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Improve/fix extract_text bug, esp. re. vert. text
Previously, utils.extract_text(...) returned incorrect results in certain cases when vertical text was present, as observed in https://github.com/jsvine/pdfplumber/pull/192. This commit fixes that by first segregating vertical and horizontal text (via "upright" char attribute) before clustering characters. It also adds two parameters, horizontal_ltr and vertical_ttb, to give users control over whethere words are meant to be read left-to-right and/or top-to-bottom vs. their opposites.
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@@ -94,7 +94,7 @@ The `pdfplumber.Page` class is at the core of `pdfplumber`. Most things you'll d
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|`.within_bbox(bounding_box)`| Similar to `.crop`, but only retains objects that fall *entirely* within the bounding box.|
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|`.filter(test_function)`| Returns a version of the page with only the `.objects` for which `test_function(obj)` returns `True`.|
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|`.extract_text(x_tolerance=0, y_tolerance=0)`| Collates all of the page's character objects into a single string. Adds spaces where the difference between the `x1` of one character and the `x0` of the next is greater than `x_tolerance`. Adds newline characters where the difference between the `doctop` of one character and the `doctop` of the next is greater than `y_tolerance`.|
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|`.extract_words(x_tolerance=0, y_tolerance=0)`| Returns a list of all word-looking things and their bounding boxes. Words are considered to be sequences of characters where the difference between the `x1` of one character and the `x0` of the next is less than or equal to `x_tolerance` *and* where the `doctop` of one character and the `doctop` of the next is less than or equal to `y_tolerance`.|
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|`.extract_words(x_tolerance=0, y_tolerance=0, horizontal_ltr=True, vertical_ttb=True)`| Returns a list of all word-looking things and their bounding boxes. Words are considered to be sequences of characters where (for "upright" characters) the difference between the `x1` of one character and the `x0` of the next is less than or equal to `x_tolerance` *and* where the `doctop` of one character and the `doctop` of the next is less than or equal to `y_tolerance`. A similar approach is taken for non-upright characters, but instead measuring the vertical, rather than horizontal, distances between them. The parameters `horizontal_ltr` and `vertical_ttb` indicate whether the words should be read from left-to-right (for horizontal words) / top-to-bottom (for vertical words).|
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|`.extract_tables(table_settings)`| Extracts tabular data from the page. For more details see "[Extracting tables](#extracting-tables)" below.|
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|`.to_image(**conversion_kwargs)`| Returns an instance of the `PageImage` class. For more details, see "[Visual debugging](#visual-debugging)" below. For conversion_kwargs, see [here](http://docs.wand-py.org/en/latest/wand/image.html#wand.image.Image).|
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+37
-11
@@ -164,10 +164,13 @@ def bbox_to_rect(bbox):
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"bottom": bbox[3]
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}
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def extract_words(chars,
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x_tolerance=DEFAULT_X_TOLERANCE,
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y_tolerance=DEFAULT_Y_TOLERANCE,
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keep_blank_chars=False
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keep_blank_chars=False,
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horizontal_ltr = True, # Should words be read left-to-right?
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vertical_ttb = True, # Should vertical words be read top-to-bottom?
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):
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x_tolerance = decimalize(x_tolerance)
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@@ -183,10 +186,13 @@ def extract_words(chars,
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"text": "".join(map(itemgetter("text"), chars))
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}
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def get_line_words(chars, tolerance=DEFAULT_X_TOLERANCE):
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def get_line_words(chars, is_upright, tolerance=DEFAULT_X_TOLERANCE):
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get_text = itemgetter("text")
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chars_sorted = sorted(chars, key=itemgetter("x0"))
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min_key = "x0" if is_upright else "top"
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max_key = "x1" if is_upright else "bottom"
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chars_sorted = sorted(chars, key=itemgetter(min_key))
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words = []
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current_word = []
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@@ -200,23 +206,43 @@ def extract_words(chars,
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current_word.append(char)
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else:
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last_char = current_word[-1]
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if char["x0"] > (last_char["x1"] + tolerance):
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if char[min_key] > (last_char[max_key] + tolerance):
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words.append(current_word)
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current_word = []
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current_word.append(char)
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if len(current_word) > 0:
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words.append(current_word)
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if upright:
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if horizontal_ltr:
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sorted_chars = current_word
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else:
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sorted_chars = sorted(current_word, key = lambda x: -x["x1"])
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else:
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if vertical_ttb:
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sorted_chars = sorted(current_word, key = itemgetter("doctop"))
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else:
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sorted_chars = sorted(current_word, key = lambda x: -x["bottom"])
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words.append(sorted_chars)
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processed_words = list(map(process_word_chars, words))
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return processed_words
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chars = to_list(chars)
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doctop_clusters = cluster_objects(chars, "doctop", y_tolerance)
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chars_by_upright = { 1: [], 0: [] }
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words = []
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for char in to_list(chars):
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chars_by_upright[char.get("upright", 1)].append(char)
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nested = [ get_line_words(line_chars, tolerance=x_tolerance)
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for line_chars in doctop_clusters ]
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for upright, char_group in chars_by_upright.items():
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clusters = cluster_objects(
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char_group,
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"doctop" if upright else "x0",
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y_tolerance, # Still use y-tolerance here, even for vertical words
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)
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for line_chars in clusters:
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words += get_line_words(line_chars, upright, tolerance = x_tolerance)
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words = list(itertools.chain(*nested))
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return words
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def extract_text(chars,
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