:
deepstack:
image: deepquestai/deepstack:latest
restart: unless-stopped
container_name: deepstack
ports:
- "80:5000"
environment:
- TZ=Asia/Jerusalem
- VISION-FACE=True
- VISION-DETECTION=True
- VISION-SCENE=True
volumes:
- ./deepstack:/datastore
```

#### Deepstack Trainer Installation
Deepstack Trainer installation is very easy using docker-compose:
```
version: "3.7"
services:
deepstack_trainer:
image: techblog/deepstack-trainer
container_name: deepstack_trainer
privileged: true
restart: always
environment:
- DEEPSTACK_HOST_ADDRESS=
- DEEPSTACK_API_KEY=
- MIN_CONFIDANCE=
ports:
- "8080:8080"
volumes:
- ./deepstack-trainer/db:/opt/trainer/db #Database storing the uploaded photos data (Filename, Person name, Date).
- ./deepstack-trainer/uploads:/opt/trainer/photos/uploads #Phisical path for storing the images

```

Basic Parameters:
* DEEPSTACK_HOST_ADDRESS - Deepstack API Url (http://localhost:5000)
* DEEPSTACK_API_KEY - If your Deepstack API is token protected enter your token here or alse leave blank
* MIN_CONFIDANCE - Minimum Confidence level to identify object or face (Default is 0.70)

## Working with Deepstack Trainer
After the docker is up and running, open your browser and navigate to your Deepstack Trainer url. you will be able to see four tabs:
* Face Learning (Registring).
[![Face Registring](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/teach%20face.png?raw=true "Face Registring")](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/teach%20face.png?raw=true "Face Registring")

* Face Recognition
[![Face Recognition](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/face%20recognition.png?raw=true "Face Recognition")](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/face%20recognition.png?raw=true "Face Recognition")

* Object Detection
[![Object Detection](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/object%20detection.png?raw=true "Object Detection")](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/object%20detection.png?raw=true "Object Detection")

* Scene Detection
[![Scene Detection](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/scene%20detection.png?raw=true "Scene Detection")](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/scene%20detection.png?raw=true "Scene Detection")

* Photo Gallery
[![Scene Detection](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/gallery.png?raw=true "Scene Detection")](https://github.com/t0mer/deepstack-trainer/blob/main/screenshots/gallery.png?raw=true "Scene Detection")

# Integrations and Community
The DeepStack ecosystem includes a number of popular integrations and libraries built to expand the functionalities of the AI engine to serve IoT, industrial, monitoring and research applications. A number of them are listed below

* [HASS-DeepStack-Object](https://github.com/robmarkcole/HASS-Deepstack-object)
* [HASS-DeepStack-Face](https://github.com/robmarkcole/HASS-Deepstack-face)
* [HASS-DeepStack-Scene](https://github.com/robmarkcole/HASS-Deepstack-scene)
* [DeepStack with Blue Iris - YouTube video](https://www.youtube.com/watch?v=fwoonl5JKgo)
* [DeepStack with Blue Iris - Forum Discussion](https://ipcamtalk.com/threads/tool-tutorial-free-ai-person-detection-for-blue-iris.37330/)
* [DeepStack on Home Assistant](https://community.home-assistant.io/t/face-and-person-detection-with-deepstack-local-and-free/92041)
* [DeepStack-UI](https://github.com/robmarkcole/deepstack-ui)
* [DeepStack-Python Helper](https://github.com/robmarkcole/deepstack-python)
* [DeepStack-Analytics](https://github.com/robmarkcole/deepstack-analytics)
* [DeepStackAI Trigger](https://github.com/danecreekphotography/node-deepstackai-trigger)