预处理后的图片，坐标可能是这张图的坐标，而且还原不回去

main.py

@@ -2,7 +2,7 @@
 # see huggingface/project/flask_auto_selection.py
 
 # C:\Users\echod\.paddlex\official_models\PP-OCRv5_server_det
-# c:\Users\echod\.conda\envs\ppv5\lib\site-packages\paddle\utils\cpp_extension\extension_utils.py 看标型加载的代码在哪
+# c:\Users\echod\.conda\envs\ppv5\lib\site-packages\paddle\utils\cpp_extension\extension_utils.py 看模型加载的代码在哪
 
 """
 
@@ -102,6 +102,7 @@ def ppresult_tojson(img, result):
 
     for res in result:
         output_img = res['doc_preprocessor_res']['output_img']  # 这是预处理后的图片，坐标可能是这张图的坐标，而且还原不回去
+        # img = output_img 
         jsn = res.json['res']
         text_word = jsn['text_word']
         text_word_boxes = jsn['text_word_boxes']
@@ -129,9 +130,9 @@ def ppresult_tojson(img, result):
 
             img = cv2.rectangle(img, (lu['x'], lu['y']), (rd['x'], rd['y']), (255, 0, 0), 2)
             if platform.system() == "Windows":
-                # if is_debug:
-                #     cv2.imshow('orig', img)
-                #     cv2.waitKey(0)
+                if is_debug:
+                    cv2.imshow('orig', img)
+                    cv2.waitKey(0)
                 pass
             for idx_word, (word, box) in enumerate(zip(words, boxs)):
 
@@ -156,9 +157,9 @@ def ppresult_tojson(img, result):
                 # print(word)
                 img = cv2.rectangle(img, (box[0], box[1]), (box[2], box[3]), (0, 255, 0), 2)  # 矩形的左上角, 矩形的右下角
                 if platform.system() == "Windows":
-                    # if is_debug:
-                    #     cv2.imshow('orgin', img)
-                    #     cv2.waitKey(0)
+                    if is_debug:
+                        cv2.imshow('orgin', img)
+                        cv2.waitKey(0)
                     pass
 
         # save_json('out.json', jn)
@@ -209,7 +210,7 @@ def autoselection():
 if __name__ == '__main__':
 
     if is_debug:
-        pth_img = "data/0170.jpg" # "data/第一单元.jpg"
+        pth_img = "data/0025.jpg" # "data/第一单元.jpg"
 
         imgData = np.fromfile(pth_img, dtype=np.uint8)
         img = cv2.imdecode(imgData, cv2.IMREAD_COLOR_BGR)