When using the ParseQ model for inference, if a blank image is input, the output content is out of thin air.
To solve this problem, I generated 10,000 blank images of varying lengths and set their labels to a single space ‘ ’, but these data were ignored when finetuning the model：
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# We filter out samples which don't contain any supported characters |
How can I solve this problem?
Should I simply set remove_whitespace to false?
For blank images of varying lengths, should I set their labels to a single space or to different numbers of spaces depending on the length of the image?
When using the ParseQ model for inference, if a blank image is input, the output content is out of thin air.
To solve this problem, I generated 10,000 blank images of varying lengths and set their labels to a single space ‘ ’, but these data were ignored when finetuning the model：
parseq/strhub/data/dataset.py
Line 115 in 1902db0
How can I solve this problem?
Should I simply set remove_whitespace to false?
For blank images of varying lengths, should I set their labels to a single space or to different numbers of spaces depending on the length of the image?