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autonise / CRAFT-Remade

Implementation of CRAFT Text Detection
MIT License
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How to reproduce the provided ICDAR2013 model? #51

Open yeonsikch opened 2 years ago

yeonsikch commented 2 years ago

Hi.

I have try that train model for ICDAR2013 dataset. my way:

  1. Save & load your SynthText Strong Supervision model (trained model for SynthText dataset, 50k iter) 2-a. python main.py weakly-supervision --model model/63000_model.pkl --iterations 2 2-b. python main.py weakly-supervision --model model/63000_model.pkl --iterations 5

[2-a] I trained for ICDAR2013 dataset and sampled SynthText dataset with probability 1/6 for each batch, totally 25k iters. But I couldn't reproduce the same performance as the ICDAR2013 model you provided. So, I did [2-b] but same results as [2-a].

How can I reproduce the results ICDAR2013 dataset?

mayank-git-hub commented 2 years ago

Hello @yeonsikch. The model file that I shared for IC13 dataset is trained on using just 1 iteration. Can you try with --iterations 1