Comments (2)
I haven't tried that. This method is designed for detection of text in images of outdoor or indoor scenes, aka scene text, and the papers proposing new methods for detection of scene text, including EAST, do not conduct experiments on documents.
In theory, it should be easy for the model to detect bounding boxes of text regions, but it only detects the boxes. For documents, you probably need to detect whole text lines and the flow of the paragraph as well, so you would have to implement some post-processing to link the detected bounding boxes in text lines, and the text lines in paragraphs.
from east.
It works extremely well on documents provided that you can adapt the training dataset.
from east.
Related Issues (20)
- Interpretation of output?
- The history object HOT 1
- CustomTensorboard and ValidationEvaluator callbacks HOT 1
- Error for input_size other that 512 HOT 1
- No such layer: activation_49 HOT 2
- Access denied HOT 1
- StopIteration error when training HOT 1
- AttributeError: 'LearningRateScheduler' object has no attribute '_implements_train_batch_hooks'
- error in adamw learning rate HOT 2
- The system cannot find the file specified HOT 1
- File "/home/u00012/code/Text-Detection/EAST-keras/model.py", line 13, in resize_bilinear HOT 1
- Run prediction on gpu
- Error in training ICDAR data on CPU
- PAINFULLY slow to do prediction with kurapan/EAST implementation
- Annotations for EAST [help wated]
- Trained Model HOT 1
- model.json Issue
- Unable to run eval.py via the provided json pre-trained model.
- can we custom train for specific number detection like credit card number
- No changes of hmean, precision and recall
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from east.