def prepare_mask(self):
img = self.obj.sheet.get_page_image(self.obj.page_number)
width, height = self.obj.width, self.obj.height
matrix = list(img.recognize.matrix)
# Remove any offset from the matrix
matrix[4] = 0
matrix[5] = 0
matrix = cairo.Matrix(*matrix)
px_width, px_height = matrix.transform_distance(width, height)
px_width, px_height = int(math.ceil(px_width)), int(
math.ceil(px_height))
surf = cairo.ImageSurface(cairo.FORMAT_A1, px_width, px_height)
cr = cairo.Context(surf)
cr.set_source_rgba(0, 0, 0, 0)
cr.set_operator(cairo.OPERATOR_SOURCE)
cr.paint()
# Move to center and apply matrix
cr.translate(0.5 * px_width, 0.5 * px_height)
cr.transform(matrix)
cr.set_source_rgba(0, 0, 0, 1)
line_width = 1 / 72.0 * 25.4
cr.set_line_width(line_width)
matrix.invert()
xoff, yoff = matrix.transform_distance(px_width / 2.0, px_height / 2.0)
xoff = xoff - width / 2
yoff = yoff - width / 2
return cr, surf, line_width, width, height, xoff, yoff
def prepare_mask(self):
img = self.obj.sheet.get_page_image(self.obj.page_number)
width, height = self.obj.width, self.obj.height
matrix = list(img.recognize.matrix)
# Remove any offset from the matrix
matrix[4] = 0
matrix[5] = 0
matrix = cairo.Matrix(*matrix)
px_width, px_height = matrix.transform_distance(width, height)
px_width, px_height = int(math.ceil(px_width)), int(math.ceil(px_height))
surf = cairo.ImageSurface(cairo.FORMAT_A1, px_width, px_height)
cr = cairo.Context(surf)
cr.set_source_rgba(0, 0, 0, 0)
cr.set_operator(cairo.OPERATOR_SOURCE)
cr.paint()
# Move to center and apply matrix
cr.translate(0.5 * px_width, 0.5 * px_height)
cr.transform(matrix)
cr.set_source_rgba(0, 0, 0, 1)
line_width = 1 / 72.0 * 25.4
cr.set_line_width(line_width)
matrix.invert()
xoff, yoff = matrix.transform_distance(px_width / 2.0, px_height / 2.0)
xoff = xoff - width / 2
yoff = yoff - height / 2
return cr, surf, line_width, width, height, xoff, yoff
def recognize(self):
img = self.obj.sheet.get_page_image(self.obj.page_number)
if img is None or img.recognize.matrix is None:
self.obj.sheet.valid = 0
return
surf, xoff, yoff = self.get_outline_mask()
matrix, covered = img.recognize.correction_matrix_masked(
self.obj.x, self.obj.y, surf)
# Calculate some sort of quality for the checkbox position
if covered < defs.image_line_coverage:
pos_quality = 0
else:
pos_quality = min(covered + 0.2, 1)
x, y = matrix.transform_point(self.obj.x, self.obj.y)
width, height = matrix.transform_distance(self.obj.width,
self.obj.height)
self.obj.data.x = x + xoff
self.obj.data.y = y + yoff
self.obj.data.width = width
self.obj.data.height = height
# The debug struct will be filled in if debugging is enabled in the
# C library. This is done by the boxgallery script currently.
self.debug = {}
mask, xoff, yoff = self.get_inner_mask()
x, y = self.obj.data.x, self.obj.data.y
x, y = x + xoff, y + yoff
x, y = img.recognize.matrix.transform_point(x, y)
x, y = int(x), int(y)
remove_line_width = 1.2 * 25.4 / 72.0
remove_line_width_px = max(
img.recognize.matrix.transform_distance(remove_line_width,
remove_line_width))
coverage = img.recognize.get_masked_coverage(mask, x, y)
self.obj.data.metrics['coverage'] = coverage
self.debug['coverage'] = image.get_debug_surface()
