I am trying to decide what is the best way to preprocess an image that I have. Basically, imagine a photo of a table that has 10 rows and 3 columns. Each cell contains a handwritten digit. I built a MNIST model and retrained with my custom data. But my question is, what is the best way to pass in such input? I want to classify each row numbers for example:
| 5 | 6 | 0 |
| 0 | 1 | 2 |
Each row is a 3 digit number. I was thinking of since image size is fixed, divide into each row then each row into a single digit and pass into model for inference then reconstruct results. I looked into using a pretrained SVHN model but the data differs from handwritten digits.
Thank you for any feedback!