Ensure all models work only on valid pages (#158)

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>
This commit is contained in:
Christoph Auer
2024-10-18 08:54:06 +02:00
committed by GitHub
parent 034a411057
commit a00c937e19
10 changed files with 413 additions and 376 deletions

View File

@@ -273,68 +273,72 @@ class LayoutModel(BasePageModel):
def __call__(self, page_batch: Iterable[Page]) -> Iterable[Page]:
for page in page_batch:
assert page.size is not None
assert page._backend is not None
if not page._backend.is_valid():
yield page
else:
assert page.size is not None
clusters = []
for ix, pred_item in enumerate(
self.layout_predictor.predict(page.get_image(scale=1.0))
):
label = DocItemLabel(
pred_item["label"].lower().replace(" ", "_").replace("-", "_")
) # Temporary, until docling-ibm-model uses docling-core types
cluster = Cluster(
id=ix,
label=label,
confidence=pred_item["confidence"],
bbox=BoundingBox.model_validate(pred_item),
cells=[],
)
clusters.append(cluster)
# Map cells to clusters
# TODO: Remove, postprocess should take care of it anyway.
for cell in page.cells:
for cluster in clusters:
if not cell.bbox.area() > 0:
overlap_frac = 0.0
else:
overlap_frac = (
cell.bbox.intersection_area_with(cluster.bbox)
/ cell.bbox.area()
)
if overlap_frac > 0.5:
cluster.cells.append(cell)
# Pre-sort clusters
# clusters = self.sort_clusters_by_cell_order(clusters)
# DEBUG code:
def draw_clusters_and_cells():
image = copy.deepcopy(page.image)
draw = ImageDraw.Draw(image)
for c in clusters:
x0, y0, x1, y1 = c.bbox.as_tuple()
draw.rectangle([(x0, y0), (x1, y1)], outline="green")
cell_color = (
random.randint(30, 140),
random.randint(30, 140),
random.randint(30, 140),
clusters = []
for ix, pred_item in enumerate(
self.layout_predictor.predict(page.get_image(scale=1.0))
):
label = DocItemLabel(
pred_item["label"].lower().replace(" ", "_").replace("-", "_")
) # Temporary, until docling-ibm-model uses docling-core types
cluster = Cluster(
id=ix,
label=label,
confidence=pred_item["confidence"],
bbox=BoundingBox.model_validate(pred_item),
cells=[],
)
for tc in c.cells: # [:1]:
x0, y0, x1, y1 = tc.bbox.as_tuple()
draw.rectangle([(x0, y0), (x1, y1)], outline=cell_color)
image.show()
clusters.append(cluster)
# draw_clusters_and_cells()
# Map cells to clusters
# TODO: Remove, postprocess should take care of it anyway.
for cell in page.cells:
for cluster in clusters:
if not cell.bbox.area() > 0:
overlap_frac = 0.0
else:
overlap_frac = (
cell.bbox.intersection_area_with(cluster.bbox)
/ cell.bbox.area()
)
clusters, page.cells = self.postprocess(
clusters, page.cells, page.size.height
)
if overlap_frac > 0.5:
cluster.cells.append(cell)
# draw_clusters_and_cells()
# Pre-sort clusters
# clusters = self.sort_clusters_by_cell_order(clusters)
page.predictions.layout = LayoutPrediction(clusters=clusters)
# DEBUG code:
def draw_clusters_and_cells():
image = copy.deepcopy(page.image)
draw = ImageDraw.Draw(image)
for c in clusters:
x0, y0, x1, y1 = c.bbox.as_tuple()
draw.rectangle([(x0, y0), (x1, y1)], outline="green")
yield page
cell_color = (
random.randint(30, 140),
random.randint(30, 140),
random.randint(30, 140),
)
for tc in c.cells: # [:1]:
x0, y0, x1, y1 = tc.bbox.as_tuple()
draw.rectangle([(x0, y0), (x1, y1)], outline=cell_color)
image.show()
# draw_clusters_and_cells()
clusters, page.cells = self.postprocess(
clusters, page.cells, page.size.height
)
# draw_clusters_and_cells()
page.predictions.layout = LayoutPrediction(clusters=clusters)
yield page