Comments (3)
The data format is specified in the README and should be the same for training and test.
from ochre.
Thank you for you reply
I have given the test data using following
python3 -m ochre.lstm_synced_correct_ocr model/0.1861-40.hdf5 gs.json ocr.json
Here ocr.json file contains data in format { "ocr":["\u2018", "\u0930", "\u0947", "\u0921", "\u093f", "\u092f", "\u094b"]}
Further I tried to give test data using txt files.
python3 -m ochre.lstm_synced_correct_ocr model/0.1861-40.hdf5 gs.txt ocr.txt
In both ways I am getting the below error
ValueError: Input 0 is incompatible with layer sequential: expected shape=(None, None, 171), found shape=[None, 25, 3825]
Can you please help me to give test data to the model.
from ochre.
My guess is that the error is due to updates in the dependencies and not necessarily to problems with the data. This can be expected from software that isn't actively being developed.
from ochre.
Related Issues (17)
- Make separate commands for the diffrent neural network architectures
- Error during preprocessing HOT 2
- About OCR_aligned and Lost or missing text HOT 3
- Permanent failure with VU recepie HOT 2
- Additional OCR Post correction datasets HOT 2
- Pretrained models HOT 1
- print error - ICDAR2017_shared_task_workflows.ipynb HOT 3
- /usr/bin/python: dateutil 2.5.0 is the minimum required version HOT 1
- Issues in testing HOT 3
- Update workflows for extracting datasets to accept zipfile as input
- Working without aligned file HOT 2
- Using ochre to evaluate synthetic ocr post processing dataset generation HOT 3
- Error in align_output_to_input HOT 3
- All chars assumption HOT 2
- Unsatisfying results HOT 2
- Where to start? HOT 1
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from ochre.