add PP-LCNet_x1_0_textline_ori

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

@@ -23,15 +23,25 @@ The text line orientation classification module primarily distinguishes the orie
 <tbody>
 <tr>
 <td>PP-LCNet_x0_25_textline_ori</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-LCNet_x0_25_textline_ori_infer.tar">Inference Model</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PP-LCNet_x0_25_textline_ori_pretrained.pdparams">Training Model</a></td>
-<td>95.54</td>
+<td>98.85</td>
 <td>-</td>
 <td>-</td>
 <td>0.32</td>
 <td>Text line classification model based on PP-LCNet_x0_25, with two classes: 0 degrees and 180 degrees</td>
 </tr>
+<tr>
+<td>PP-LCNet_x1_0_textline_ori</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-LCNet_x1_0_textline_ori_infer.tar">Inference Model</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PP-LCNet_x1_0_textline_ori_pretrained.pdparams">Training Model</a></td>
+<td>99.42</td>
+<td>-</td>
+<td>-</td>
+<td>6.5</td>
+<td>Text line classification model based on PP-LCNet_x1_0, with two classes: 0 degrees and 180 degrees</td>
+</tr>
 </tbody>
 </table>
 
+> ❗ **Note**: The text line orientation classification model has been recently upgraded, and `PP-LCNet_x1_0_textline_ori` has been added. If you need to use the pre-upgrade model weights, please click the <a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-LCNet_x0_25_textline_ori_infer.bak.tar">download link</a>.
+
 <strong>Test Environment Description:</strong>
 
   <ul>
@@ -94,22 +104,23 @@ for res in output:
 After running, the result obtained is:
 
 ```bash
-{'res': {'input_path': 'test_imgs/textline_rot180_demo.jpg', 'class_ids': [1], 'scores': [1.0], 'label_names': ['180_degree']}}
+{'res': {'input_path': 'textline_rot180_demo.jpg', 'page_index': None, 'class_ids': array([1], dtype=int32), 'scores': array([0.99864], dtype=float32), 'label_names': ['180_degree']}}
 ```
 
 The meanings of the running results parameters are as follows:
 
 - `input_path`：Indicates the path of the input image.
+- `page_index`：If the input is a PDF file, it indicates the current page number of the PDF; otherwise, it is `None`.
 - `class_ids`：Indicates the class ID of the prediction result.
 - `scores`：Indicates the confidence score of the prediction result.
 - `label_names`：Indicates the class name of the prediction result.
 The visualization image is as follows:
 
-<img src="https://raw.githubusercontent.com/cuicheng01/PaddleX_doc_images/refs/heads/main/images/modules/image_classification/general_image_classification_001_res.jpg">
+<img src="https://raw.githubusercontent.com/cuicheng01/PaddleX_doc_images/refs/heads/main/images/modules/textline_ori_classification/textline_rot180_demo_res.jpg">
 
 The explanations for the methods, parameters, etc., are as follows:
 
-* `create_model` instantiates a text recognition model (here, `PP-LCNet_x0_25_textline_ori` is used as an example), and the specific explanations are as follows:
+* `create_model` instantiates a textline classification model (here, `PP-LCNet_x0_25_textline_ori` is used as an example), and the specific explanations are as follows:
 
 <table>
 <thead>

docs/module_usage/tutorials/ocr_modules/textline_orientation_classification.md

@@ -25,15 +25,25 @@ comments: true
 <tbody>
 <tr>
 <td>PP-LCNet_x0_25_textline_ori</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-LCNet_x0_25_textline_ori_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PP-LCNet_x0_25_textline_ori_pretrained.pdparams">训练模型</a></td>
-<td>95.54</td>
+<td>98.85</td>
 <td>-</td>
 <td>-</td>
 <td>0.32</td>
 <td>基于PP-LCNet_x0_25的文本行分类模型，含有两个类别，即0度，180度</td>
 </tr>
+<tr>
+<td>PP-LCNet_x1_0_textline_ori</td><td><a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-LCNet_x1_0_textline_ori_infer.tar">推理模型</a>/<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PP-LCNet_x1_0_textline_ori_pretrained.pdparams">训练模型</a></td>
+<td>99.42</td>
+<td>-</td>
+<td>-</td>
+<td>6.5</td>
+<td>基于PP-LCNet_x1_0的文本行分类模型，含有两个类别，即0度，180度</td>
+</tr>
 </tbody>
 </table>
 
