fix: 修复ROI切片y_offset丢失导致地址拼接失败的问题

resize步骤未传递y_offset，导致OCR worker无法还原切片坐标，
跨切片的地址行（如"楼3号"）无法与前一行正确拼接。
同时重写extract_with_layout为锚点算法（邮编/电话锚点+单栏/多栏自动切换），
支持单位名含地址关键字、电话同行等场景。

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

scripts/test_extract_info.py

@@ -80,10 +80,81 @@ def case_text_fallback() -> None:
     assert "华南建设小组办公室" in result["联系人/单位名"] or result["联系人/单位名"] == "王五"
 
 
+def case_company_contact_with_phone() -> None:
+    """单位名含地址关键字 + 电话同行，地址跨两行。"""
+    ocr_lines = [
+        {"text": "610000", "box": [[80, 40], [180, 40], [180, 80], [80, 80]], "source": "main"},
+        {"text": "四川省成都市蒲江县鹤山街道", "box": [[80, 100], [520, 100], [520, 132], [80, 132]], "source": "main"},
+        {"text": "健民路246号2栋1楼3号", "box": [[80, 140], [460, 140], [460, 172], [80, 172]], "source": "main"},
+        {"text": "蒲江县宏利物流有限公司 15680801653", "box": [[80, 180], [560, 180], [560, 212], [80, 212]], "source": "main"},
+        {"text": "20260200425708", "box": [[280, 60], [760, 60], [760, 94], [280, 94]], "source": "number"},
+    ]
+    result = extract_info(ocr_lines)
+    _print_case("单位名+电话同行（带坐标）", result)
+
+    assert result["邮编"] == "610000"
+    assert result["电话"] == "15680801653"
+    assert "四川省成都市蒲江县鹤山街道" in result["地址"]
+    assert "健民路246号2栋1楼3号" in result["地址"]
+    assert "蒲江县宏利物流有限公司" not in result["地址"], f"单位名不应混入地址: {result['地址']}"
+    assert "宏利物流" in result["联系人/单位名"], f"联系人应含单位名: {result['联系人/单位名']}"
+    assert result["编号"] == "20260200425708"
+
+
+def case_company_contact_separate_line() -> None:
+    """单位名和电话分两行（无坐标回退）。"""
+    ocr_texts = [
+        "610000",
+        "四川省成都市蒲江县鹤山街道",
+        "健民路246号2栋1楼3号",
+        "蒲江县宏利物流有限公司",
+        "15680801653",
+    ]
+    result = extract_info(ocr_texts)
+    _print_case("单位名+电话分行（纯文本）", result)
+
+    assert result["邮编"] == "610000"
+    assert result["电话"] == "15680801653"
+    assert "四川省成都市蒲江县鹤山街道" in result["地址"]
+    assert "健民路246号2栋1楼3号" in result["地址"]
+    assert "宏利物流" in result["联系人/单位名"], f"联系人应含单位名: {result['联系人/单位名']}"
+
+
+def case_split_roi_address() -> None:
+    """模拟 ROI 切片后坐标已偏移还原的场景：地址跨两个切片。
+
+    切片1 (y_offset=0): 邮编 + 地址第一行
+    切片2 (y_offset=200): 地址第二行 + 联系人+电话
+    坐标已在 worker 中加上 y_offset，此处直接传最终坐标。
+    """
+    ocr_lines = [
+        # 切片1 的结果（y_offset=0，坐标不变）
+        {"text": "610000", "box": [[80, 30], [180, 30], [180, 60], [80, 60]], "source": "main"},
+        {"text": "四川省成都市蒲江县鹤山街道健民路246号2栋1", "box": [[80, 80], [560, 80], [560, 112], [80, 112]], "source": "main"},
+        # 切片2 的结果（原始 y 约 10~42，加上 y_offset=200 后变成 210~242）
+        {"text": "楼3号", "box": [[80, 210], [160, 210], [160, 242], [80, 242]], "source": "main"},
+        {"text": "蒲江县宏利物流有限公司 15680801653", "box": [[80, 260], [560, 260], [560, 292], [80, 292]], "source": "main"},
+        # 编号区域
+        {"text": "20260200425708", "box": [[280, 400], [760, 400], [760, 434], [280, 434]], "source": "number"},
+    ]
+    result = extract_info(ocr_lines)
+    _print_case("ROI切片坐标还原", result)
+
+    assert result["邮编"] == "610000"
+    assert result["电话"] == "15680801653"
+    # 关键：地址两行应正确拼接
+    assert "健民路246号2栋1" in result["地址"], f"地址应含第一行: {result['地址']}"
+    assert "楼3号" in result["地址"], f"地址应含第二行: {result['地址']}"
+    assert "宏利物流" in result["联系人/单位名"], f"联系人应含单位名: {result['联系人/单位名']}"
+
+
 def main() -> None:
     case_layout_multi_column()
     case_layout_single_column()
     case_text_fallback()
+    case_company_contact_with_phone()
+    case_company_contact_separate_line()
+    case_split_roi_address()
     print("\n所有场景断言通过。")
 
