Merge pull request #83 from RapidAI/optim_wired_logic_decode

fix: optim logic points decode

wired_table_rec/table_recover.py

@@ -66,57 +66,49 @@ def get_benchmark_cols(
     ) -> Tuple[np.ndarray, List[float], int]:
         longest_col = max(rows.values(), key=lambda x: len(x))
         longest_col_points = polygons[longest_col]
-        longest_x = longest_col_points[:, 0, 0]
-
+        longest_x_start = list(longest_col_points[:, 0, 0])
+        longest_x_end = list(longest_col_points[:, 2, 0])
+        min_x = longest_x_start[0]
+        max_x = longest_x_end[-1]
         theta = 15
-        for row_value in rows.values():
-            cur_row = polygons[row_value][:, 0, 0]
-
-            range_res = {}
-            for idx, cur_v in enumerate(cur_row):
-                start_idx, end_idx = None, None
-                for i, v in enumerate(longest_x):
-                    if cur_v - theta <= v <= cur_v + theta:
-                        break
 
-                    if cur_v > v:
-                        start_idx = i
-                        continue
+        # 根据当前col的起始x坐标，更新col的边界
+        def update_longest_col(col_x_list, cur_v, min_x_, max_x_):
+            for i, v in enumerate(col_x_list):
+                if cur_v - theta <= v <= cur_v + theta:
+                    break
+                if cur_v > v:
+                    continue
+                if cur_v < min_x_:
+                    col_x_list.insert(0, cur_v)
+                    min_x_ = cur_v
+                    break
+                if cur_v > max_x_:
+                    col_x_list.append(max_x_)
+                    max_x_ = cur_v
+                if cur_v < v:
+                    col_x_list.insert(i, cur_v)
+                    break
+            return min_x_, max_x_
 
-                    if cur_v < v:
-                        end_idx = i
-                        break
+        for row_value in rows.values():
+            cur_row_start = list(polygons[row_value][:, 0, 0])
+            cur_row_end = list(polygons[row_value][:, 2, 0])
+            for idx, (cur_v_start, cur_v_end) in enumerate(
+                zip(cur_row_start, cur_row_end)
+            ):
+                min_x, max_x = update_longest_col(
+                    longest_x_start, cur_v_start, min_x, max_x
+                )
+                min_x, max_x = update_longest_col(
+                    longest_x_start, cur_v_end, min_x, max_x
+                )
 
-                range_res[idx] = [start_idx, end_idx]
-
-            sorted_res = dict(
-                sorted(range_res.items(), key=lambda x: x[0], reverse=True)
-            )
-            for k, v in sorted_res.items():
-                # bugfix: https://github.com/RapidAI/TableStructureRec/discussions/55
-                # 最长列不包含第一列和最后一列的场景需要兼容
-                if all(v) or v[1] == 0:
-                    longest_x = np.insert(longest_x, v[1], cur_row[k])
-                    longest_col_points = np.insert(
-                        longest_col_points, v[1], polygons[row_value[k]], axis=0
-                    )
-                elif v[0] and v[0] + 1 == len(longest_x):
-                    longest_x = np.append(longest_x, cur_row[k])
-                    longest_col_points = np.append(
-                        longest_col_points,
-                        polygons[row_value[k]][np.newaxis, :, :],
-                        axis=0,
-                    )
-        # 求出最右侧所有cell的宽，其中最小的作为最后一列宽度
-        rightmost_idxs = [v[-1] for v in rows.values()]
-        rightmost_boxes = polygons[rightmost_idxs]
-        min_width = min([self.compute_L2(v[3, :], v[0, :]) for v in rightmost_boxes])
-
-        each_col_widths = (longest_x[1:] - longest_x[:-1]).tolist()
-        each_col_widths.append(min_width)
-
-        col_nums = longest_x.shape[0]
-        return longest_col_points, each_col_widths, col_nums
+        longest_x_start = np.array(longest_x_start)
+        each_col_widths = (longest_x_start[1:] - longest_x_start[:-1]).tolist()
+        each_col_widths.append(max_x - longest_x_start[-1])
+        col_nums = longest_x_start.shape[0]
+        return longest_x_start, each_col_widths, col_nums
 
     def get_benchmark_rows(
         self, rows: Dict[int, List], polygons: np.ndarray
@@ -160,7 +152,7 @@ def get_merge_cells(
                 box_width = self.compute_L2(box[3, :], box[0, :])
 
                 # 不一定是从0开始的，应该综合已有值和x坐标位置来确定起始位置
-                loc_col_idx = np.argmin(np.abs(longest_col[:, 0, 0] - box[0, 0]))
+                loc_col_idx = np.argmin(np.abs(longest_col - box[0, 0]))
                 col_start = max(sum(one_col_result.values()), loc_col_idx)
 
                 # 计算合并多少个列方向单元格