+> ❗ <b>注</b>：文本行方向分类模型近期升级，并增加 `PP-LCNet_x1_0_textline_ori`，如需使用升级前的模型权重，请点击<a href="https://paddle-model-ecology.bj.bcebos.com/paddlex/official_inference_model/paddle3.0.0/PP-LCNet_x0_25_textline_ori_infer.bak.tar">下载链接</a>
+
 <strong>测试环境说明:</strong>
 
   <ul>
@@ -96,7 +106,7 @@ for res in output:
 
 运行后，得到的结果为：
 ```bash
-{'res': {'input_path': 'textline_rot180_demo.jpg', 'page_index': None, 'class_ids': array([1], dtype=int32), 'scores': array([1.], dtype=float32), 'label_names': ['180_degree']}}
+{'res': {'input_path': 'textline_rot180_demo.jpg', 'page_index': None, 'class_ids': array([1], dtype=int32), 'scores': array([0.99864], dtype=float32), 'label_names': ['180_degree']}}
 ```
 
 运行结果参数含义如下：

paddlex/configs/modules/textline_orientation/PP-LCNet_x1_0_textline_ori.yaml

@@ -0,0 +1,41 @@
+Global:
+  model: PP-LCNet_x1_0_textline_ori
+  mode: check_dataset # check_dataset/train/evaluate/predict
+  dataset_dir: "/paddle/dataset/paddlex/cls/textline_orientation_example_data"
+  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: 2
+  epochs_iters: 20
+  batch_size: 32
+  learning_rate: 0.8
+  pretrain_weight_path: https://paddle-model-ecology.bj.bcebos.com/paddlex/official_pretrained_model/PP-LCNet_x1_0_textline_ori_pretrained.pdparams
+  warmup_steps: 100
+  resume_path: null
+  log_interval: 10
+  eval_interval: 1
+  save_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/PP-LCNet_x1_0_textline_ori_pretrained.pdparams
+
+Predict:
+  batch_size: 1
+  model_dir: "output/best_model/inference"
+  input: "https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/img_textline180_demo.jpg"
+  kernel_option:
+    run_mode: paddle

paddlex/modules/image_classification/model_list.py

@@ -62,6 +62,7 @@ MODELS = [
     "PP-LCNet_x0_75",
     "PP-LCNet_x1_0",
     "PP-LCNet_x1_0_doc_ori",
+    "PP-LCNet_x1_0_textline_ori",
     "PP-LCNet_x1_5",
     "PP-LCNet_x2_0",
     "PP-LCNet_x2_5",

paddlex/repo_apis/PaddleClas_api/cls/register.py

@@ -898,6 +898,16 @@ register_model_info(
 
 register_model_info(
     {
+        "model_name": "PP-LCNet_x1_0_textline_ori",
+        "suite": "Cls",
+        "config_path": osp.join(PDX_CONFIG_DIR, "PP-LCNet_x1_0_textline_ori.yaml"),
+        "supported_apis": ["train", "evaluate", "predict", "export", "infer"],
+        "infer_config": "deploy/configs/inference_cls.yaml",
+    }
+)
+
+register_model_info(
+    {
         "model_name": "PP-LCNet_x1_0_table_cls",
         "suite": "Cls",
         "config_path": osp.join(PDX_CONFIG_DIR, "PP-LCNet_x1_0_table_cls.yaml"),

paddlex/repo_apis/PaddleClas_api/configs/PP-LCNet_x0_25_textline_ori.yaml

@@ -22,10 +22,9 @@ Global:
 Arch:
   name: PPLCNet_x0_25
   class_num: 2
-  pretrained: True
-  use_ssld: True
-  use_last_conv: False
-  stride_list: [[1, 2], [2, 1], [2, 1], [2, 1], [2, 1]]
+  pretrained: False
+  use_ssld: False
+  stride_list: [2, [2, 1], [2, 1], [2, 1], [2, 1]]
  
 # loss function config for traing/eval process
 Loss:
@@ -46,7 +45,7 @@ Optimizer:
     warmup_epoch: 5
   regularizer:
     name: 'L2'
-    coeff: 0.00004
+    coeff: 0.00001
 
