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neural-network-autotrain-digital-counter

Action and script controlled automated training of neural network to readout the value of a digital counter. This is an via GitHub Actions automatized version of https://github.com/jomjol/neural-network-digital-counter-readout.

There you also find further background information.

Working principle:

1. New training image of a digital counter is uploaded to the directory /ziffer_raw/ is uploaded
2. GitHub action for a training cycle including the new images is started
   • starting point: old trained neural network (loading of the old training status)
   • different versions of the neural network are trained in a dedicated docker container
3. Standardized report are generated to evaluate the training success
4. Reports and results are pushed to the GitHub for further investigations and usage
   • Old training status is stored additionally (reports and neural network configurations)

The neural network is used within the "AI-on-the-edge" project to digitize different analog meters (watermeter, gasmeter, ...) as the a water meter measurement system. An overview can be found here: https://github.com/jomjol/AI-on-the-edge-device

1.2.2 New Images - (2022-06-30)

• Accumulate new images

1.5.0 New Images - (2022-04-24)

• New Images

1.4.0 New Images - (2022-03-15)

• Techem images

1.3.1 New Images - (2022-02-27)

• new images

1.3.0 New Images - (2022-02-23)

• new images series (ISKRA meters)

1.2.3 New Images - (2022-02-23)

• new images

1.2.2 New Images - (2022-02-11)

• new images

1.2.1 New Images - (2022-02-05)

• new images

1.2.0 Reset - (2022-01-21)

• Corrected wrong labeling (LCD) and reset the learing

1.1.1 New Images - (2022-01-10)

• Updated LCD images

1.1.0 New Images - (2022-01-02)

• Full set of LCD images (rather pasty)

1.0.0 Initial Version - (2021-12-20)

• Initial Version

Overview older Versions

Description

Background and details for the neural network can be found in: https://github.com/jomjol/neural-network-digital-counter-readout