未验证 提交 57e4b882 编写于 作者: Z zhoujun 提交者: GitHub

update inference doc (#8796)

* fixed opencv version

* update infernence
上级 97ef80e3
......@@ -11,7 +11,7 @@
- [2.3 多语言模型的推理](#23-多语言模型的推理)
- [3. 方向分类模型推理](#3-方向分类模型推理)
- [4. 文本检测、方向分类和文字识别串联推理](#4-文本检测方向分类和文字识别串联推理)
- [5. TensorRT推理](5-TensorRT推理)
- [5. TensorRT推理](#5-tensorrt推理)
<a name="文本检测模型推理"></a>
......@@ -144,7 +144,7 @@ Predicts of ./doc/imgs_words/ch/word_4.jpg:['0', 0.9999982]
**注意** `PP-OCRv3`的识别模型使用的输入shape为`3,48,320`, 如果使用其他识别模型,则需根据模型设置参数`--rec_image_shape`。此外,`PP-OCRv3`的识别模型默认使用的`rec_algorithm``SVTR_LCNet`,注意和原始`SVTR`的区别。
以超轻量中文OCR模型推理为例,在执行预测时,需要通过参数`image_dir`指定单张图像或者图像集合的路径,也支持PDF文件、参数`det_model_dir`,`cls_model_dir``rec_model_dir`分别指定检测,方向分类和识别的inference模型路径。参数`use_angle_cls`用于控制是否启用方向分类模型。`use_mp`表示是否使用多进程。`total_process_num`表示在使用多进程时的进程数。可视化识别结果默认保存到 ./inference_results 文件夹里面。
以超轻量中文OCR模型推理为例,在执行预测时,需要通过参数`image_dir`指定单张图像或者图像集合的路径,也支持PDF文件、参数`det_model_dir`,`cls_model_dir``rec_model_dir`分别指定检测,方向分类和识别的inference模型路径。参数`use_angle_cls`用于控制是否启用方向分类模型。`use_mp`表示是否使用多进程(Paddle Inference并不是线程安全,建议使用多进程)`total_process_num`表示在使用多进程时的进程数。可视化识别结果默认保存到 ./inference_results 文件夹里面。
```shell
# 使用方向分类器
......
......@@ -10,30 +10,28 @@ For more details, please refer to the document [Classification Framework](https:
Next, we first introduce how to convert a trained model into an inference model, and then we will introduce text detection, text recognition, angle class, and the concatenation of them based on inference model.
- [1. Convert Training Model to Inference Model](#CONVERT)
- [1.1 Convert Detection Model to Inference Model](#Convert_detection_model)
- [1.2 Convert Recognition Model to Inference Model](#Convert_recognition_model)
- [1.3 Convert Angle Classification Model to Inference Model](#Convert_angle_class_model)
- [2. Text Detection Model Inference](#DETECTION_MODEL_INFERENCE)
- [2.1 Lightweight Chinese Detection Model Inference](#LIGHTWEIGHT_DETECTION)
- [2.2 DB Text Detection Model Inference](#DB_DETECTION)
- [2.3 East Text Detection Model Inference](#EAST_DETECTION)
- [2.4 Sast Text Detection Model Inference](#SAST_DETECTION)
- [3. Text Recognition Model Inference](#RECOGNITION_MODEL_INFERENCE)
- [3.1 Lightweight Chinese Text Recognition Model Reference](#LIGHTWEIGHT_RECOGNITION)
- [3.2 CTC-Based Text Recognition Model Inference](#CTC-BASED_RECOGNITION)
- [3.3 SRN-Based Text Recognition Model Inference](#SRN-BASED_RECOGNITION)
- [3.4 Text Recognition Model Inference Using Custom Characters Dictionary](#USING_CUSTOM_CHARACTERS)
- [3.5 Multilingual Model Inference](#MULTILINGUAL_MODEL_INFERENCE)
- [4. Angle Classification Model Inference](#ANGLE_CLASS_MODEL_INFERENCE)
- [5. Text Detection Angle Classification And Recognition Inference Concatenation](#CONCATENATION)
- [5.1 Lightweight Chinese Model](#LIGHTWEIGHT_CHINESE_MODEL)
- [5.2 Other Models](#OTHER_MODELS)
- [Inference Based on Python Prediction Engine](#inference-based-on-python-prediction-engine)
- [1. Convert Training Model to Inference Model](#1-convert-training-model-to-inference-model)
- [1.1 Convert Detection Model to Inference Model](#11-convert-detection-model-to-inference-model)
- [1.2 Convert Recognition Model to Inference Model](#12-convert-recognition-model-to-inference-model)
- [1.3 Convert Angle Classification Model to Inference Model](#13-convert-angle-classification-model-to-inference-model)
- [2. Text Detection Model Inference](#2-text-detection-model-inference)
