Comments (1)
Hi,
this is quite broad question. First, the project is divided into 4 main steps:
- Detection of page and removal of background
- Detection and separation of words
- Normalization of words
- Recognition of words (separation and recegnition of characters)
If you want to train the model on your own dataset, I would recommend this. Create dataset of words images (image of word and corresponding label). Then reprocess the images to mach the required format and used them for training of CTC classifier.
from handwriting-ocr.
Related Issues (20)
- Query: Punctuation Marks HOT 1
- Language HOT 3
- not giving output same as in your github ocr.ipynb ctc model HOT 9
- ValueError: zero-size array to reduction operation minimum which has no identity
- unimplementederror: tensor array has size zero, but element shape [?,256] is not fully defined. currently only static shapes are supported when packing zero-size tensorarray
- File models/gap-clas/CNN-CG.meta does not exist.
- No Function : imageNorm ? HOT 1
- 'TrainingPlot' object has no attribute 'updateCost' HOT 2
- Tensor shape error / not training my images HOT 1
- handwriting-ocr/word_classifier_CTC.ipynb question
- ModuleNotFoundError: No module named 'ocr'
- ValueError: too many values to unpack (expected 2) HOT 5
- training time
- How much time it takes for training i am waiting for 2 hours and what is value of LOSS_ITER and also can you check the train.csv, dev.csv, test.csv i have generated are good to use or have some error?
- What does this code doing and how can i visualize it's output. HOT 1
- ValueError: Cannot feed value of shape (13, 1, 3600) for Tensor 'inputs:0', which has shape '(None, 64, None, 1)'
- Javascript implementation HOT 1
- File does not exist. Received: F:\MY_PROJECT\handwriting-ocr-master\src\ocr\../../models/gap-clas/CNN-CG.meta. HOT 1
- Request for resources
- field to access
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from handwriting-ocr.