 
 # data loader for train and eval

paddlex/repo_apis/PaddleClas_api/configs/PP-LCNet_x1_0_textline_ori.yaml

@@ -0,0 +1,143 @@
+# global configs
+Global:
+  checkpoints: null
+  pretrained_model: null
+  output_dir: ./output/
+  device: gpu
+  save_interval: 1
+  eval_during_train: True
+  start_eval_epoch: 1
+  eval_interval: 1
+  epochs: 20
+  print_batch_step: 10
+  use_visualdl: False
+  # used for static mode and model export
+  image_shape: [3, 80, 160]
+  save_inference_dir: ./inference
+  # training model under @to_static
+  to_static: False
+  use_dali: False
+
+# model architecture
+Arch:
+  name: PPLCNet_x1_0
+  class_num: 2
+  pretrained: False
+  use_ssld: False
+  stride_list: [2, [2, 1], [2, 1], [2, 1], [2, 1]]
+ 
+# loss function config for traing/eval process
+Loss:
+  Train:
+    - CELoss:
+        weight: 1.0
+  Eval:
+    - CELoss:
+        weight: 1.0
+
+
+Optimizer:
+  name: Momentum
+  momentum: 0.9
+  lr:
+    name: Cosine
+    learning_rate: 0.8
+    warmup_epoch: 5
+  regularizer:
+    name: 'L2'
+    coeff: 0.00001
+
+
+# data loader for train and eval
+DataLoader:
+  Train:
+    dataset:
+      name: ImageNetDataset
+      image_root: ./dataset/textline_orientation/
+      cls_label_path: ./dataset/textline_orientation/train_list.txt
+      transform_ops:
+        - DecodeImage:
+            to_rgb: True
+            channel_first: False
+        - ResizeImage:
+            size: [160, 80]
+        - TimmAutoAugment:
+            prob: 1.0
+            config_str: rand-m9-mstd0.5-inc1
+            interpolation: bicubic
+            img_size: [160, 80]
+        - NormalizeImage:
+            scale: 1.0/255.0
+            mean: [0.485, 0.456, 0.406]
+            std: [0.229, 0.224, 0.225]
+            order: ''
+        - RandomErasing:
+            EPSILON: 0.0
+            sl: 0.02
+            sh: 1.0/3.0
+            r1: 0.3
+            attempt: 10
+            use_log_aspect: True
+            mode: pixel
+
+    sampler:
+      name: DistributedBatchSampler
+      batch_size: 256
+      drop_last: False
+      shuffle: True
+    loader:
+      num_workers: 16
+      use_shared_memory: True
+
+  Eval:
+    dataset: 
+      name: ImageNetDataset
+      image_root: ./dataset/textline_orientation/
+      cls_label_path: ./dataset/textline_orientation/val_list.txt
+      transform_ops:
+        - DecodeImage:
+            to_rgb: True
+            channel_first: False
+        - ResizeImage:
+            size: [160, 80]
+        - NormalizeImage:
+            scale: 1.0/255.0
+            mean: [0.485, 0.456, 0.406]
+            std: [0.229, 0.224, 0.225]
+            order: ''
+    sampler:
+      name: DistributedBatchSampler
+      batch_size: 32
+      drop_last: False
+      shuffle: False
+    loader:
+      num_workers: 8
+      use_shared_memory: True
+
+Infer:
+  infer_imgs: deploy/images/PULC/textline_orientation/textline_orientation_test_0_0.png
+  batch_size: 10
+  transforms:
+    - DecodeImage:
+        to_rgb: True
+        channel_first: False
+    - ResizeImage:
+        size: [160, 80]
+    - NormalizeImage:
+        scale: 1.0/255.0
+        mean: [0.485, 0.456, 0.406]
+        std: [0.229, 0.224, 0.225]
+        order: ''
+    - ToCHWImage:
+  PostProcess:
+    name: Topk
+    topk: 1
+    class_id_map_file: ppcls/utils/PULC_label_list/textline_orientation_label_list.txt
+
+Metric:
+  Train:
+    - TopkAcc:
+        topk: [1, 2]
+  Eval:
+    - TopkAcc:
+        topk: [1, 2]