# Interface Change Documentation

## 1. Model and Module Related

### 1.1 Model Configuration Files

- **Storage Directory Change**: `paddlex/configs` has been updated to `paddlex/configs/modules`.
- **Module Name Changes**, and related configuration file paths have also been updated:
  - `anomaly_detection` updated to `image_anomaly_detection`
  - `face_recognition` updated to `face_feature`
  - `general_recognition` updated to `image_feature`
  - `multilabel_classification` updated to `image_multilabel_classification`
  - `pedestrian_attribute` updated to `pedestrian_attribute_recognition`
  - `structure_analysis` updated to `layout_detection`
  - `table_recognition` updated to `table_structure_recognition`
  - `text_detection_seal` updated to `seal_text_detection`
  - `vehicle_attribute` updated to `vehicle_attribute_recognition`

### 1.2 Module Inference

#### 1. `create_model()`

- **Parameter Change**:
  - `model_name`: Only accepts model name.
  - **New Parameters**:
    - `model_dir`: Specifies the local directory for inference model files, defaults to `None`, which means automatically downloading and using the official model.
    - `batch_size`: Specifies the batch size during inference, defaults to `1`.
    - Supports specifying common model inference hyperparameters, with specific parameters related to the module, as detailed in the module tutorial documentation. For example, image classification module support `topk`.
    - `use_hpip` and `hpi_params`: For supporting high-performance inference, not enabled by default.

- **Function Updates**:
  - Supports using PDF files as input samples for CV modules.
  - Prediction results remain of `dict` type, but the format has changed: from `{'key1': val}` to `{"res": {'key': val}}`, using `"res"` as the key with the original result data as the value.
  - When using the `save_to_xxx()` method to save prediction results, if `save_path` is a directory, the name for stored files has changed. For example, saving in JSON format is `{input_file_prefix}_res.json`; saving in image format is `{input_file_prefix}_res_img.{input_file_extension}`.

## 2. Pipeline Related

### 2.1 Pipeline Configuration Files

- **Configuration File Storage Directory Change**: `paddlex/pipelines` updated to `paddlex/configs/pipelines`.
- **Pipeline Name Changes**:
  - `ts_fc` updated to `ts_forecast`
  - `ts_ad` updated to `ts_anomaly_detection`
  - `ts_cls` updated to `ts_classification`

### 2.2 Pipeline Inference

#### 1. CLI Inference for Pipelines

- **New Support**:
  - Inference hyperparameters, specific parameters related to the pipeline, detailed in the pipeline tutorial documentation. For example, image classification pipeline supports the `--topk` parameter to specify the `topk` results to return.
- **Removed**:
  - `--serial_number`, high-performance inference no longer requires the serial number.

#### 2. `create_pipeline()`

- **Removed**:
  - The `serial_number` parameter in high-performance inference `hpi_params`, high-performance inference no longer requires the serial number.
- **No Longer Supported**:
  - Setting pipeline inference hyperparameters, all related parameters must be set through the pipeline configuration file, such as `batch_size`, thresholds, etc.
- **Function Updates**:
  1. When using the `save_to_xxx()` method to save prediction results, if `save_path` is a directory, the name for stored files has updated.
  2. CV model prediction results have a new `page_index` field, which indicates the page number of the current prediction result only when the input sample is a PDF file.
  3. Model pipeline prediction results have new pipeline inference parameter fields, such as the `text_det_params` field in the OCR pipeline, with values for the post-processing settings of the text detection model.
- **Configuration File Format Update**:
  - After updating the content of the pipeline configuration file, it is divided into three parts: pipeline name, pipeline-related parameter settings, and sub-pipelines and sub-modules composition. For example:

    ```yaml
    pipeline_name: pipeline # Pipeline Name
    threshold: 0.5 # Pipeline Inference Related Parameters
    SubPipelines: # Sub-pipelines
      DocPreprocessor:
        pipeline_name: doc_preprocessor
        use_doc_unwarping: True # Settings related to the sub-pipeline DocPreprocessor
    SubModules: # Sub-modules
      TextDetection:
        module_name: text_detection
        model_name: PP-OCRv4_mobile_det
        model_dir: null
        limit_side_len: 960 # Settings related to the sub-module TextDetection
        limit_type: max
        max_side_limit: 4000
        thresh: 0.3
        box_thresh: 0.6
        unclip_ratio: 1.5
    ```

## 3. Pipeline Features Changes

### 3.1 OCR Pipeline

- **New Features**:
  - Document Preprocessing: Supports whole image direction classification and correction, controlled by relevant parameters in the `OCR.yaml` configuration file.
  - Text Line Direction Classification: Controlled by relevant parameters in the configuration file.
  - Support for modifying model inference hyperparameters, such as post-processing parameters of the text detection model, controlled by relevant parameters in the configuration file.

### 3.2 Seal Recognition and Formula Recognition Pipeline

- **New Features**:
  - Document Preprocessing: Supports whole image direction classification and correction, controlled by relevant parameters in the configuration file.
  - Option to use the layout detection model: Controlled by relevant parameters in the configuration file.

### 3.3 Table Recognition Pipeline

- **New Features**:
  - Document Preprocessing: Supports whole image direction classification and correction, controlled by relevant parameters in the configuration file.
  - Option to use the OCR pipeline for text detection and recognition: Controlled by relevant parameters in the configuration file.

### 3.4 Layout Analysis Pipeline

- **Updated Features**:
  - Supports more inference hyperparameter settings, such as document preprocessing, text recognition, and model post-processing parameter settings, all of which can be configured in the pipeline configuration file.

### 3.5 PP-ChatOCRv3-doc Pipeline

- **New Features**:
  - Supports standard OpenAI API calls, which can be controlled through relevant parameters in the configuration file.
  - Allows switching large language models during Chat API calls by passing the relevant configuration through the API call parameters.

- **Updated Features**:
  - Inference Module Initialization: Supports initialization of the inference module upon its first invocation, eliminating the need for full initialization at pipeline startup.
  - Vector Library: Enables setting block size for long text and removes the control of interval duration between vector library calls.