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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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+
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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