PaddleOCR Parser and message #62
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…r characters. This PR adds a classification_sequence_message that returns a sequence of charecters corresponding to maximum probability in the sequence. The message has optional parameters to remove duplicates and ignore background class indexes. In addition this PR also adds a PaddleOCR Parser, which utilizes the classification_sequence message.
aljazkonec1
requested review from
tersekmatija,
jkbmrz,
kkeroo and
klemen1999
as code owners
Test Results110 tests 110 ✅ 1s ⏱️ Results for commit d4cea65. |
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aljazkonec1
changed the title
jkbmrz
requested changes
Sep 10, 2024
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| """Initializes the PaddleOCR Parser node. | ||
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| @param classes: List of class names to be |
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some descriptions are missing here
| self.out = self.createOutput() | ||
| self.input = self.createInput() | ||
| self.remove_duplicates = remove_duplicates | ||
| self.ignored_indexes = [0] if ignored_indexes is None else ignored_indexes |
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it would be more clean to set the default ignored_indexes to [0] instead of None
| def setRemoveDuplicates(self, remove_duplicates: bool): | ||
| """Sets the remove_duplicates flag for the classification sequence model. | ||
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| @param remove_duplicates: If True, removes consecutive duplicates from the |
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@type is missing in the docstring (also below)
| from .. import Classifications | ||
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| def create_classification_sequence_message( |
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I'm not sure this needs a separate creator function. Could we adjust the create_classification_message to also support the new features (remove_duplicates and ignored_indexes)?
| @type classes: List | ||
| @param scores: A numpy array of shape (sequence_length, n_classes) containing the (row-wise) probability distributions over the classes. | ||
| @type scores: np.ndarray | ||
| @param remove_duplicates: If True, removes consecutive duplicates from the sequence. |
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Maybe explain this duplicate removal better as it not really clear what is removed and why
Merged
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This PR adds a classification_sequence_message that returns a sequence of charecters corresponding to maximum probability in the sequence. The message has optional parameters to remove duplicates and ignore background class indexes.
In addition this PR also adds a PaddleOCR Parser, which utilizes the classification_sequence message.