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.

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

• new images

• new images

• Corrected wrong labeling (LCD) and reset the learing

• Updated LCD images

• Full set of LCD images (rather pasty)

• Initial Version

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