# Remove 3 lines with width 1.2pt(about 5px).
coverage = img.recognize.get_masked_coverage_without_lines(
mask, x, y, remove_line_width_px, 3)
self.obj.data.metrics['cov-lines-removed'] = coverage
self.debug['cov-lines-removed'] = image.get_debug_surface()
count, coverage = img.recognize.get_masked_white_area_count(
mask, x, y, 0.05, 1.0)
self.obj.data.metrics['cov-min-size'] = coverage
self.debug['cov-min-size'] = image.get_debug_surface()
state = 0
quality = -1
# Iterate the ranges
for metric, value in self.obj.data.metrics.iteritems():
metric = defs.checkbox_metrics[
self.obj.sheet.survey.defs.checkmode][metric]
for lower, upper in zip(metric[:-1], metric[1:]):
if value >= lower[0] and value <= upper[0]:
# Interpolate quality value
if lower[0] != upper[0]:
metric_quality = lower[2] + (upper[2] - lower[2]) * (
value - lower[0]) / (upper[0] - lower[0])
else:
metric_quality = lower[2]
if metric_quality > quality:
state = lower[1]
quality = metric_quality
self.obj.data.state = state
self.obj.data.quality = min(quality, pos_quality)
def recognize(self):
img = self.obj.sheet.get_page_image(self.obj.page_number)
if img is None or img.recognize.matrix is None:
self.obj.sheet.valid = 0
return
surf, xoff, yoff = self.get_outline_mask()
matrix, covered = img.recognize.correction_matrix_masked(
self.obj.x, self.obj.y,
surf
)
# Calculate some sort of quality for the checkbox position
if covered < defs.image_line_coverage:
pos_quality = 0
else:
pos_quality = min(covered + 0.2, 1)
x, y = matrix.transform_point(self.obj.x, self.obj.y)
width, height = matrix.transform_distance(self.obj.width, self.obj.height)
self.obj.data.x = x + xoff
self.obj.data.y = y + yoff
self.obj.data.width = width
self.obj.data.height = height
# The debug struct will be filled in if debugging is enabled in the
# C library. This is done by the boxgallery script currently.
self.debug = {}
mask, xoff, yoff = self.get_inner_mask()
x, y = self.obj.data.x, self.obj.data.y
x, y = x + xoff, y + yoff
x, y = img.recognize.matrix.transform_point(x, y)
x, y = int(x), int(y)
remove_line_width = 1.2 * 25.4 / 72.0
remove_line_width_px = max(img.recognize.matrix.transform_distance(remove_line_width, remove_line_width))
coverage = img.recognize.get_masked_coverage(mask, x, y)
self.obj.data.metrics['coverage'] = coverage
self.debug['coverage'] = image.get_debug_surface()
# Remove 3 lines with width 1.2pt(about 5px).
coverage = img.recognize.get_masked_coverage_without_lines(mask, x, y, remove_line_width_px, 3)
self.obj.data.metrics['cov-lines-removed'] = coverage
self.debug['cov-lines-removed'] = image.get_debug_surface()
count, coverage = img.recognize.get_masked_white_area_count(mask, x, y, 0.05, 1.0)
self.obj.data.metrics['cov-min-size'] = coverage
self.debug['cov-min-size'] = image.get_debug_surface()
state = 0
quality = -1
# Iterate the ranges
for metric, value in self.obj.data.metrics.iteritems():
metric = defs.checkbox_metrics[self.obj.sheet.survey.defs.checkmode][metric]
for lower, upper in zip(metric[:-1], metric[1:]):
if value >= lower[0] and value <= upper[0]:
# Interpolate quality value
if lower[0] != upper[0]:
metric_quality = lower[2] + (upper[2] - lower[2]) * (value - lower[0]) / (upper[0] - lower[0])
else:
metric_quality = lower[2]
if metric_quality > quality:
state = lower[1]
quality = metric_quality
self.obj.data.state = state
self.obj.data.quality = min(quality, pos_quality)
