feat: Updated Layout processing with forms and key-value areas (#530)
* Upgraded Layout Postprocessing, sending old code back to ERZ Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Implement hierachical cluster layout processing Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Pass nested cluster processing through full pipeline Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Pass nested clusters through GLM as payload Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Move to_docling_document from ds-glm to this repo Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Clean up imports again Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * feat(Accelerator): Introduce options to control the num_threads and device from API, envvars, CLI. - Introduce the AcceleratorOptions, AcceleratorDevice and use them to set the device where the models run. - Introduce the accelerator_utils with function to decide the device and resolve the AUTO setting. - Refactor the way how the docling-ibm-models are called to match the new init signature of models. - Translate the accelerator options to the specific inputs for third-party models. - Extend the docling CLI with parameters to set the num_threads and device. - Add new unit tests. - Write new example how to use the accelerator options. * fix: Improve the pydantic objects in the pipeline_options and imports. Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com> * fix: TableStructureModel: Refactor the artifacts path to use the new structure for fast/accurate model Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com> * Updated test ground-truth Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Updated test ground-truth (again), bugfix for empty layout Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * fix: Do proper check to set the device in EasyOCR, RapidOCR. Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com> * fix: Correct the way to set GPU for EasyOCR, RapidOCR Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com> * fix: Ocr AccleratorDevice Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com> * Merge pull request #556 from DS4SD/cau/layout-processing-improvement feat: layout processing improvements and bugfixes * Update lockfile Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Update tests Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Update HF model ref, reset test generate Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Repin to release package versions Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Many layout processing improvements, add document index type Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Update pinnings to docling-core Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Update test GT Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Fix table box snapping Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Fixes for cluster pre-ordering Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Introduce OCR confidence, propagate to orphan in post-processing Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Fix form and key value area groups Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Adjust confidence in EasyOcr Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Roll back CLI changes from main Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Update test GT Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Update docling-core pinning Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Annoying fixes for historical python versions Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Updated test GT for legacy Signed-off-by: Christoph Auer <cau@zurich.ibm.com> * Comment cleanup Signed-off-by: Christoph Auer <cau@zurich.ibm.com> --------- Signed-off-by: Christoph Auer <cau@zurich.ibm.com> Signed-off-by: Nikos Livathinos <nli@zurich.ibm.com> Co-authored-by: Nikos Livathinos <nli@zurich.ibm.com>
This commit is contained in:
Christoph Auer
GitHub
@@ -76,6 +76,10 @@ class TableStructureModel(BasePageModel):
|
||||
x0, y0, x1, y1 = table_element.cluster.bbox.as_tuple()
|
||||
draw.rectangle([(x0, y0), (x1, y1)], outline="red")
|
||||
|
||||
for cell in table_element.cluster.cells:
|
||||
x0, y0, x1, y1 = cell.bbox.as_tuple()
|
||||
draw.rectangle([(x0, y0), (x1, y1)], outline="green")
|
||||
|
||||
for tc in table_element.table_cells:
|
||||
if tc.bbox is not None:
|
||||
x0, y0, x1, y1 = tc.bbox.as_tuple()
|
||||
@@ -89,7 +93,6 @@ class TableStructureModel(BasePageModel):
|
||||
text=f"{tc.start_row_offset_idx}, {tc.start_col_offset_idx}",
|
||||
fill="black",
|
||||
)
|
||||
|
||||
if show:
|
||||
image.show()
|
||||
else:
|
||||
@@ -135,47 +138,40 @@ class TableStructureModel(BasePageModel):
|
||||
],
|
||||
)
|
||||
for cluster in page.predictions.layout.clusters
|
||||
if cluster.label == DocItemLabel.TABLE
|
||||
if cluster.label
|
||||
in [DocItemLabel.TABLE, DocItemLabel.DOCUMENT_INDEX]
|
||||
]
|
||||
if not len(in_tables):
|
||||
yield page
|
||||
continue
|
||||
|
||||
tokens = []
|
||||
for c in page.cells:
|
||||
for cluster, _ in in_tables:
|
||||
if c.bbox.area() > 0:
|
||||
if (
|
||||
c.bbox.intersection_area_with(cluster.bbox)
|
||||
/ c.bbox.area()
|
||||
> 0.2
|
||||
):
|
||||
# Only allow non empty stings (spaces) into the cells of a table
|
||||
if len(c.text.strip()) > 0:
|
||||
new_cell = copy.deepcopy(c)
|
||||
new_cell.bbox = new_cell.bbox.scaled(
|
||||
scale=self.scale
|
||||
)
|
||||
|
||||
tokens.append(new_cell.model_dump())
|
||||
|
||||
page_input = {
|
||||
"tokens": tokens,
|
||||
"width": page.size.width * self.scale,
|
||||
"height": page.size.height * self.scale,
|
||||
"image": numpy.asarray(page.get_image(scale=self.scale)),
|
||||
}
|
||||
page_input["image"] = numpy.asarray(
|
||||
page.get_image(scale=self.scale)
|
||||
)
|
||||
|
||||
table_clusters, table_bboxes = zip(*in_tables)
|
||||
|
||||
if len(table_bboxes):
|
||||
tf_output = self.tf_predictor.multi_table_predict(
|
||||
page_input, table_bboxes, do_matching=self.do_cell_matching
|
||||
)
|
||||
for table_cluster, tbl_box in in_tables:
|
||||
|
||||
for table_cluster, table_out in zip(table_clusters, tf_output):
|
||||
tokens = []
|
||||
for c in table_cluster.cells:
|
||||
# Only allow non empty stings (spaces) into the cells of a table
|
||||
if len(c.text.strip()) > 0:
|
||||
new_cell = copy.deepcopy(c)
|
||||
new_cell.bbox = new_cell.bbox.scaled(
|
||||
scale=self.scale
|
||||
)
|
||||
|
||||
tokens.append(new_cell.model_dump())
|
||||
page_input["tokens"] = tokens
|
||||
|
||||
tf_output = self.tf_predictor.multi_table_predict(
|
||||
page_input, [tbl_box], do_matching=self.do_cell_matching
|
||||
)
|
||||
table_out = tf_output[0]
|
||||
table_cells = []
|
||||
for element in table_out["tf_responses"]:
|
||||
|
||||
@@ -208,7 +204,7 @@ class TableStructureModel(BasePageModel):
|
||||
id=table_cluster.id,
|
||||
page_no=page.page_no,
|
||||
cluster=table_cluster,
|
||||
label=DocItemLabel.TABLE,
|
||||
label=table_cluster.label,
|
||||
)
|
||||
|
||||
page.predictions.tablestructure.table_map[
|
||||
|
||||
Reference in New Issue
Block a user