https://github.com/nliaudat/meter-reader
meter (water, gas, electricity) reader from image to digits
https://github.com/nliaudat/meter-reader
electricity-meter gas-meter meter-reading tflite water-meter
Last synced: about 1 month ago
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meter (water, gas, electricity) reader from image to digits
- Host: GitHub
- URL: https://github.com/nliaudat/meter-reader
- Owner: nliaudat
- License: other
- Created: 2025-01-02T17:31:28.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-02-24T17:54:25.000Z (3 months ago)
- Last Synced: 2025-04-11T18:51:23.081Z (about 1 month ago)
- Topics: electricity-meter, gas-meter, meter-reading, tflite, water-meter
- Language: Python
- Homepage:
- Size: 894 KB
- Stars: 5
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
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README
# meter-reader
meter (water, gas, electricity) reader from image to digits
## Goals :
* Read meter (water, gas, electricity)
* Hardware independant (works with any camera that can produce a fixed image)
* Keep simple
## Process :
* Get image from any camera (local or http)
* Setup a python compatible apps to process the image (docker, flask or other python compatible apps)
* [onetime] set regions to process
* Produce digits from image
## Solutions 1 - python only : (tested on Python 3.12.3)
`pip install -r requirements.txt`
`python draw_regions.py`
*input image source and draw digits regions from left to right*
`python meter_reading.py`
`optional arguments : --image_source http://192.168.1.113/img_tmp/alg.jpg --model model.tflite --regions regions.txt --no-gui --no-output-image`
## Solutions 2 - webapp - flask_meter_reader :
`pip install -r requirements.txt`
`python app.py`
*- http://127.0.0.1:5000
- [onetime]Go to Draw Regions> input you image (http or local) and set regions
- Return to index and process you image
## Todos:
* test and improve
* make a hassio component (not actually possible cause nor tflite-runtime nor tensorflow supports python 3.13). Perhaps can hassio use venv ?
* make a scene text recognition model to recognise all digits in one shot. (actually investigating paddleOcr, OpenOcr, Parsec)
## Sources and inspiration:
* The idea : https://github.com/jomjol/AI-on-the-edge-device/
* The AI model : https://github.com/haverland/Tenth-of-step-of-a-meter-digit/tree/master/output
## Licence:
* Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC-BY-NC-SA)
* No commercial use
* The AI model from haverland is under Apache Licence