Add table regions support

pull/2/head
Vinayak Mehta 2019-01-04 19:17:54 +05:30
parent a5027e81c5
commit 03f301b25c
8 changed files with 100 additions and 47 deletions

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@ -56,12 +56,15 @@ def cli(ctx, *args, **kwargs):
@cli.command('lattice')
@click.option('-R', '--table_regions', default=[], multiple=True,
help='Page regions to analyze. Example: x1,y1,x2,y2'
' where x1, y1 -> left-top and x2, y2 -> right-bottom.')
@click.option('-T', '--table_areas', default=[], multiple=True,
help='Table areas to process. Example: x1,y1,x2,y2'
' where x1, y1 -> left-top and x2, y2 -> right-bottom.')
@click.option('-back', '--process_background', is_flag=True,
help='Process background lines.')
@click.option('-scale', '--line_size_scaling', default=15,
@click.option('-scale', '--line_scale', default=15,
help='Line size scaling factor. The larger the value,'
' the smaller the detected lines.')
@click.option('-copy', '--copy_text', default=[], type=click.Choice(['h', 'v']),
@ -105,6 +108,8 @@ def lattice(c, *args, **kwargs):
filepath = kwargs.pop('filepath')
kwargs.update(conf)
table_regions = list(kwargs['table_regions'])
kwargs['table_regions'] = None if not table_regions else table_regions
table_areas = list(kwargs['table_areas'])
kwargs['table_areas'] = None if not table_areas else table_areas
copy_text = list(kwargs['copy_text'])
@ -132,6 +137,9 @@ def lattice(c, *args, **kwargs):
@cli.command('stream')
@click.option('-R', '--table_regions', default=[], multiple=True,
help='Page regions to analyze. Example: x1,y1,x2,y2'
' where x1, y1 -> left-top and x2, y2 -> right-bottom.')
@click.option('-T', '--table_areas', default=[], multiple=True,
help='Table areas to process. Example: x1,y1,x2,y2'
' where x1, y1 -> left-top and x2, y2 -> right-bottom.')
@ -160,6 +168,8 @@ def stream(c, *args, **kwargs):
filepath = kwargs.pop('filepath')
kwargs.update(conf)
table_regions = list(kwargs['table_regions'])
kwargs['table_regions'] = None if not table_regions else table_regions
table_areas = list(kwargs['table_areas'])
kwargs['table_areas'] = None if not table_areas else table_areas
columns = list(kwargs['columns'])

