fix det xyxy (#4037)

* fix det xyxy

* fix new layout

docs/module_usage/tutorials/ocr_modules/layout_detection.en.md

@@ -292,7 +292,7 @@ After installing the wheel package, a few lines of code can complete the inferen
 ```python
 from paddlex import create_model
 
-model_name = "PP-DocLayout-L"
+model_name = "PP-DocLayout_plus-L"
 model = create_model(model_name=model_name)
 output = model.predict("layout.jpg", batch_size=1, layout_nms=True)
 
@@ -306,7 +306,7 @@ for res in output:
 <details><summary>👉 <b>After running, the result is: (Click to expand)</b></summary>
 
 ```bash
-{'res': {'input_path': 'layout.jpg', 'page_index': None, 'boxes': [{'cls_id': 8, 'label': 'table', 'score': 0.9866330623626709, 'coordinate': [74.30875, 105.7123, 321.98837, 299.10858]}, {'cls_id': 2, 'label': 'text', 'score': 0.9859815835952759, 'coordinate': [34.658115, 349.9102, 358.33835, 611.34314]}, {'cls_id': 2, 'label': 'text', 'score': 0.9850621223449707, 'coordinate': [34.944622, 647.37946, 358.3256, 849.2333]}, {'cls_id': 8, 'label': 'table', 'score': 0.9850116968154907, 'coordinate': [438.0683, 105.377174, 662.8872, 313.88733]}, {'cls_id': 2, 'label': 'text', 'score': 0.9847850799560547, 'coordinate': [385.97052, 497.03925, 710.9549, 697.6805]}, {'cls_id': 2, 'label': 'text', 'score': 0.9805687665939331, 'coordinate': [385.79697, 345.93753, 710.07336, 459.14374]}, {'cls_id': 2, 'label': 'text', 'score': 0.9799897074699402, 'coordinate': [386.07574, 735.3798, 710.60785, 850.2002]}, {'cls_id': 9, 'label': 'table_title', 'score': 0.9375936388969421, 'coordinate': [35.273827, 19.851961, 358.92508, 77.812584]}, {'cls_id': 0, 'label': 'paragraph_title', 'score': 0.8755733966827393, 'coordinate': [386.63184, 476.60715, 699.78345, 490.1164]}, {'cls_id': 0, 'label': 'paragraph_title', 'score': 0.8617452383041382, 'coordinate': [387.27448, 715.95795, 524.38367, 729.20795]}, {'cls_id': 0, 'label': 'paragraph_title', 'score': 0.8607752919197083, 'coordinate': [35.451626, 627.496, 185.63443, 640.4029]}, {'cls_id': 0, 'label': 'paragraph_title', 'score': 0.8575425148010254, 'coordinate': [35.33491, 330.8047, 141.46854, 344.4073]}, {'cls_id': 9, 'label': 'table_title', 'score': 0.7957680225372314, 'coordinate': [385.9386, 19.754547, 711.51184, 75.00631]}]}}
+{'res': {'input_path': 'layout.jpg', 'page_index': None, 'boxes': [{'cls_id': 2, 'label': 'text', 'score': 0.9870226979255676, 'coordinate': [34.101906, 349.85275, 358.59213, 611.0772]}, {'cls_id': 2, 'label': 'text', 'score': 0.9866003394126892, 'coordinate': [34.500324, 647.1585, 358.29367, 848.66797]}, {'cls_id': 2, 'label': 'text', 'score': 0.9846674203872681, 'coordinate': [385.71445, 497.40973, 711.2261, 697.84265]}, {'cls_id': 8, 'label': 'table', 'score': 0.984126091003418, 'coordinate': [73.76879, 105.94899, 321.95303, 298.84888]}, {'cls_id': 8, 'label': 'table', 'score': 0.9834211468696594, 'coordinate': [436.95642, 105.81531, 662.7168, 313.48462]}, {'cls_id': 2, 'label': 'text', 'score': 0.9832247495651245, 'coordinate': [385.62787, 346.2288, 710.10095, 458.77127]}, {'cls_id': 2, 'label': 'text', 'score': 0.9816061854362488, 'coordinate': [385.7802, 735.1931, 710.56134, 849.9764]}, {'cls_id': 6, 'label': 'figure_title', 'score': 0.9577341079711914, 'coordinate': [34.421448, 20.055151, 358.71283, 76.53663]}, {'cls_id': 6, 'label': 'figure_title', 'score': 0.9505634307861328, 'coordinate': [385.72278, 20.053688, 711.29333, 74.92744]}, {'cls_id': 0, 'label': 'paragraph_title', 'score': 0.9001723527908325, 'coordinate': [386.46344, 477.03488, 699.4023, 490.07474]}, {'cls_id': 0, 'label': 'paragraph_title', 'score': 0.8845751285552979, 'coordinate': [35.413048, 627.73596, 185.58383, 640.52264]}, {'cls_id': 0, 'label': 'paragraph_title', 'score': 0.8837394118309021, 'coordinate': [387.17603, 716.3423, 524.7841, 729.258]}, {'cls_id': 0, 'label': 'paragraph_title', 'score': 0.8508939743041992, 'coordinate': [35.50064, 331.18445, 141.6444, 344.81097]}]}}
 ```
 The meanings of the parameters are as follows:
 - `input_path`: The path to the input image for prediction.
@@ -320,11 +320,11 @@ The meanings of the parameters are as follows:
 </details>
 
 The visualized image is as follows:
-<img src="https://raw.githubusercontent.com/cuicheng01/PaddleX_doc_images/refs/heads/main/images/modules/layout_det/layout_res.jpg"/>
+<img src="https://raw.githubusercontent.com/cuicheng01/PaddleX_doc_images/refs/heads/main/images/modules/layout_det/layout_res_plus.jpg"/>
 
 Relevant methods, parameters, and explanations are as follows:
 
-* `create_model` instantiates a target detection model (here, `PP-DocLayout-L` is used as an example). The detailed explanation is as follows:
+* `create_model` instantiates a target detection model (here, `PP-DocLayout_plus-L` is used as an example). The detailed explanation is as follows:
 <table>
 <thead>
 <tr>

docs/module_usage/tutorials/ocr_modules/layout_detection.md

@@ -295,7 +295,7 @@ comments: true
 ```python
 from paddlex import create_model
 
-model_name = "PP-DocLayout-L"
+model_name = "PP-DocLayout_plus-L"
 model = create_model(model_name=model_name)
 output = model.predict("layout.jpg", batch_size=1, layout_nms=True)
 
@@ -309,7 +309,7 @@ for res in output:
 <details><summary>👉 <b>运行后，得到的结果为：（点击展开）</b></summary>
 
 ```bash
-{'res': {'input_path': 'layout.jpg', 'page_index': None, 'boxes': [{'cls_id': 8, 'label': 'table', 'score': 0.9866330623626709, 'coordinate': [74.30875, 105.7123, 321.98837, 299.10858]}, {'cls_id': 2, 'label': 'text', 'score': 0.9859815835952759, 'coordinate': [34.658115, 349.9102, 358.33835, 611.34314]}, {'cls_id': 2, 'label': 'text', 'score': 0.9850621223449707, 'coordinate': [34.944622, 647.37946, 358.3256, 849.2333]}, {'cls_id': 8, 'label': 'table', 'score': 0.9850116968154907, 'coordinate': [438.0683, 105.377174, 662.8872, 313.88733]}, {'cls_id': 2, 'label': 'text', 'score': 0.9847850799560547, 'coordinate': [385.97052, 497.03925, 710.9549, 697.6805]}, {'cls_id': 2, 'label': 'text', 'score': 0.9805687665939331, 'coordinate': [385.79697, 345.93753, 710.07336, 459.14374]}, {'cls_id': 2, 'label': 'text', 'score': 0.9799897074699402, 'coordinate': [386.07574, 735.3798, 710.60785, 850.2002]}, {'cls_id': 9, 'label': 'table_title', 'score': 0.9375936388969421, 'coordinate': [35.273827, 19.851961, 358.92508, 77.812584]}, {'cls_id': 0, 'label': 'paragraph_title', 'score': 0.8755733966827393, 'coordinate': [386.63184, 476.60715, 699.78345, 490.1164]}, {'cls_id': 0, 'label': 'paragraph_title', 'score': 0.8617452383041382, 'coordinate': [387.27448, 715.95795, 524.38367, 729.20795]}, {'cls_id': 0, 'label': 'paragraph_title', 'score': 0.8607752919197083, 'coordinate': [35.451626, 627.496, 185.63443, 640.4029]}, {'cls_id': 0, 'label': 'paragraph_title', 'score': 0.8575425148010254, 'coordinate': [35.33491, 330.8047, 141.46854, 344.4073]}, {'cls_id': 9, 'label': 'table_title', 'score': 0.7957680225372314, 'coordinate': [385.9386, 19.754547, 711.51184, 75.00631]}]}}
+{'res': {'input_path': 'layout.jpg', 'page_index': None, 'boxes': [{'cls_id': 2, 'label': 'text', 'score': 0.9870226979255676, 'coordinate': [34.101906, 349.85275, 358.59213, 611.0772]}, {'cls_id': 2, 'label': 'text', 'score': 0.9866003394126892, 'coordinate': [34.500324, 647.1585, 358.29367, 848.66797]}, {'cls_id': 2, 'label': 'text', 'score': 0.9846674203872681, 'coordinate': [385.71445, 497.40973, 711.2261, 697.84265]}, {'cls_id': 8, 'label': 'table', 'score': 0.984126091003418, 'coordinate': [73.76879, 105.94899, 321.95303, 298.84888]}, {'cls_id': 8, 'label': 'table', 'score': 0.9834211468696594, 'coordinate': [436.95642, 105.81531, 662.7168, 313.48462]}, {'cls_id': 2, 'label': 'text', 'score': 0.9832247495651245, 'coordinate': [385.62787, 346.2288, 710.10095, 458.77127]}, {'cls_id': 2, 'label': 'text', 'score': 0.9816061854362488, 'coordinate': [385.7802, 735.1931, 710.56134, 849.9764]}, {'cls_id': 6, 'label': 'figure_title', 'score': 0.9577341079711914, 'coordinate': [34.421448, 20.055151, 358.71283, 76.53663]}, {'cls_id': 6, 'label': 'figure_title', 'score': 0.9505634307861328, 'coordinate': [385.72278, 20.053688, 711.29333, 74.92744]}, {'cls_id': 0, 'label': 'paragraph_title', 'score': 0.9001723527908325, 'coordinate': [386.46344, 477.03488, 699.4023, 490.07474]}, {'cls_id': 0, 'label': 'paragraph_title', 'score': 0.8845751285552979, 'coordinate': [35.413048, 627.73596, 185.58383, 640.52264]}, {'cls_id': 0, 'label': 'paragraph_title', 'score': 0.8837394118309021, 'coordinate': [387.17603, 716.3423, 524.7841, 729.258]}, {'cls_id': 0, 'label': 'paragraph_title', 'score': 0.8508939743041992, 'coordinate': [35.50064, 331.18445, 141.6444, 344.81097]}]}}
 ```
 
 参数含义如下：
@@ -323,12 +323,12 @@ for res in output:
 </details>
 
 可视化图片如下：
-<img src="https://raw.githubusercontent.com/cuicheng01/PaddleX_doc_images/refs/heads/main/images/modules/layout_det/layout_res.jpg"/>
+<img src="https://raw.githubusercontent.com/cuicheng01/PaddleX_doc_images/refs/heads/main/images/modules/layout_det/layout_res_plus.jpg"/>
 
 
 相关方法、参数等说明如下：
 
-* `create_model`实例化目标检测模型（此处以`PP-DocLayout-L`为例），具体说明如下：
+* `create_model`实例化目标检测模型（此处以`PP-DocLayout_plus-L`为例），具体说明如下：
 <table>
 <thead>
 <tr>

paddlex/inference/models/object_detection/processors.py

@@ -474,6 +474,8 @@ def restructured_boxes(
         ymin = max(0, ymin)
         xmax = min(w, xmax)
         ymax = min(h, ymax)
+        if xmax <= xmin or ymax <= ymin:
+            continue
         box_list.append(
             {
                 "cls_id": int(box[0]),