Class: Rpdfium::Util::LabelMatcher

Inherits:
Object
  • Object
show all
Defined in:
lib/rpdfium/util/label_matcher.rb

Overview

Associa label semantiche a valori inseriti su PDF di moduli compilati (F24, comunicazioni IVA, modelli 770) dove template e dati coesistono come testo grafico in font diversi.

Strategia base:

  1. Cluster le parole del template in “label coerenti”: word geometricamente vicine formano un’unica label.

  2. **Per ogni valore** cerca:

    • ‘:col` — label SOPRA in stessa colonna

    • ‘:row` — label A SINISTRA in stessa riga

  3. (Opzionale) **Riassegnazione per colonne**: usa ‘ColumnInference` per identificare colonne ripetitive (es. ST2..ST13 del 770 Quadro ST) e propaga l’header canonico a tutti i valori della colonna, superando il limite ‘col_max_dy`.

Examples:

uso base

matcher = Rpdfium::Util::LabelMatcher.new
matcher.match(value_words, anchor_words)

con tabelle ripetitive (header in cima alla colonna)

matcher = Rpdfium::Util::LabelMatcher.new(
  column_inference: Rpdfium::Util::ColumnInference.new
)
matcher.match(value_words, anchor_words)

Constant Summary collapse

DEFAULT_COL_MAX_DY = 
80.0
DEFAULT_ROW_MAX_DX = 
200.0
DEFAULT_COL_X_TOLERANCE = 
10.0
DEFAULT_ROW_Y_TOLERANCE = 
2.0
DEFAULT_CLUSTER_SAME_ROW_DY = 
4.0
DEFAULT_CLUSTER_SAME_ROW_DX = 
12.0
DEFAULT_CLUSTER_ADJ_ROW_DY = 
4.0
DEFAULT_IGNORE_LABEL_PATTERN = 
/\A\d{1,3}\z|\A[IVX]{1,5}\z/.freeze
WIDE_VALUE_THRESHOLD = 
60.0

Instance Method Summary collapse

Constructor Details

#initialize(col_max_dy: DEFAULT_COL_MAX_DY, row_max_dx: DEFAULT_ROW_MAX_DX, col_x_tolerance: DEFAULT_COL_X_TOLERANCE, row_y_tolerance: DEFAULT_ROW_Y_TOLERANCE, cluster_same_row_dy: DEFAULT_CLUSTER_SAME_ROW_DY, cluster_same_row_dx: DEFAULT_CLUSTER_SAME_ROW_DX, cluster_adj_row_dy: DEFAULT_CLUSTER_ADJ_ROW_DY, ignore_label_pattern: DEFAULT_IGNORE_LABEL_PATTERN, column_inference: nil) ⇒ LabelMatcher

Returns a new instance of LabelMatcher.



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# File 'lib/rpdfium/util/label_matcher.rb', line 43

def initialize(col_max_dy: DEFAULT_COL_MAX_DY,
               row_max_dx: DEFAULT_ROW_MAX_DX,
               col_x_tolerance: DEFAULT_COL_X_TOLERANCE,
               row_y_tolerance: DEFAULT_ROW_Y_TOLERANCE,
               cluster_same_row_dy: DEFAULT_CLUSTER_SAME_ROW_DY,
               cluster_same_row_dx: DEFAULT_CLUSTER_SAME_ROW_DX,
               cluster_adj_row_dy: DEFAULT_CLUSTER_ADJ_ROW_DY,
               ignore_label_pattern: DEFAULT_IGNORE_LABEL_PATTERN,
               column_inference: nil)
  @col_max_dy = col_max_dy
  @row_max_dx = row_max_dx
  @col_x_tolerance = col_x_tolerance
  @row_y_tolerance = row_y_tolerance
  @cluster_same_row_dy = cluster_same_row_dy
  @cluster_same_row_dx = cluster_same_row_dx
  @cluster_adj_row_dy = cluster_adj_row_dy
  @ignore_label_pattern = ignore_label_pattern
  @column_inference = column_inference
end

Instance Method Details

#cluster_anchors(anchor_words) ⇒ Object

Ricostruisce le label dal cluster delle word del template. Esposto pubblicamente per ispezione/debug.



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# File 'lib/rpdfium/util/label_matcher.rb', line 97

def cluster_anchors(anchor_words)
  remaining = anchor_words.dup
  groups = []
  until remaining.empty?
    seed = remaining.shift
    group = [seed]
    grew = true
    while grew
      grew = false
      remaining.dup.each do |w|
        close = group.any? do |g|
          dx_horiz = [w[:x0] - g[:x1], g[:x0] - w[:x1]].max
          same_row = (w[:top] - g[:top]).abs < @cluster_same_row_dy &&
                     dx_horiz < @cluster_same_row_dx
          dy_above = (g[:top] - w[:bottom]).abs
          dy_below = (w[:top] - g[:bottom]).abs
          vertical_adjacent = [dy_above, dy_below].min < @cluster_adj_row_dy
          x_overlap = !(w[:x1] < g[:x0] - 3 || w[:x0] > g[:x1] + 3)
          adj_row = vertical_adjacent && x_overlap
          same_row || adj_row
        end
        if close
          group << w
          remaining.delete(w)
          grew = true
        end
      end
    end
    groups << group
  end
  labels = groups.map { |g| group_to_label(g) }
  if @ignore_label_pattern
    labels = labels.reject { |l| l[:text].match?(@ignore_label_pattern) }
  end
  labels
end

#match(values, anchors) ⇒ Array<Hash>

Calcola le associazioni label → valore.

Parameters:

  • values (Array<Hash>) —

    word del layer “dati”

  • anchors (Array<Hash>) —

    word del layer “template”

Returns:

  • (Array<Hash>) —

    uno per valore: { value:, labels: { col:, row: }, geometry: }



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# File 'lib/rpdfium/util/label_matcher.rb', line 68

def match(values, anchors)
  labels = cluster_anchors(anchors)

  prelim = values.map do |v|
    col = find_col_label(v, labels)
    row = find_row_label(v, labels)
    { value: v, col: col, row: row }
  end

  # Riassegnazione opzionale per colonne ripetitive
  prelim = reassign_by_columns(prelim, labels, values) if @column_inference

  prelim.map do |entry|
    v = entry[:value]
    {
      value: v[:text],
      labels: {
        col: entry[:col]&.dig(:text),
        row: entry[:row]&.dig(:text)
      },
      geometry: {
        x0: v[:x0], x1: v[:x1], top: v[:top], bottom: v[:bottom]
      }
    }
  end
end