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@ -48,7 +48,8 @@ def adaptive_threshold(imagename, process_background=False, blocksize=15, c=-2):
return img, threshold
def find_lines(threshold, direction='horizontal', line_size_scaling=15, iterations=0):
def find_lines(threshold, regions=None, direction='horizontal',
line_scale=15, iterations=0):
"""Finds horizontal and vertical lines by applying morphological
transformations on an image.
@ -56,9 +57,13 @@ def find_lines(threshold, direction='horizontal', line_size_scaling=15, iteratio
----------
threshold : object
numpy.ndarray representing the thresholded image.
regions : list, optional (default: None)
List of page regions that may contain tables of the form x1,y1,x2,y2
where (x1, y1) -> left-top and (x2, y2) -> right-bottom
in image coordinate space.
direction : string, optional (default: 'horizontal')
Specifies whether to find vertical or horizontal lines.
line_size_scaling : int, optional (default: 15)
line_scale : int, optional (default: 15)
Factor by which the page dimensions will be divided to get
smallest length of lines that should be detected.
@ -83,10 +88,10 @@ def find_lines(threshold, direction='horizontal', line_size_scaling=15, iteratio
lines = []
if direction == 'vertical':
size = threshold.shape[0] // line_size_scaling
size = threshold.shape[0] // line_scale
el = cv2.getStructuringElement(cv2.MORPH_RECT, (1, size))
elif direction == 'horizontal':
size = threshold.shape[1] // line_size_scaling
size = threshold.shape[1] // line_scale
el = cv2.getStructuringElement(cv2.MORPH_RECT, (size, 1))
elif direction is None:
raise ValueError("Specify direction as either 'vertical' or"
@ -112,11 +117,17 @@ def find_lines(threshold, direction='horizontal', line_size_scaling=15, iteratio
lines.append(((x1 + x2) // 2, y2, (x1 + x2) // 2, y1))
elif direction == 'horizontal':
lines.append((x1, (y1 + y2) // 2, x2, (y1 + y2) // 2))
if regions is not None:
region_mask = np.zeros(dmask.shape)
for region in regions:
x, y, w, h = region
region_mask[y : y + h, x : x + w] = 1
dmask = np.multiply(dmask, region_mask)
return dmask, lines
def find_table_contours(vertical, horizontal):
def find_contours(vertical, horizontal):
"""Finds table boundaries using OpenCV's findContours.
Parameters
@ -138,11 +149,12 @@ def find_table_contours(vertical, horizontal):
try:
__, contours, __ = cv2.findContours(
mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
mask.astype(np.uint8), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
except ValueError:
# for opencv backward compatibility
contours, __ = cv2.findContours(
mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
mask.astype(np.uint8), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# sort in reverse based on contour area and use first 10 contours
contours = sorted(contours, key=cv2.contourArea, reverse=True)[:10]
cont = []
@ -153,7 +165,7 @@ def find_table_contours(vertical, horizontal):
return cont
def find_table_joints(contours, vertical, horizontal):
def find_joints(contours, vertical, horizontal):
"""Finds joints/intersections present inside each table boundary.
Parameters
@ -176,18 +188,18 @@ def find_table_joints(contours, vertical, horizontal):
and (x2, y2) -> rt in image coordinate space.
"""
joints = np.bitwise_and(vertical, horizontal)
joints = np.multiply(vertical, horizontal)
tables = {}
for c in contours:
x, y, w, h = c
roi = joints[y : y + h, x : x + w]
try:
__, jc, __ = cv2.findContours(
roi, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
roi.astype(np.uint8), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
except ValueError:
# for opencv backward compatibility
jc, __ = cv2.findContours(
roi, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
roi.astype(np.uint8), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
if len(jc) <= 4: # remove contours with less than 4 joints
continue
joint_coords = []

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@ -52,7 +52,7 @@ def read_pdf(filepath, pages='1', password=None, flavor='lattice',
to generate columns.
process_background* : bool, optional (default: False)
Process background lines.
line_size_scaling* : int, optional (default: 15)
line_scale* : int, optional (default: 15)
Line size scaling factor. The larger the value the smaller
the detected lines. Making it very large will lead to text
being detected as lines.

