Classifiying electric meters with only 45 images

Part 1 (2019)
1

Hi All!

I work for one of the biggest utilities companies in the US and currently working on a project involving automatically updating electric meter readings sent by our customers to our mainframe. I was taking part 1 of this course as a try and tested the fast.ai library with only 45 images: 15 analog meters, 15 standard, and 15 digital…the result? 87% accuracy!

We get almost 1000 images a day so imagine how many I can feed this same model after a week or two…or maybe just after 1 day! Can’t wait to see the results!

Next step is to have it identify where on the image the numbers are then will have it identify the numbers individually to give me a full meter reading.

Thanks fast.ai team!

Amir

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2

After adding another 25 images or so I’m getting this as a result now:
Total time: 00:13

epoch train_loss valid_loss error_rate
1 0.369539 0.222055 0.000000
2 0.388205 0.288855 0.133333
3 0.341020 0.396107 0.266667
4 0.293078 0.345871 0.133333
5 0.318980 0.188861 0.000000
6 0.269424 0.203167 0.133333
7 0.274584 0.187801 0.000000

Am I overfitting?

Amir