Comments (8)
Should I work on this issue? @smaranjitghose
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How do you propose we intergrate the OCR model ( I do not recommend using Tesseract) into the Flutter APP?
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I am not very sure of the exact integration method we could use for it. But we can use a pre-trained model's weights, train it on our use case's dataset and then we can look forward to integrating it into the app.
As far as i know we can plugin our own tensorflow models in the flutter app
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https://medium.com/@am15hg/text-classification-using-tensorflow-lite-plugin-for-flutter-3b92f6655982
This article deals with the problem, but it doesn't train its own model , instead its directly integrates a model from tensorflow.
from doclense.
I am not very sure of the exact integration method we could use for it. But we can use a pre-trained model's weights, train it on our use case's dataset and then we can look forward to integrating it into the app.
As far as i know we can plugin our own tensorflow models in the flutter app
Yes I am aware of using tflite with Flutter. But for that you need to train your own model, quantize it and then convert it to tflite
from doclense.
I think I can use the pretrained weights to create a new model, train it on a dataset on GPU-enabled google colab. Since it is fort he purpose of OCR, i think it can be done. I have done a similar docscanner project in the past but we didnt worry for its integration with a mobile app back then.
Seems challenging , but worth a try!
What do you say @smaranjitghose?
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And can u add the DWOC label if I proceed with this? @smaranjitghose
from doclense.
I think I can use the pretrained weights to create a new model, train it on a dataset on GPU-enabled google colab. Since it is fort he purpose of OCR, i think it can be done. I have done a similar docscanner project in the past but we didnt worry for its integration with a mobile app back then.
Seems challenging , but worth a try!
What do you say @smaranjitghose?
Unless we can integrate the model, the entire effort would be futile. Read some blogs on it and get back to us
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