 

src/desktop.py

@@ -540,6 +540,9 @@ class MainWindow(QMainWindow):
         if job_id != self._ocr_job_id:
             return
 
+        logger.info("OCR job=%s 原始文本: %s", job_id, texts)
+        logger.info("OCR job=%s 解析结果: %s", job_id, record)
+
         self.records.append(record)
         self.update_table()
         cost = ""
@@ -996,7 +999,7 @@ class MainWindow(QMainWindow):
                     split_count = min(split_count, 4)
 
                     if split_count <= 1 or roi_box.shape[0] < 120:
-                        roi_inputs.append({"img": roi_box, "source": "main"})
+                        roi_inputs.append({"img": roi_box, "source": "main", "y_offset": 0})
                     else:
                         h_box = roi_box.shape[0]
                         step = h_box / float(split_count)
@@ -1012,7 +1015,7 @@ class MainWindow(QMainWindow):
                             )
                             part = roi_box[sy:ey, :]
                             if part is not None and part.size > 0:
-                                roi_inputs.append({"img": part, "source": "main"})
+                                roi_inputs.append({"img": part, "source": "main", "y_offset": sy})
             except Exception:
                 pass
 
@@ -1043,13 +1046,15 @@ class MainWindow(QMainWindow):
             for item in roi_inputs:
                 img = item.get("img")
                 source = item.get("source", "main")
+                y_off = item.get("y_offset", 0)
+                scale = 1.0
                 try:
                     if img is not None and img.shape[1] > max_w:
                         scale = max_w / img.shape[1]
                         img = cv2.resize(img, (int(img.shape[1] * scale), int(img.shape[0] * scale)))
                 except Exception:
                     pass
-                resized_inputs.append({"img": img, "source": source})
+                resized_inputs.append({"img": img, "source": source, "y_offset": int(y_off * scale)})
 
             logger.info(
                 "UI 触发识别：frame=%s, rois=%s, frame_age=%.3fs",

src/ocr_worker_process.py

@@ -48,9 +48,11 @@ def run_ocr_worker(models_base_dir: str, request_q, response_q) -> None:
             for roi_index, entry in enumerate(images):
                 source = "main"
                 img = entry
+                y_offset = 0
                 if isinstance(entry, dict):
                     source = str(entry.get("source", "main"))
                     img = entry.get("img")
+                    y_offset = int(entry.get("y_offset", 0))
                 elif roi_index > 0:
                     source = "number"
                 if img is None:
@@ -68,10 +70,14 @@ def run_ocr_worker(models_base_dir: str, request_q, response_q) -> None:
                                 conf = float(line[1][1])
                             except Exception:
                                 conf = None
+                            # 将切片内的局部坐标还原为完整 ROI 坐标
+                            box = line[0]
+                            if y_offset and isinstance(box, (list, tuple)):
+                                box = [[p[0], p[1] + y_offset] for p in box]
                             ocr_lines.append(
                                 {
                                     "text": text,
-                                    "box": line[0],
+                                    "box": box,
                                     "conf": conf,
                                     "source": source,
                                     "roi_index": roi_index,

