feat: add use_preprocess_img and use_vertical_padding logic

python/rapidocr/config.yaml

@@ -9,7 +9,7 @@ Global:
     min_side_len: 30
     max_side_len: 2000
 
-    use_apply_vertical_padding: true
+    use_vertical_padding: true
     min_height: 30
     width_height_ratio: 8
 

python/rapidocr/main.py

@@ -279,21 +279,26 @@ class RapidOCR:
             setattr(obj, path[-1], value)
 
     def preprocess_img(self, ori_img: np.ndarray) -> Tuple[np.ndarray, Dict[str, Any]]:
-        op_record = {}
+        if not self.cfg.Global.use_preprocess_img:
+            return ori_img, {"preprocess": {"ratio_h": 1.0, "ratio_w": 1.0}}
+
         img, ratio_h, ratio_w = resize_image_within_bounds(
             ori_img, self.min_side_len, self.max_side_len
         )
-        op_record["preprocess"] = {"ratio_h": ratio_h, "ratio_w": ratio_w}
+        op_record = {"preprocess": {"ratio_h": ratio_h, "ratio_w": ratio_w}}
         return img, op_record
 
     def detect_and_crop(
         self, img: np.ndarray, op_record: Dict[str, Any]
     ) -> Tuple[List[np.ndarray], TextDetOutput]:
-        img, op_record = apply_vertical_padding(
-            img, op_record, self.width_height_ratio, self.min_height
-        )
-        det_res = self.text_det(img)
+        if self.cfg.Global.use_vertical_padding:
+            img, op_record = apply_vertical_padding(
+                img, op_record, self.width_height_ratio, self.min_height
+            )
+        else:
+            op_record["padding_1"] = {"top": 0, "left": 0}
 
+        det_res = self.text_det(img)
         if det_res.boxes is None:
             raise RapidOCRError("The text detection result is empty")
 

python/tests/test_image_preprocessing.py

@@ -0,0 +1,57 @@
+# -*- encoding: utf-8 -*-
+# @Author: SWHL
+# @Contact: liekkaskono@163.com
+from types import SimpleNamespace
+
+import numpy as np
+
+import rapidocr.main as main_module
+from rapidocr import RapidOCR
+from rapidocr.ch_ppocr_det import TextDetOutput
+
+
+def test_preprocess_img_returns_original_when_disabled(monkeypatch):
+    engine = RapidOCR.__new__(RapidOCR)
+    engine.cfg = SimpleNamespace(
+        Global=SimpleNamespace(use_preprocess_img=False)
+    )
+    ori_img = np.zeros((20, 40, 3), dtype=np.uint8)
+
+    def fail_if_called(*args, **kwargs):
+        raise AssertionError("resize_image_within_bounds should not be called")
+
+    monkeypatch.setattr(main_module, "resize_image_within_bounds", fail_if_called)
+
+    img, op_record = engine.preprocess_img(ori_img)
+
+    assert img is ori_img
+    assert op_record == {"preprocess": {"ratio_h": 1.0, "ratio_w": 1.0}}
+
+
+def test_detect_and_crop_skips_vertical_padding_when_disabled(monkeypatch):
+    engine = RapidOCR.__new__(RapidOCR)
+    engine.cfg = SimpleNamespace(
+        Global=SimpleNamespace(use_vertical_padding=False)
+    )
+    img = np.zeros((20, 40, 3), dtype=np.uint8)
+    boxes = np.array([[[0, 0], [10, 0], [10, 10], [0, 10]]], dtype=np.float32)
+    detected_images = []
+
+    def fail_if_called(*args, **kwargs):
+        raise AssertionError("apply_vertical_padding should not be called")
+
+    def text_det(det_img):
+        detected_images.append(det_img)
+        return TextDetOutput(boxes=boxes)
+
+    monkeypatch.setattr(main_module, "apply_vertical_padding", fail_if_called)
+    engine.text_det = text_det
+    engine.crop_text_regions = lambda crop_img, det_boxes: [crop_img]
+    op_record = {}
+
+    cropped_imgs, det_res = engine.detect_and_crop(img, op_record)
+
+    assert detected_images[0] is img
+    assert cropped_imgs[0] is img
+    assert det_res.boxes is boxes
+    assert op_record["padding_1"] == {"top": 0, "left": 0}