- [2.1 Lightweight Chinese Detection Model Inference](#21-lightweight-chinese-detection-model-inference)
- [2.2 DB Text Detection Model Inference](#22-db-text-detection-model-inference)
- [2.3 EAST TEXT DETECTION MODEL INFERENCE](#23-east-text-detection-model-inference)
- [2.4 Sast Text Detection Model Inference](#24-sast-text-detection-model-inference)
- [(1). Quadrangle text detection model (ICDAR2015)](#1-quadrangle-text-detection-model-icdar2015)
- [(2). Curved text detection model (Total-Text)](#2-curved-text-detection-model-total-text)
- [3. Text Recognition Model Inference](#3-text-recognition-model-inference)
- [3.1 Lightweight Chinese Text Recognition Model Reference](#31-lightweight-chinese-text-recognition-model-reference)
- [3.2 CTC-Based Text Recognition Model Inference](#32-ctc-based-text-recognition-model-inference)
- [3.3 SRN-Based Text Recognition Model Inference](#33-srn-based-text-recognition-model-inference)
- [3.4 Text Recognition Model Inference Using Custom Characters Dictionary](#34-text-recognition-model-inference-using-custom-characters-dictionary)
- [3.5 Multilingual Model Inference](#35-multilingual-model-inference)
- [4. Angle Classification Model Inference](#4-angle-classification-model-inference)
- [5. Text Detection Angle Classification and Recognition Inference Concatenation](#5-text-detection-angle-classification-and-recognition-inference-concatenation)
- [5.1 Lightweight Chinese Model](#51-lightweight-chinese-model)
- [5.2 Other Models](#52-other-models)
<a name="CONVERT"></a>
## 1. Convert Training Model to Inference Model
......@@ -371,7 +369,7 @@ After executing the command, the prediction results (classification angle and sc
<a name="LIGHTWEIGHT_CHINESE_MODEL"></a>
### 5.1 Lightweight Chinese Model
When performing prediction, you need to specify the path of a single image or a folder of images through the parameter `image_dir`, the parameter `det_model_dir` specifies the path to detect the inference model, the parameter `cls_model_dir` specifies the path to angle classification inference model and the parameter `rec_model_dir` specifies the path to identify the inference model. The parameter `use_angle_cls` is used to control whether to enable the angle classification model. The parameter `use_mp` specifies whether to use multi-process to infer `total_process_num` specifies process number when using multi-process. The parameter . The visualized recognition results are saved to the `./inference_results` folder by default.
When performing prediction, you need to specify the path of a single image or a folder of images through the parameter `image_dir`, the parameter `det_model_dir` specifies the path to detect the inference model, the parameter `cls_model_dir` specifies the path to angle classification inference model and the parameter `rec_model_dir` specifies the path to identify the inference model. The parameter `use_angle_cls` is used to control whether to enable the angle classification model. The parameter `use_mp` specifies whether to use multi-process to infer `total_process_num` specifies process number when using multi-process. The parameter(Paddle Inference is not thread-safe, it is recommended to use multi-process) . The visualized recognition results are saved to the `./inference_results` folder by default.
```shell
# use direction classifier
......
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