src/processor.py

@@ -11,6 +11,10 @@ ZIP_PATTERN = re.compile(r"(?<!\d)(\d{6})(?!\d)")
 PHONE_PATTERN = re.compile(r"(?<!\d)(1[3-9]\d{9}|0\d{2,3}-?\d{7,8})(?!\d)")
 LONG_NUMBER_PATTERN = re.compile(r"(?<!\d)(\d{10,20})(?!\d)")
 ADDRESS_HINT_PATTERN = re.compile(r"(省|市|区|县|乡|镇|街|路|村|号|栋|单元|室)")
+COMPANY_HINT_PATTERN = re.compile(
+    r"(公司|有限|集团|工厂|物流|商贸|商行|超市|药房|药店|诊所|医院|学校|幼儿园"
+    r"|办公室|办事处|服务部|经营部|工作室|研究所|事务所|中心|银行|信用社|合作社)"
+)
 
 
 @dataclass
@@ -247,6 +251,15 @@ def _extract_tracking_number(lines: List[OCRLine], zip_code: str, phone: str) ->
 
 
 def _extract_with_layout(lines: List[OCRLine], data: Dict[str, str]) -> Tuple[str, str, bool]:
+    """基于邮编/电话锚点的版面提取。
+
+    两种模式自动切换：
+    - 单栏模式（信封典型排版）：邮编后连续行=地址，电话行去掉电话=联系人
+    - 多栏模式：左侧=地址，右侧=联系人（按 split_x 分割）
+
+    单栏/多栏判断：比较邮编和电话的左边缘（x1），而非中心点（cx），
+    避免因文本长度不同导致误判。
+    """
     main_lines = [line for line in lines if line.source != "number"]
     if len(main_lines) < 2:
         return "", "", False
@@ -262,6 +275,9 @@ def _extract_with_layout(lines: List[OCRLine], data: Dict[str, str]) -> Tuple[st
     if phone_anchor and not data["电话"]:
         data["电话"] = phone_anchor[1]
 
+    if not zip_anchor and not phone_anchor:
+        return "", "", False
+
     if zip_anchor:
         start_row = zip_anchor[0].row_idx
     else:
@@ -273,13 +289,62 @@ def _extract_with_layout(lines: List[OCRLine], data: Dict[str, str]) -> Tuple[st
     if start_row > end_row:
         start_row, end_row = end_row, start_row
 
+    # ── 单栏/多栏判断：用左边缘 x1 而非中心点 cx ──
     single_column_mode = False
     if zip_anchor and phone_anchor:
+        zip_x1 = zip_anchor[0].x1 if zip_anchor[0].x1 is not None else zip_anchor[0].cx
+        phone_x1 = phone_anchor[0].x1 if phone_anchor[0].x1 is not None else phone_anchor[0].cx
         line_widths = [line.width for line in main_lines if line.width > 0]
         width_ref = median(line_widths) if line_widths else 120.0
-        single_column_mode = abs(phone_anchor[0].cx - zip_anchor[0].cx) < max(60.0, width_ref * 0.6)
+        single_column_mode = abs(phone_x1 - zip_x1) < max(60.0, width_ref * 0.4)
 
