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KNN OCR Confidence

My program scans an image and is able to identify a string of numbers. It crops and rotates the image to include only the area of interest. Unfortunately, given the circumstances I have no way of knowing whether the image is upside down or rightside up. However, I do know that it is one of the two, and is not sideways or angled.

The only way I can know if the image is upright is if the numbers indicate that it is. So I am trying to figure out a method of determining confidence for KNN OCR so that I can decide to rotate 180 degrees or not.

The test would go something like this:

randomly take 10 bounding rects call k nearest on each save confidence for whole as a single number "A" rotate bounding rects 180 degrees call k nearest on each save confidence for whole as a single number "B" if B

KNN OCR Confidence

My program scans an image and is able to identify a string of numbers. It crops and rotates the image to include only the area of interest. Unfortunately, given the circumstances I have no way of knowing whether the image is upside down or rightside up. However, I do know that it is one of the two, and is not sideways or angled.

The only way I can know if the image is upright is if the numbers indicate that it is. So I am trying to figure out a method of determining confidence for KNN OCR so that I can decide to rotate 180 degrees or not.

The test would go something like this:

randomly take 10 bounding rects call k nearest on each save confidence for whole as a single number "A" rotate bounding rects 180 degrees call k nearest on each save confidence for whole as a single number "B" if B

KNN OCR Confidence

My program scans an image and is able to identify a string of numbers. It crops and rotates the image to include only the area of interest. Unfortunately, given the circumstances I have no way of knowing whether the image is upside down or rightside up. However, I do know that it is one of the two, and is not sideways or angled.

The only way I can know if the image is upright is if the numbers indicate that it is. So I am trying to figure out a method of determining confidence for KNN OCR so that I can decide to rotate 180 degrees or not.

The test would go something like this:

randomly take 10 bounding rects call k nearest on each save confidence for whole as a single number "A" rotate bounding rects 180 degrees call k nearest on each save confidence for whole as a single number "B" if B

KNN OCR Confidence

My program scans an image and is able to identify a string of numbers. It crops and rotates the image to include only the area of interest. Unfortunately, given the circumstances I have no way of knowing whether the image is upside down or rightside up. However, I do know that it is one of the two, and is not sideways or angled.

The only way I can know if the image is upright is if the numbers indicate that it is. So I am trying to figure out a method of determining confidence for KNN OCR so that I can decide to rotate 180 degrees or not.

The test would go something like this:

randomly take 10 bounding rects rects

call k nearest on each each

save confidence for whole as a single number "A" "A"

rotate bounding rects 180 degrees degrees

call k nearest on each each

save confidence for whole as a single number "B" "B"

if B

B is greater than A, rotate ROI by 180 degrees

Any advice on getting that confidence value?