Comments (6)
And pretrained model trained on which datasets?
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Directly only trained on ICDAR13 is not suitable, since there are too few images. You can trained on SynthText and Synth90K which can be found here. And you can finetune the model on ICDAR2013 but it is optional.
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I will try the dataset,thx
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I can't get 0.918 acc, just 0.889
Even when I test with your pretrained model, the ICDAR13 acc is 0.8928? not 0.918
can you offer more details?
my batch size is 64
i can reproduce SVTP and ICDAR2015
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I finetune the model on ICDAR2013 and train for 625 iters and get 0.914acc
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I'm so sorry. I checked it again. The accuracy 91.8 is achieved on ICDAR13-857 not 1015.
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Related Issues (20)
- Same character repeated in test prediction HOT 1
- ArTLoader, Syn90KLoader and SynTextLoader missing HOT 2
- Reduce model size HOT 1
- Name of the output node with the inferenced word HOT 1
- Model tensors are linked to batch size
- train with multi gpus HOT 2
- 训练数据集 HOT 4
- Experiments or performance on Chinese HOT 2
- Mismatch with paper HOT 1
- freeze.py error HOT 3
- dataset of pre-trained model HOT 1
- Two identical experiments have completely different results
- The result of training test and offline test is different in same data HOT 1
- 中文训练
- Can you show me code to visualize the attention map?
- Performance issues in the programs
- Why the test accuracy of CUTE80 is 80.49%, not 83.6%? thanks.
- AttributeError: Can't pickle local object 'GeneratorEnqueuer.start.<locals>.data_generator_task' HOT 3
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