View File

@ -16,7 +16,7 @@ from ..utils import (scale_image, scale_pdf, segments_in_bbox, text_in_bbox,
merge_close_lines, get_table_index, compute_accuracy,
compute_whitespace)
from ..image_processing import (adaptive_threshold, find_lines,
find_table_contours, find_table_joints)
find_contours, find_joints)
logger = logging.getLogger('camelot')
@ -28,13 +28,17 @@ class Lattice(BaseParser):
Parameters
----------
table_regions : list, optional (default: None)
List of page regions that may contain tables of the form x1,y1,x2,y2
where (x1, y1) -> left-top and (x2, y2) -> right-bottom
in PDF coordinate space.
table_areas : list, optional (default: None)
List of table area strings of the form x1,y1,x2,y2
where (x1, y1) -> left-top and (x2, y2) -> right-bottom
in PDF coordinate space.
process_background : bool, optional (default: False)
Process background lines.
line_size_scaling : int, optional (default: 15)
line_scale : int, optional (default: 15)
Line size scaling factor. The larger the value the smaller
the detected lines. Making it very large will lead to text
being detected as lines.
@ -77,14 +81,15 @@ class Lattice(BaseParser):
Resolution used for PDF to PNG conversion.
"""
def __init__(self, table_areas=None, process_background=False,
line_size_scaling=15, copy_text=None, shift_text=['l', 't'],
def __init__(self, table_regions=None, table_areas=None, process_background=False,
line_scale=15, copy_text=None, shift_text=['l', 't'],
split_text=False, flag_size=False, strip_text='', line_tol=2,
joint_tol=2, threshold_blocksize=15, threshold_constant=-2,
iterations=0, resolution=300, **kwargs):
self.table_regions = table_regions
self.table_areas = table_areas
self.process_background = process_background
self.line_size_scaling = line_size_scaling
self.line_scale = line_scale
self.copy_text = copy_text
self.shift_text = shift_text
self.split_text = split_text
@ -239,14 +244,35 @@ class Lattice(BaseParser):
image_scalers = (image_width_scaler, image_height_scaler, self.pdf_height)
pdf_scalers = (pdf_width_scaler, pdf_height_scaler, image_height)
vertical_mask, vertical_segments = find_lines(
self.threshold, direction='vertical',
line_size_scaling=self.line_size_scaling, iterations=self.iterations)
horizontal_mask, horizontal_segments = find_lines(
self.threshold, direction='horizontal',
line_size_scaling=self.line_size_scaling, iterations=self.iterations)
if self.table_areas is None:
regions = None
if self.table_regions is not None:
regions = []
for region in self.table_regions:
x1, y1, x2, y2 = region.split(",")
x1 = float(x1)
y1 = float(y1)
x2 = float(x2)
y2 = float(y2)
x1, y1, x2, y2 = scale_pdf((x1, y1, x2, y2), image_scalers)
regions.append((x1, y1, abs(x2 - x1), abs(y2 - y1)))
vertical_mask, vertical_segments = find_lines(
self.threshold, regions=regions, direction='vertical',
line_scale=self.line_scale, iterations=self.iterations)
horizontal_mask, horizontal_segments = find_lines(
self.threshold, regions=regions, direction='horizontal',
line_scale=self.line_scale, iterations=self.iterations)
contours = find_contours(vertical_mask, horizontal_mask)
table_bbox = find_joints(contours, vertical_mask, horizontal_mask)
else:
vertical_mask, vertical_segments = find_lines(
self.threshold, direction='vertical', line_scale=self.line_scale,
iterations=self.iterations)
horizontal_mask, horizontal_segments = find_lines(
self.threshold, direction='horizontal', line_scale=self.line_scale,
iterations=self.iterations)
if self.table_areas is not None:
areas = []
for area in self.table_areas:
x1, y1, x2, y2 = area.split(",")
@ -256,10 +282,7 @@ class Lattice(BaseParser):
y2 = float(y2)
x1, y1, x2, y2 = scale_pdf((x1, y1, x2, y2), image_scalers)
areas.append((x1, y1, abs(x2 - x1), abs(y2 - y1)))
table_bbox = find_table_joints(areas, vertical_mask, horizontal_mask)
else:
contours = find_table_contours(vertical_mask, horizontal_mask)
table_bbox = find_table_joints(contours, vertical_mask, horizontal_mask)
table_bbox = find_joints(areas, vertical_mask, horizontal_mask)
self.table_bbox_unscaled = copy.deepcopy(table_bbox)

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@ -26,6 +26,10 @@ class Stream(BaseParser):
Parameters
----------
table_regions : list, optional (default: None)
List of page regions that may contain tables of the form x1,y1,x2,y2
where (x1, y1) -> left-top and (x2, y2) -> right-bottom
in PDF coordinate space.
table_areas : list, optional (default: None)
List of table area strings of the form x1,y1,x2,y2
where (x1, y1) -> left-top and (x2, y2) -> right-bottom
@ -51,9 +55,10 @@ class Stream(BaseParser):
to generate columns.
"""
def __init__(self, table_areas=None, columns=None, split_text=False,
def __init__(self, table_regions=None, table_areas=None, columns=None, split_text=False,
flag_size=False, strip_text='', edge_tol=50, row_tol=2,
column_tol=0, **kwargs):
self.table_regions = table_regions
self.table_areas = table_areas
self.columns = columns
self._validate_columns()
@ -275,7 +280,13 @@ class Stream(BaseParser):
def _generate_table_bbox(self):
self.textedges = []
if self.table_areas is not None:
if self.table_areas is None:
if self.table_regions is not None:
# filter horizontal text
pass
# find tables based on nurminen's detection algorithm
table_bbox = self._nurminen_table_detection(self.horizontal_text)
else:
table_bbox = {}
for area in self.table_areas:
x1, y1, x2, y2 = area.split(",")
@ -284,9 +295,6 @@ class Stream(BaseParser):
x2 = float(x2)
y2 = float(y2)
table_bbox[(x1, y2, x2, y1)] = None
else:
# find tables based on nurminen's detection algorithm
table_bbox = self._nurminen_table_detection(self.horizontal_text)
self.table_bbox = table_bbox
def _generate_columns_and_rows(self, table_idx, tk):

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@ -101,7 +101,7 @@ stream_kwargs = [
]
lattice_kwargs = [
'process_background',
'line_size_scaling',
'line_scale',
'copy_text',
'shift_text',
'line_tol',
@ -339,7 +339,7 @@ def text_in_bbox(bbox, text):
----------
bbox : tuple
Tuple (x1, y1, x2, y2) representing a bounding box where
(x1, y1) -> lb and (x2, y2) -> rt in PDFMiner coordinate
(x1, y1) -> lb and (x2, y2) -> rt in the PDF coordinate
space.
text : List of PDFMiner text objects.

