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recognize: skip tiny or bin-empty lines, too #76

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Sep 16, 2022
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recognize: skip tiny or bin-empty lines, too #76

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14 changes: 11 additions & 3 deletions ocrd_calamari/recognize.py
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Original file line number Diff line number Diff line change
Expand Up @@ -97,15 +97,23 @@ def process(self):
log.debug("Recognizing line '%s' in region '%s'", line.id, region.id)

line_image, line_coords = self.workspace.image_from_segment(line, region_image, region_coords, feature_selector=self.features)
if ('binarized' not in line_coords['features'] and 'grayscale_normalized' not in line_coords['features'] and self.network_input_channels == 1):
if ('binarized' not in line_coords['features'] and
'grayscale_normalized' not in line_coords['features'] and
self.network_input_channels == 1):
# We cannot use a feature selector for this since we don't
# know whether the model expects (has been trained on)
# binarized or grayscale images; but raw images are likely
# always inadequate:
log.warning("Using raw image for line '%s' in region '%s'", line.id, region.id)

line_image = line_image if all(line_image.size) else [[0]]
line_image_np = np.array(line_image, dtype=np.uint8)
if (not all(line_image.size) or
line_image.height <= 8 or line_image.width <= 8 or
'binarized' in line_coords['features'] and line_image.convert('1').getextrema()[0] == 255):
# empty size or too tiny or no foreground at all: skip
log.warning("Skipping empty line '%s' in region '%s'", line.id, region.id)
line_image_np = np.array([[0]], dtype=np.uint8)
else:
line_image_np = np.array(line_image, dtype=np.uint8)
line_images_np.append(line_image_np)
line_coordss.append(line_coords)
raw_results_all = self.predictor.predict_raw(line_images_np, progress_bar=False)
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