-    if zip_anchor and phone_anchor and phone_anchor[0].cx > zip_anchor[0].cx and not single_column_mode:
+    # ════════════════════════════════════════════
+    # 单栏模式：邮编后连续行=地址，电话行去掉电话=联系人
+    # ════════════════════════════════════════════
+    if single_column_mode:
+        # 从电话行提取联系人
+        contact_text = ""
+        if phone_anchor:
+            remainder = clean_text(phone_anchor[0].text.replace(phone_anchor[1], ""))
+            if remainder and not re.fullmatch(r"\d{2,20}", remainder):
+                contact_text = _sanitize_contact(remainder)
+
+        # 邮编行之后、电话行之前的所有行 → 地址
+        address_entries: List[Tuple[int, int, str]] = []
+        for line in main_lines:
+            if line.row_idx < start_row or line.row_idx > end_row:
+                continue
+            if phone_anchor and line is phone_anchor[0]:
+                continue
+            text = line.text
+            if zip_anchor and line is zip_anchor[0]:
+                text = text.replace(zip_anchor[1], "")
+            text = clean_text(text)
+            if not text or re.fullmatch(r"\d{6,20}", text):
+                continue
+            address_entries.append((line.row_idx, line.col_idx, text))
+
+        # 联系人为空时，从地址末尾回退一行
+        if not contact_text and address_entries:
+            last_row = max(item[0] for item in address_entries)
+            last_entries = [item for item in address_entries if item[0] == last_row]
+            last_text = _join_entries(last_entries)
+            candidate = _sanitize_contact(last_text)
+            if candidate:
+                prev_rows = [item[0] for item in address_entries if item[0] < last_row]
+                # 与前面地址行有行间距 > 1，或含单位关键字 → 视为联系人
+                gap = (last_row - max(prev_rows)) if prev_rows else 999
+                if gap > 1 or COMPANY_HINT_PATTERN.search(last_text):
+                    contact_text = candidate
+                    address_entries = [item for item in address_entries if item[0] != last_row]
+
+        address_text = _sanitize_address(_join_entries(address_entries))
+        return address_text, contact_text, True
+
+    # ════════════════════════════════════════════
+    # 多栏模式：按 split_x 左右分割
+    # ════════════════════════════════════════════
+    if zip_anchor and phone_anchor and phone_anchor[0].cx > zip_anchor[0].cx:
         split_x = (zip_anchor[0].cx + phone_anchor[0].cx) / 2.0
     elif phone_anchor:
         split_x = phone_anchor[0].cx - max(40.0, phone_anchor[0].width * 0.6)
@@ -288,29 +353,19 @@ def _extract_with_layout(lines: List[OCRLine], data: Dict[str, str]) -> Tuple[st
     else:
         split_x = median([line.cx for line in main_lines])
 
-    address_entries: List[Tuple[int, int, str]] = []
+    address_entries = []
     contact_entries: List[Tuple[int, int, str]] = []
 
     for line in main_lines:
         if line.row_idx < start_row or line.row_idx > end_row:
             continue
-
         text = line.text
         if zip_anchor and line is zip_anchor[0]:
             text = text.replace(zip_anchor[1], "")
         if phone_anchor and line is phone_anchor[0]:
             text = text.replace(phone_anchor[1], "")
         text = clean_text(text)
-        if not text:
+        if not text or re.fullmatch(r"\d{6,20}", text):
-            continue
-        if re.fullmatch(r"\d{6,20}", text):
-            continue
-
-        if single_column_mode:
-            if phone_anchor and line is phone_anchor[0]:
-                contact_entries.append((line.row_idx, line.col_idx, text))
-            else:
-                address_entries.append((line.row_idx, line.col_idx, text))
             continue
 
         if line.cx <= split_x:
@@ -318,7 +373,7 @@ def _extract_with_layout(lines: List[OCRLine], data: Dict[str, str]) -> Tuple[st
         else:
             contact_entries.append((line.row_idx, line.col_idx, text))
 