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@ -434,11 +434,11 @@ You can pass ``row_tol=<+int>`` to group the rows closer together, as shown belo
Detect short lines
------------------
There might be cases while using :ref:`Lattice <lattice>` when smaller lines don't get detected. The size of the smallest line that gets detected is calculated by dividing the PDF page's dimensions with a scaling factor called ``line_size_scaling``. By default, its value is 15.
There might be cases while using :ref:`Lattice <lattice>` when smaller lines don't get detected. The size of the smallest line that gets detected is calculated by dividing the PDF page's dimensions with a scaling factor called ``line_scale``. By default, its value is 15.
As you can guess, the larger the ``line_size_scaling``, the smaller the size of lines getting detected.
As you can guess, the larger the ``line_scale``, the smaller the size of lines getting detected.
.. warning:: Making ``line_size_scaling`` very large (>150) will lead to text getting detected as lines.
.. warning:: Making ``line_scale`` very large (>150) will lead to text getting detected as lines.
Here's a `PDF <../_static/pdf/short_lines.pdf>`__ where small lines separating the the headers don't get detected with the default value of 15.
@ -458,11 +458,11 @@ Let's plot the table for this PDF.
:alt: A plot of the PDF table with short lines
:align: left
Clearly, the smaller lines separating the headers, couldn't be detected. Let's try with ``line_size_scaling=40``, and plot the table again.
Clearly, the smaller lines separating the headers, couldn't be detected. Let's try with ``line_scale=40``, and plot the table again.
::
>>> tables = camelot.read_pdf('short_lines.pdf', line_size_scaling=40)
>>> tables = camelot.read_pdf('short_lines.pdf', line_scale=40)
>>> camelot.plot(tables[0], kind='grid')
>>> plt.show()
@ -511,7 +511,7 @@ We'll use the `PDF <../_static/pdf/short_lines.pdf>`__ from the previous example
::
>>> tables = camelot.read_pdf('short_lines.pdf', line_size_scaling=40, shift_text=[''])
>>> tables = camelot.read_pdf('short_lines.pdf', line_scale=40, shift_text=[''])
>>> tables[0].df
.. csv-table::
@ -532,7 +532,7 @@ No surprises there — it did remain in place (observe the strings "2400" and "A
::
>>> tables = camelot.read_pdf('short_lines.pdf', line_size_scaling=40, shift_text=['r', 'b'])
>>> tables = camelot.read_pdf('short_lines.pdf', line_scale=40, shift_text=['r', 'b'])
>>> tables[0].df
.. tip::

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@ -179,7 +179,7 @@ def test_lattice_copy_text():
df = pd.DataFrame(data_lattice_copy_text)
filename = os.path.join(testdir, "row_span_1.pdf")
tables = camelot.read_pdf(filename, line_size_scaling=60, copy_text="v")
tables = camelot.read_pdf(filename, line_scale=60, copy_text="v")
assert df.equals(tables[0].df)
@ -189,13 +189,13 @@ def test_lattice_shift_text():
df_rb = pd.DataFrame(data_lattice_shift_text_right_bottom)
filename = os.path.join(testdir, "column_span_2.pdf")
tables = camelot.read_pdf(filename, line_size_scaling=40)
tables = camelot.read_pdf(filename, line_scale=40)
assert df_lt.equals(tables[0].df)
tables = camelot.read_pdf(filename, line_size_scaling=40, shift_text=[''])
tables = camelot.read_pdf(filename, line_scale=40, shift_text=[''])
assert df_disable.equals(tables[0].df)
tables = camelot.read_pdf(filename, line_size_scaling=40, shift_text=['r', 'b'])
tables = camelot.read_pdf(filename, line_scale=40, shift_text=['r', 'b'])
assert df_rb.equals(tables[0].df)