Datasets:
Tasks:
Image Classification
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
100K - 1M
Tags:
OCR
Handwriting
Character Recognition
Grayscale Images
ASCII Labels
Optical Character Recognition
License:
Louis Rädisch
commited on
Commit
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Parent(s):
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Update README.md
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README.md
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@@ -33,6 +33,9 @@ The AlphaNum dataset caters to a variety of use cases including text recognition
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## Null Category Image Generation
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The 'null' category comprises images generated by injecting noise to mimic randomly distributed light pixels. The creation of these images is accomplished through the following Python script:
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This approach is particularly valuable as it enables the model to effectively disregard specific areas of the training data by utilizing a 'null' label. By doing so, the model becomes better at recognizing letters and can ignore irrelevant parts, enhancing its performance in reallive OCR tasks.
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```python
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import os
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import numpy as np
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## Null Category Image Generation
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The 'null' category comprises images generated by injecting noise to mimic randomly distributed light pixels. The creation of these images is accomplished through the following Python script:
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This approach is particularly valuable as it enables the model to effectively disregard specific areas of the training data by utilizing a 'null' label. By doing so, the model becomes better at recognizing letters and can ignore irrelevant parts, enhancing its performance in reallive OCR tasks.
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The 'null' labelled images in this dataset have been generated using the following algorithm.
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(Please note that this is a non-deterministic approach, so you will most likely get different results.)
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```python
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import os
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import numpy as np
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