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In fact this plate would be detected as NV12345. Note the missing “spaces”. This might not be an issue for US plates, but it is for EU.
I tried the model with an EU (German) video feed. I was surprised, that it perfectly detects EU number plates, but it has a big problem: The loss of the “spaces” causes ambiguities.
For instance: A Berlin number plate can look like so: “B NO 1234”. A Bonn number plate could look like so “BN O 1234”. Due to the loss of “spaces” both are indicated as “BNO1234” which is ambiguous.
Is there anything which can be done to tackle this?
The text was updated successfully, but these errors were encountered:
This image is misleading:
In fact this plate would be detected as NV12345. Note the missing “spaces”. This might not be an issue for US plates, but it is for EU.
I tried the model with an EU (German) video feed. I was surprised, that it perfectly detects EU number plates, but it has a big problem: The loss of the “spaces” causes ambiguities.
For instance: A Berlin number plate can look like so: “B NO 1234”. A Bonn number plate could look like so “BN O 1234”. Due to the loss of “spaces” both are indicated as “BNO1234” which is ambiguous.
Is there anything which can be done to tackle this?
The text was updated successfully, but these errors were encountered: