PaddlePaddle · Sunting78 · Nov 21, 2024
diff --git a/docs/module_usage/tutorials/ocr_modules/layout_detection.en.md b/docs/module_usage/tutorials/ocr_modules/layout_detection.en.md
@@ -31,6 +31,14 @@ The core task of structure analysis is to parse and segment the content of input
 <td>An efficient layout area localization model trained on the PubLayNet dataset based on PicoDet-1x can locate five types of areas, including text, titles, tables, images, and lists.</td>
 </tr>
 <tr>
+<td>PicoDet_layout_1x_table</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet_layout_1x_table_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet_layout_1x_table_pretrained.pdparams">训练模型</a></td>
+<td>95.7</td>
+<td>12.623</td>
+<td>90.8934</td>
+<td>7.4 M</td>
+<td>An efficient layout area localization model trained on the PubLayNet dataset based on PicoDet-1x can locate one type of tables.</td>
+</tr>
+<tr>
 <td>PicoDet-S_layout_3cls</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet-S_layout_3cls_infer.tar">Inference Model</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet-S_layout_3cls_pretrained.pdparams">Trained Model</a></td>
 <td>87.1</td>
 <td>13.5</td>

diff --git a/docs/module_usage/tutorials/ocr_modules/layout_detection.md b/docs/module_usage/tutorials/ocr_modules/layout_detection.md
@@ -31,6 +31,14 @@ comments: true
 <td>基于PicoDet-1x在PubLayNet数据集训练的高效率版面区域定位模型，可定位包含文字、标题、表格、图片以及列表这5类区域</td>
 </tr>
 <tr>
+<td>PicoDet_layout_1x_table</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet_layout_1x_table_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet_layout_1x_table_pretrained.pdparams">训练模型</a></td>
+<td>95.7</td>
+<td>12.623</td>
+<td>90.8934</td>
+<td>7.4 M</td>
+<td>基于PicoDet-1x在自建数据集训练的高效率版面区域定位模型，可定位包含表格这1类区域</td>
+</tr>
+<tr>
 <td>PicoDet-S_layout_3cls</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet-S_layout_3cls_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet-S_layout_3cls_pretrained.pdparams">训练模型</a></td>
 <td>87.1</td>
 <td>13.5</td>

diff --git a/...ls/information_extraction_pipelines/document_scene_information_extraction.en.md b/...ls/information_extraction_pipelines/document_scene_information_extraction.en.md
@@ -66,6 +66,14 @@ The <b>PP-ChatOCRv3-doc</b> pipeline includes modules for <b>Table Structure Rec
 <td>An efficient layout area localization model trained on the PubLayNet dataset based on PicoDet-1x can locate five types of areas, including text, titles, tables, images, and lists.</td>
 </tr>
 <tr>
+<td>PicoDet_layout_1x_table</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet_layout_1x_table_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet_layout_1x_table_pretrained.pdparams">训练模型</a></td>
+<td>95.7</td>
+<td>12.623</td>
+<td>90.8934</td>
+<td>7.4 M</td>
+<td>An efficient layout area localization model trained on the PubLayNet dataset based on PicoDet-1x can locate one type of tables.</td>
+</tr>
+<tr>
 <td>PicoDet-S_layout_3cls</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet-S_layout_3cls_infer.tar">Inference Model</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet-S_layout_3cls_pretrained.pdparams">Trained Model</a></td>
 <td>87.1</td>
 <td>13.5</td>

diff --git a/...rials/information_extraction_pipelines/document_scene_information_extraction.md b/...rials/information_extraction_pipelines/document_scene_information_extraction.md
@@ -66,6 +66,14 @@ comments: true
 <td>基于PicoDet-1x在PubLayNet数据集训练的高效率版面区域定位模型，可定位包含文字、标题、表格、图片以及列表这5类区域</td>
 </tr>
 <tr>
+<td>PicoDet_layout_1x_table</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet_layout_1x_table_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet_layout_1x_table_pretrained.pdparams">训练模型</a></td>
+<td>95.7</td>
+<td>12.623</td>
+<td>90.8934</td>
+<td>7.4 M</td>
+<td>基于PicoDet-1x在自建数据集训练的高效率版面区域定位模型，可定位包含表格这1类区域</td>
+</tr>
+<tr>
 <td>PicoDet-S_layout_3cls</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet-S_layout_3cls_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet-S_layout_3cls_pretrained.pdparams">训练模型</a></td>
 <td>87.1</td>
 <td>13.5</td>

diff --git a/docs/pipeline_usage/tutorials/ocr_pipelines/layout_parsing.en.md b/docs/pipeline_usage/tutorials/ocr_pipelines/layout_parsing.en.md
@@ -64,6 +64,14 @@ The <b>General Layout Parsing Pipeline</b> includes modules for table structure
 <td>An efficient layout area localization model trained on the PubLayNet dataset based on PicoDet-1x can locate five types of areas, including text, titles, tables, images, and lists.</td>
 </tr>
 <tr>
+<td>PicoDet_layout_1x_table</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet_layout_1x_table_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet_layout_1x_table_pretrained.pdparams">训练模型</a></td>
+<td>95.7</td>
+<td>12.623</td>
+<td>90.8934</td>
+<td>7.4 M</td>
+<td>An efficient layout area localization model trained on the PubLayNet dataset based on PicoDet-1x can locate one type of tables.</td>
+</tr>
+<tr>
 <td>PicoDet-S_layout_3cls</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet-S_layout_3cls_infer.tar">Inference Model</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet-S_layout_3cls_pretrained.pdparams">Trained Model</a></td>
 <td>87.1</td>
 <td>13.5</td>

diff --git a/docs/pipeline_usage/tutorials/ocr_pipelines/layout_parsing.md b/docs/pipeline_usage/tutorials/ocr_pipelines/layout_parsing.md
@@ -64,6 +64,14 @@ comments: true
 <td>基于PicoDet-1x在PubLayNet数据集训练的高效率版面区域定位模型，可定位包含文字、标题、表格、图片以及列表这5类区域</td>
 </tr>
 <tr>
+<td>PicoDet_layout_1x_table</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet_layout_1x_table_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet_layout_1x_table_pretrained.pdparams">训练模型</a></td>
+<td>95.7</td>
+<td>12.623</td>
+<td>90.8934</td>
+<td>7.4 M</td>
+<td>基于PicoDet-1x在自建数据集训练的高效率版面区域定位模型，可定位包含表格这1类区域</td>
+</tr>
+<tr>
 <td>PicoDet-S_layout_3cls</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet-S_layout_3cls_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet-S_layout_3cls_pretrained.pdparams">训练模型</a></td>
 <td>87.1</td>
 <td>13.5</td>

diff --git a/docs/pipeline_usage/tutorials/ocr_pipelines/seal_recognition.en.md b/docs/pipeline_usage/tutorials/ocr_pipelines/seal_recognition.en.md
@@ -36,6 +36,14 @@ The <b>Seal Recognition</b> pipeline includes a layout area analysis module, a s
 <td>An efficient layout area localization model trained on the PubLayNet dataset based on PicoDet-1x can locate five types of areas, including text, titles, tables, images, and lists.</td>
 </tr>
 <tr>
+<td>PicoDet_layout_1x_table</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet_layout_1x_table_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet_layout_1x_table_pretrained.pdparams">训练模型</a></td>
+<td>95.7</td>
+<td>12.623</td>
+<td>90.8934</td>
+<td>7.4 M</td>
+<td>An efficient layout area localization model trained on the PubLayNet dataset based on PicoDet-1x can locate one type of tables.</td>
+</tr>
+<tr>
 <td>PicoDet-S_layout_3cls</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet-S_layout_3cls_infer.tar">Inference Model</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet-S_layout_3cls_pretrained.pdparams">Trained Model</a></td>
 <td>87.1</td>
 <td>13.5</td>

diff --git a/docs/pipeline_usage/tutorials/ocr_pipelines/seal_recognition.md b/docs/pipeline_usage/tutorials/ocr_pipelines/seal_recognition.md
@@ -38,6 +38,14 @@ comments: true
 <td>基于PicoDet-1x在PubLayNet数据集训练的高效率版面区域定位模型，可定位包含文字、标题、表格、图片以及列表这5类区域</td>
 </tr>
 <tr>
+<td>PicoDet_layout_1x_table</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet_layout_1x_table_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet_layout_1x_table_pretrained.pdparams">训练模型</a></td>
+<td>95.7</td>
+<td>12.623</td>
+<td>90.8934</td>
+<td>7.4 M</td>
+<td>基于PicoDet-1x在自建数据集训练的高效率版面区域定位模型，可定位包含表格这1类区域</td>
+</tr>
+<tr>
 <td>PicoDet-S_layout_3cls</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet-S_layout_3cls_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet-S_layout_3cls_pretrained.pdparams">训练模型</a></td>
 <td>87.1</td>
 <td>13.5</td>

diff --git a/docs/pipeline_usage/tutorials/ocr_pipelines/table_recognition.en.md b/docs/pipeline_usage/tutorials/ocr_pipelines/table_recognition.en.md
@@ -70,6 +70,14 @@ SLANet_plus is an enhanced version of SLANet, a table structure recognition mode
 <td>An efficient layout area localization model trained on the PubLayNet dataset based on PicoDet-1x can locate five types of areas, including text, titles, tables, images, and lists.</td>
 </tr>
 <tr>
+<td>PicoDet_layout_1x_table</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet_layout_1x_table_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet_layout_1x_table_pretrained.pdparams">训练模型</a></td>
+<td>95.7</td>
+<td>12.623</td>
+<td>90.8934</td>
+<td>7.4 M</td>
+<td>An efficient layout area localization model trained on the PubLayNet dataset based on PicoDet-1x can locate one type of tables.</td>
+</tr>
+<tr>
 <td>PicoDet-S_layout_3cls</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet-S_layout_3cls_infer.tar">Inference Model</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet-S_layout_3cls_pretrained.pdparams">Trained Model</a></td>
 <td>87.1</td>
 <td>13.5</td>

diff --git a/docs/pipeline_usage/tutorials/ocr_pipelines/table_recognition.md b/docs/pipeline_usage/tutorials/ocr_pipelines/table_recognition.md
@@ -65,6 +65,14 @@ comments: true
 <td>基于PicoDet-1x在PubLayNet数据集训练的高效率版面区域定位模型，可定位包含文字、标题、表格、图片以及列表这5类区域</td>
 </tr>
 <tr>
+<td>PicoDet_layout_1x_table</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet_layout_1x_table_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet_layout_1x_table_pretrained.pdparams">训练模型</a></td>
+<td>95.7</td>
+<td>12.623</td>
+<td>90.8934</td>
+<td>7.4 M</td>
+<td>基于PicoDet-1x在自建数据集训练的高效率版面区域定位模型，可定位包含表格这1类区域</td>
+</tr>
+<tr>
 <td>PicoDet-S_layout_3cls</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet-S_layout_3cls_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet-S_layout_3cls_pretrained.pdparams">训练模型</a></td>
 <td>87.1</td>
 <td>13.5</td>

diff --git a/...utorials/document_scene_information_extraction(layout_detection)_tutorial.en.md b/...utorials/document_scene_information_extraction(layout_detection)_tutorial.en.md
@@ -109,6 +109,14 @@ PaddleX provides 4 end-to-end layout detection models, which can be referenced i
 <td>An efficient layout area localization model trained on the PubLayNet dataset based on PicoDet-1x can locate five types of areas, including text, titles, tables, images, and lists.</td>
 </tr>
 <tr>
+<td>PicoDet_layout_1x_table</td>
+<td>95.7</td>
+<td>12.623</td>
+<td>90.8934</td>
+<td>7.4 M</td>
+<td>An efficient layout area localization model trained on the PubLayNet dataset based on PicoDet-1x can locate one type of tables.</td>
+</tr>
+<tr>
 <td>PicoDet-S_layout_3cls</td>
 <td>87.1</td>
 <td>13.5</td>

diff --git a/...l_tutorials/document_scene_information_extraction(layout_detection)_tutorial.md b/...l_tutorials/document_scene_information_extraction(layout_detection)_tutorial.md
@@ -114,6 +114,14 @@ PaddleX 提供了 4 个端到端的版面区域定位模型，具体可参考 [
 <td>基于PicoDet-1x在PubLayNet数据集训练的高效率版面区域定位模型，可定位包含文字、标题、表格、图片以及列表这5类区域</td>
 </tr>
 <tr>
+<td>PicoDet_layout_1x_table</td>
+<td>95.7</td>
+<td>12.623</td>
+<td>90.8934</td>
+<td>7.4 M</td>
+<td>基于PicoDet-1x在自建数据集训练的高效率版面区域定位模型，可定位包含表格1个类别</td>
+</tr>
+<tr>
 <td>PicoDet-S_layout_3cls</td>
 <td>87.1</td>
 <td>13.5</td>

diff --git a/docs/support_list/models_list.en.md b/docs/support_list/models_list.en.md
@@ -1963,6 +1963,14 @@ PaddleX incorporates multiple pipelines, each containing several modules, and ea
 <td><a href="https://github.com/PaddlePaddle/PaddleX/blob/develop/paddlex/configs/structure_analysis/PicoDet_layout_1x.yaml">PicoDet_layout_1x.yaml</a></td>
 <td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet_layout_1x_infer.tar">Inference Model</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet_layout_1x_pretrained.pdparams">Trained Model</a></td></tr>
 <tr>
+<td>PicoDet_layout_1x_table</td>
+<td>95.7</td>
+<td>12.623</td>
+<td>90.8934</td>
+<td>7.4 M</td>
+<td><a href="https://github.com/PaddlePaddle/PaddleX/blob/develop/paddlex/configs/structure_analysis/PicoDet_layout_1x_table.yaml">PicoDet_layout_1x_table.yaml</a></td>
+<td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet_layout_1x_table_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet_layout_1x_table_pretrained.pdparams">训练模型</a></td></tr>
+<tr>
 <td>PicoDet-S_layout_3cls</td>
 <td>87.1</td>
 <td>13.521</td>

diff --git a/docs/support_list/models_list.md b/docs/support_list/models_list.md
@@ -1961,6 +1961,14 @@ PaddleX 内置了多条产线，每条产线都包含了若干模块，每个模
 <td><a href="https://github.com/PaddlePaddle/PaddleX/blob/develop/paddlex/configs/structure_analysis/PicoDet_layout_1x.yaml">PicoDet_layout_1x.yaml</a></td>
 <td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet_layout_1x_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet_layout_1x_pretrained.pdparams">训练模型</a></td></tr>
 <tr>
+<td>PicoDet_layout_1x_table</td>
+<td>95.7</td>
+<td>12.623</td>
+<td>90.8934</td>
+<td>7.4 M</td>
+<td><a href="https://github.com/PaddlePaddle/PaddleX/blob/develop/paddlex/configs/structure_analysis/PicoDet_layout_1x_table.yaml">PicoDet_layout_1x_table.yaml</a></td>
+<td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet_layout_1x_table_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet_layout_1x_table_pretrained.pdparams">训练模型</a></td></tr>
+<tr>
 <td>PicoDet-S_layout_3cls</td>
 <td>87.1</td>
 <td>13.521</td>

diff --git a/paddlex/configs/structure_analysis/PicoDet_layout_1x_table.yaml b/paddlex/configs/structure_analysis/PicoDet_layout_1x_table.yaml
@@ -0,0 +1,40 @@
+Global:
+  model: PicoDet_layout_1x_table
+  mode: check_dataset # check_dataset/train/evaluate/predict
+  dataset_dir: "/paddle/dataset/paddlex/layout/det_layout_examples"
+  device: gpu:0,1,2,3
+  output: "output"
+
+CheckDataset:
+  convert:
+    enable: False
+    src_dataset_type: null
+  split:
+    enable: False
+    train_percent: null
+    val_percent: null
+
+Train:
+  num_classes: 11
+  epochs_iters: 50
+  batch_size: 24
+  learning_rate: 0.4
+  pretrain_weight_path: https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet_layout_1x_table_pretrained.pdparams
+  warmup_steps: 100
+  resume_path: null
+  log_interval: 1
+  eval_interval: 1
+
+Evaluate:
+  weight_path: "output/best_model/best_model.pdparams"
+  log_interval: 10
+
+Export:
+  weight_path: https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PicoDet_layout_1x_table_pretrained.pdparams
+
+Predict:
+  batch_size: 1
+  model_dir: "output/best_model/inference"
+  input: "https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/layout.jpg"
+  kernel_option:
+    run_mode: paddle
diff --git a/paddlex/inference/utils/official_models.py b/paddlex/inference/utils/official_models.py
@@ -211,6 +211,7 @@
     "PP-LCNet_x1_0_vehicle_attribute": "https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/\
 PP-LCNet_x1_0_vehicle_attribute_infer.tar",
     "PicoDet_layout_1x": "https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet_layout_1x_infer.tar",
+    "PicoDet_layout_1x_table": "https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/PicoDet_layout_1x_table_infer.tar",
     "SLANet": "https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/SLANet_infer.tar",
     "SLANet_plus": "https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/SLANet_plus_infer.tar",
     "LaTeX_OCR_rec": "https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0b2/LaTeX_OCR_rec_infer.tar",

diff --git a/paddlex/modules/object_detection/model_list.py b/paddlex/modules/object_detection/model_list.py
@@ -26,6 +26,7 @@
     "RT-DETR-R50",
     "RT-DETR-X",
     "PicoDet_layout_1x",
+    "PicoDet_layout_1x_table",
     "PicoDet-S_layout_3cls",
     "PicoDet-S_layout_17cls",
     "PicoDet-L_layout_3cls",

diff --git a/paddlex/pipelines/table_recognition.yaml b/paddlex/pipelines/table_recognition.yaml
@@ -3,7 +3,7 @@ Global:
   input: https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/table_recognition.jpg
 
 Pipeline:
-  layout_model: PicoDet_layout_1x
+  layout_model: PicoDet_layout_1x_table
   table_model: SLANet_plus
   text_det_model: PP-OCRv4_mobile_det
   text_rec_model: PP-OCRv4_mobile_rec