-    # 联系人优先取靠近电话的一段，降低把地址误分到联系人的概率
+    # 联系人优先取靠近电话的一段
     if phone_anchor and contact_entries:
         phone_row = phone_anchor[0].row_idx
         min_dist = min(abs(item[0] - phone_row) for item in contact_entries)
@@ -329,34 +384,13 @@ def _extract_with_layout(lines: List[OCRLine], data: Dict[str, str]) -> Tuple[st
     contact_text = _sanitize_contact(_join_entries(contact_entries))
     address_text = _sanitize_address(_join_entries(address_entries))
 
-    # 如果联系人仍为空，尝试从“电话所在行去掉电话号码”的残余文本提取
+    # 多栏模式下联系人为空的回退
     if not contact_text and phone_anchor:
-        fallback_contact = clean_text(phone_anchor[0].text.replace(phone_anchor[1], ""))
+        remainder = clean_text(phone_anchor[0].text.replace(phone_anchor[1], ""))
-        if fallback_contact and not re.fullmatch(r"\d{2,20}", fallback_contact):
+        if remainder and not re.fullmatch(r"\d{2,20}", remainder):
-            contact_text = _sanitize_contact(fallback_contact)
+            contact_text = _sanitize_contact(remainder)
 
-    # 若仍缺联系人，尝试从靠近电话的地址候选中回退一行
+    return address_text, contact_text, True
-    if not contact_text and phone_anchor and address_entries:
-        phone_row = phone_anchor[0].row_idx
-        sorted_candidates = sorted(
-            address_entries,
-            key=lambda item: (abs(item[0] - phone_row), -item[0], item[1]),
-        )
-        for row_idx, col_idx, txt in sorted_candidates:
-            if ADDRESS_HINT_PATTERN.search(txt):
-                continue
-            contact_text = _sanitize_contact(txt)
-            if contact_text:
-                address_entries = [
-                    item
-                    for item in address_entries
-                    if not (item[0] == row_idx and item[1] == col_idx and item[2] == txt)
-                ]
-                address_text = _sanitize_address(_join_entries(address_entries))
-                break
-
-    has_signal = bool(zip_anchor or phone_anchor)
-    return address_text, contact_text, has_signal
 
 
 def _extract_with_text_order(lines: List[OCRLine], data: Dict[str, str]) -> Tuple[str, str, bool]:
@@ -407,13 +441,22 @@ def _extract_with_text_order(lines: List[OCRLine], data: Dict[str, str]) -> Tupl
 
     if not contact_text and address_parts:
         for idx, text in reversed(address_parts):
-            if ADDRESS_HINT_PATTERN.search(text):
+            # 含单位关键字的直接采纳；纯地址行跳过
+            if ADDRESS_HINT_PATTERN.search(text) and not COMPANY_HINT_PATTERN.search(text):
                 continue
             contact_text = _sanitize_contact(text)
             if contact_text:
                 address_parts = [item for item in address_parts if item[0] != idx]
                 break
 
+    # 兜底：电话紧邻上一行即使含地址关键字也采纳（如"蒲江县宏利物流有限公司"）
+    if not contact_text and address_parts:
+        last_idx, last_text = address_parts[-1]
+        if last_idx == phone_idx - 1:
+            contact_text = _sanitize_contact(last_text)
+            if contact_text:
+                address_parts = address_parts[:-1]
+
     address_text = _sanitize_address("".join(text for _, text in address_parts))
     return address_text, contact_text, True
 
@@ -436,7 +479,7 @@ def extract_info(ocr_results: List[Any]) -> Dict[str, str]:
     data["电话"] = _first_match(PHONE_PATTERN, full_content)
     data["编号"] = _extract_tracking_number(lines, data["邮编"], data["电话"])
 
-    # 第一优先级：使用版面坐标进行“邮编-电话锚点 + 连续块”解析
+    # 第一优先级：使用版面坐标进行"邮编-电话锚点 + 连续块"解析
     address_text, contact_text, used_layout = _extract_with_layout(lines, data)
     if not used_layout:
         # 第二优先级：无坐标时按文本顺序回退