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https://github.com/5sControl/machine-control
Automatically detect when a worker is absent using power of computer vision
https://github.com/5sControl/machine-control
algorithm machine-learning manufacturing python
Last synced: about 19 hours ago
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Automatically detect when a worker is absent using power of computer vision
- Host: GitHub
- URL: https://github.com/5sControl/machine-control
- Owner: 5sControl
- License: agpl-3.0
- Created: 2023-06-13T06:47:55.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-04-04T08:09:49.000Z (7 months ago)
- Last Synced: 2024-08-01T21:46:18.618Z (3 months ago)
- Topics: algorithm, machine-learning, manufacturing, python
- Language: Python
- Homepage: https://5controls.com
- Size: 138 KB
- Stars: 0
- Watchers: 4
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
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- awesome-openvino - Machine control - industrial machine surveillance system designed to help increase efficiency of processes. (Table of content / AI Computer Vision)
README
# About Machine control
Machine control is one of the Official [5sControl](https://5sControl.com/) algorithm. Plug it in our video monitoring system with AI analysis and ERP Integration (Open Source) to increase the efficiency of your processes.
Designed to handle complex industrial processes with ease, this innovative tool is perfect for use with semi-automated equipment. With Machine Control you can optimize your industrial processes and keep your equipment running smoothly, saving you time and money.
## Key features
- monitors use of equipment;
- prevents downtime of valuable and expensive equipment.
**Plug-in Machine control to 5controlS platform to detect when your workers are absent!**
> Learn more about Machine control on the [5sControl website](https://5scontrol.com/solutions/machine-control).
# Getting started
### Build image for machine_control_python algorithm
- For x86 users
```docker build -t 5scontrol/machine_control_python:latest .```
- for AArch64 users
```docker buildx build --platform linux/amd64 -t 5scontrol/machine_control_python:latest .```
### Build image for machine_control_python_server_model algorithm
- For x86 users
```docker build -t 5scontrol/machine_control_python_model_server:latest .```
- For AArch64 users
```docker buildx build --platform linux/amd64 -t 5scontrol/machine_control_python_model_server:latest .```
### Run containers
*Check id of container:* ```docker image list```
- For machine_control_python
```docker run -e username=admin -e password=just4Taqtile -e camera_url="http://192.168.1.163/onvif-http/snapshot?Profile_1" -e server_url=http://192.168.1.110 -e folder=images/192.168.1.163 -it ```
- For machine_control_python_server_model
```docker run -it ```
### Run/Test code
- For machine_control_python
```python main.py```
- For machine_control_python_server_model
```python -m flask run --host 0.0.0.0 --port 5002```
### Push images
- For machine_control_python:
```docker image push 5scontrol/machine_control_python:latest```
- For machine_control_python_server_model:
```docker image push 5scontrol/machine_control_python_model_server:latest```
[optional]: -e extra=[...]
---
**Request**: https://github.com/5sControl/QA_documentation/blob/main/algorithms/run_machine-control.json
**Responce**: https://github.com/5sControl/QA_documentation/blob/main/algorithms/report-with-photos_machine-control.json
- You have to download models:
**Models**: https://drive.google.com/file/d/1oHgIA6D8vgOfWl5AjyclPMvl21Vj_O_G/view?usp=sharing
you have to download models
# **Documentation**
[Documentation for Developers](https://github.com/5sControl/5s-dev-documentation/wiki)
[User Documentation](https://github.com/5sControl/Manufacturing-Automatization-Enterprise/wiki)
# **Contributing**
Thank you for considering contributing to 5sControl. We truly believe that we can build an outstanding product together!
We welcome a variety of ways to contribute. Read below to learn how you can take part in improving 5sControl.
## **Code of conduct**
Please note that this project is released with a [Contributor Code of Conduct](CODE_OF_CONDUCT.md). By participating in this project you agree to abide by its terms.
## Code contributing
If you want to contribute, read our [contributing guide](CONTRIBUTING.md) to learn about our development process and pull requests workflow.
We also have a list of [good first issues](https://github.com/5sControl/machine-control/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22) that will help you make your first step to beсoming a 5S contributor.
# **Project repositories**
**5controlS Platform:**
1. [5s-webserver](https://github.com/5sControl/5s-webserver)
2. [5s-backend](https://github.com/5sControl/5s-backend)
3. [5s-frontend](https://github.com/5sControl/5s-frontend)
4. [5s-algorithms-controller](https://github.com/5sControl/5s-algorithms-controller)
5. [5s-onvif](https://github.com/5sControl/5s-onvif)
6. [5s-onvif-finder](https://github.com/5sControl/5s-onvif-finder)
**Official Algorithms:**
1. [min-max](https://github.com/5sControl/min-max)
2. [idle-control](https://github.com/5sControl/idle-control)
3. [operation-control-js](https://github.com/5sControl/operation-control-js)
4. [machine-control](https://github.com/5sControl/machine-control)
5. [machine-control-js](https://github.com/5sControl/machine-control-js)
**Algorithms Servers:**
1. [inference-server-js](https://github.com/5sControl/inference-server-js)
# **License**
[AGPL-3.0](LICENSE)
> Machine control uses third party libraries that are distributed under their own terms (see [LICENSE-3RD-PARTY.md](https://github.com/5sControl/machine-control/blob/main/LICENSE-3RD-PARTY.md)).
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