Parameters can apply to the whole model or be specific for a given component.
The following table gives an overview, which parameters can be set and
which ones retrieved as well as for which model part they apply.
Note, the device can be reset for an individual component, in which case
only the possibly remaining part of the model (e.g., the remaining
component) will be executed on the device of this handle.
Default: Handle of the default device, thus the GPU with index
0 when querying a list using get_systemget_systemGetSystemGetSystemGetSystemget_system
with 'cuda_devices'"cuda_devices""cuda_devices""cuda_devices""cuda_devices""cuda_devices".
If no device is available, this is an empty tuple.
This parameter will set the device on which the detection component of
the Deep OCR model is executed. For a further description, see
'device'"device""device""device""device""device".
Default: The same value as for 'device'"device""device""device""device""device".
Tuple containing the image dimensions ('detection_image_width'"detection_image_width""detection_image_width""detection_image_width""detection_image_width""detection_image_width",
'detection_image_height'"detection_image_height""detection_image_height""detection_image_height""detection_image_height""detection_image_height", number of channels) the detection
component will process.
The input image is scaled to 'detection_image_dimensions'"detection_image_dimensions""detection_image_dimensions""detection_image_dimensions""detection_image_dimensions""detection_image_dimensions"
such that the original aspect ratio is preserved. The scaled image
is padded with gray value 0 if necessary. Therefore, changing
the 'detection_image_height'"detection_image_height""detection_image_height""detection_image_height""detection_image_height""detection_image_height" or 'detection_image_width'"detection_image_width""detection_image_width""detection_image_width""detection_image_width""detection_image_width"
can influence the results.
Height of the images the detection component will process.
This means, the network preserves the aspect ratio of the input image by
scaling it to a maximum of this height before processing it. Thus this size
can influence the results.
The model architecture requires that the height is a multiple of 32. If
this is not the case, the height is rounded up to the nearest integer
multiple of 32.
Tuple containing the image size ('detection_image_width'"detection_image_width""detection_image_width""detection_image_width""detection_image_width""detection_image_width",
'detection_image_height'"detection_image_height""detection_image_height""detection_image_height""detection_image_height""detection_image_height") the detection component will
process.
Width of the images the detection component will process.
This means, the network preserves the aspect ratio of the input image by
scaling it to a maximum of this width before processing it. Thus this size
can influence the results.
The model architecture requires that the width is a multiple of 32. If
this is not the case, the width is rounded up to the nearest integer
multiple of 32.
The parameter 'detection_min_character_score'"detection_min_character_score""detection_min_character_score""detection_min_character_score""detection_min_character_score""detection_min_character_score" specifies the lower
threshold used for the character score map to estimate the dimensions of
the characters.
By adjusting the parameter, suggested instances can be split up or
neighboring instances can be merged.
The parameter 'detection_min_link_score'"detection_min_link_score""detection_min_link_score""detection_min_link_score""detection_min_link_score""detection_min_link_score" defines the minimum link
score required between two localized characters to recognize these
characters as coherent word.
The parameter 'detection_min_word_area'"detection_min_word_area""detection_min_word_area""detection_min_word_area""detection_min_word_area""detection_min_word_area" defines the minimum size
that a localized word must have in order to be suggested.
This parameter can be used to filter suggestions that are too small.
The parameter 'detection_min_word_score'"detection_min_word_score""detection_min_word_score""detection_min_word_score""detection_min_word_score""detection_min_word_score" defines the minimum
score a localized instance must contain to be suggested as valid word.
With this parameter uncertain words can be filtered out.
This parameter allows to set a predefined orientation angle for the word
detection. To revert to default behavior using the internal orientation
estimation, 'detection_orientation'"detection_orientation""detection_orientation""detection_orientation""detection_orientation""detection_orientation" is set to 'auto'"auto""auto""auto""auto""auto".
The words are sorted line-wise based on the orientation of the localized
word instances. If a sorting in row and column direction is preferred, the
parameter 'detection_sort_by_line'"detection_sort_by_line""detection_sort_by_line""detection_sort_by_line""detection_sort_by_line""detection_sort_by_line" has to be set to
'false'"false""false""false""false""false".
The input image is automatically split into overlapping tile images of
size 'detection_image_size'"detection_image_size""detection_image_size""detection_image_size""detection_image_size""detection_image_size", which are processed separately by
the detection component. This allows processing images that are much
larger than the actual 'detection_image_size'"detection_image_size""detection_image_size""detection_image_size""detection_image_size""detection_image_size" without having to
zoom the input image.
Thus, if 'detection_tiling'"detection_tiling""detection_tiling""detection_tiling""detection_tiling""detection_tiling" = {'true'}, the input image will
not be zoomed before processing it.
Number of images in a batch that is transferred to device memory and
processed in parallel in the recognition component. For further
details, please refer to the reference documentation of
apply_dl_modelapply_dl_modelApplyDlModelApplyDlModelApplyDlModelapply_dl_model with respect to the parameter
'batch_size'"batch_size""batch_size""batch_size""batch_size""batch_size". This parameter can be used to optimize the
runtime of apply_deep_ocrapply_deep_ocrApplyDeepOcrApplyDeepOcrApplyDeepOcrapply_deep_ocr on a given dl device. If the
recognition component has to process multiple inputs (words),
processing multiple inputs in parallel can result in a faster execution
of apply_deep_ocrapply_deep_ocrApplyDeepOcrApplyDeepOcrApplyDeepOcrapply_deep_ocr. Note, however, that a higher
'recognition_batch_size'"recognition_batch_size""recognition_batch_size""recognition_batch_size""recognition_batch_size""recognition_batch_size" will require more device memory.
This parameter will set the device on which the recognition component of
the Deep OCR model is executed. For a further description, see
'device'"device""device""device""device""device".
Default: The same value as for 'device'"device""device""device""device""device".
Tuple containing the image dimensions ('recognition_image_width'"recognition_image_width""recognition_image_width""recognition_image_width""recognition_image_width""recognition_image_width",
'recognition_image_height'"recognition_image_height""recognition_image_height""recognition_image_height""recognition_image_height""recognition_image_height", number of channels)
the recognition component will process.
This means, the network will first zoom the input image part to
'recognition_image_height'"recognition_image_height""recognition_image_height""recognition_image_height""recognition_image_height""recognition_image_height" while maintaining the aspect ratio
of the input. If the width of the resulting image is smaller than
'recognition_image_width'"recognition_image_width""recognition_image_width""recognition_image_width""recognition_image_width""recognition_image_width", the image part is padded with
gray value 0 on the right. If it is larger, the image is
zoomed to 'recognition_image_width'"recognition_image_width""recognition_image_width""recognition_image_width""recognition_image_width""recognition_image_width".
If the parameters are valid, the operator get_deep_ocr_paramget_deep_ocr_paramGetDeepOcrParamGetDeepOcrParamGetDeepOcrParamget_deep_ocr_param
returns the value TRUE. If necessary, an exception is raised.