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courao avatar courao commented on May 20, 2024

Hi,
there may be many reasons causing such results,
like too-few training samples, wrong mapping from original predicting vectors to final text results, or unsuitable alphabet(check if all chars are included in the alphabet),
you can check the output predicting results and compare these with the ground-truth,
if they are similar, you can training more time, or add more training data.

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vasu03042000 avatar vasu03042000 commented on May 20, 2024

Actually its not predicting anything after every epoch. And by the way what should be the size of the dataset? i am training it on 1200 images

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courao avatar courao commented on May 20, 2024

Actually its not predicting anything after every epoch. And by the way what should be the size of the dataset? i am training it on 1200 images

1200 seems not enough, 10000+ or more will be better, you can add some synthetic data to overcome under-fitting.

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vasu03042000 avatar vasu03042000 commented on May 20, 2024

Can you please provide me with your dataset. Actually this will help me a lot to go through the dataset.
Mine email id is [email protected]

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vasu03042000 avatar vasu03042000 commented on May 20, 2024

I won't be commercializing it, just needed it for personal work

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courao avatar courao commented on May 20, 2024

Can you please provide me with your dataset. Actually this will help me a lot to go through the dataset.
Mine email id is [email protected]

Hi, actually most of my training are synthetic data,
you can combine part of your real data with synthetic data as total training data, and another part real data for test,
a lot of repos on GitHub are able to generate large-scale synthetic data, such as .

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