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Apply mask at threshold level

pull/2/head
Vinayak Mehta 2019-01-04 20:15:41 +05:30
parent 03f301b25c
commit eaca147b9d
2 changed files with 25 additions and 26 deletions
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17
camelot/image_processing.py
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@ -97,17 +97,24 @@ def find_lines(threshold, regions=None, direction='horizontal',
raise ValueError("Specify direction as either 'vertical' or" raise ValueError("Specify direction as either 'vertical' or"
" 'horizontal'") " 'horizontal'")
if regions is not None:
region_mask = np.zeros(threshold.shape)
for region in regions:
x, y, w, h = region
region_mask[y : y + h, x : x + w] = 1
threshold = np.multiply(threshold, region_mask)
threshold = cv2.erode(threshold, el) threshold = cv2.erode(threshold, el)
threshold = cv2.dilate(threshold, el) threshold = cv2.dilate(threshold, el)
dmask = cv2.dilate(threshold, el, iterations=iterations) dmask = cv2.dilate(threshold, el, iterations=iterations)
try: try:
_, contours, _ = cv2.findContours( _, contours, _ = cv2.findContours(
threshold, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) threshold.astype(np.uint8), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
except ValueError: except ValueError:
# for opencv backward compatibility # for opencv backward compatibility
contours, _ = cv2.findContours( contours, _ = cv2.findContours(
threshold, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) threshold.astype(np.uint8), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
for c in contours: for c in contours:
x, y, w, h = cv2.boundingRect(c) x, y, w, h = cv2.boundingRect(c)
@ -117,12 +124,6 @@ def find_lines(threshold, regions=None, direction='horizontal',
lines.append(((x1 + x2) // 2, y2, (x1 + x2) // 2, y1)) lines.append(((x1 + x2) // 2, y2, (x1 + x2) // 2, y1))
elif direction == 'horizontal': elif direction == 'horizontal':
lines.append((x1, (y1 + y2) // 2, x2, (y1 + y2) // 2)) 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 return dmask, lines

34
camelot/parsers/lattice.py
View File

@ -232,9 +232,22 @@ class Lattice(BaseParser):
stderr=subprocess.STDOUT) stderr=subprocess.STDOUT)
def _generate_table_bbox(self): def _generate_table_bbox(self):
def scale_areas(areas):
scaled_areas = []
for area in areas:
x1, y1, x2, y2 = area.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)
scaled_areas.append((x1, y1, abs(x2 - x1), abs(y2 - y1)))
return scaled_areas
self.image, self.threshold = adaptive_threshold( self.image, self.threshold = adaptive_threshold(
self.imagename, process_background=self.process_background, self.imagename, process_background=self.process_background,
blocksize=self.threshold_blocksize, c=self.threshold_constant) blocksize=self.threshold_blocksize, c=self.threshold_constant)
image_width = self.image.shape[1] image_width = self.image.shape[1]
image_height = self.image.shape[0] image_height = self.image.shape[0]
image_width_scaler = image_width / float(self.pdf_width) image_width_scaler = image_width / float(self.pdf_width)
@ -247,15 +260,8 @@ class Lattice(BaseParser):
if self.table_areas is None: if self.table_areas is None:
regions = None regions = None
if self.table_regions is not None: if self.table_regions is not None:
regions = [] regions = scale_areas(self.table_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( vertical_mask, vertical_segments = find_lines(
self.threshold, regions=regions, direction='vertical', self.threshold, regions=regions, direction='vertical',
line_scale=self.line_scale, iterations=self.iterations) line_scale=self.line_scale, iterations=self.iterations)
@ -273,15 +279,7 @@ class Lattice(BaseParser):
self.threshold, direction='horizontal', line_scale=self.line_scale, self.threshold, direction='horizontal', line_scale=self.line_scale,
iterations=self.iterations) iterations=self.iterations)
areas = [] areas = scale_areas(self.table_areas)
for area in self.table_areas:
x1, y1, x2, y2 = area.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)
areas.append((x1, y1, abs(x2 - x1), abs(y2 - y1)))
table_bbox = find_joints(areas, vertical_mask, horizontal_mask) table_bbox = find_joints(areas, vertical_mask, horizontal_mask)
self.table_bbox_unscaled = copy.deepcopy(table_bbox) self.table_bbox_unscaled = copy.deepcopy(table_bbox)