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fix v6 docs (#18209)
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‎docs/version3.x/pipeline_usage/OCR.en.md‎

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@@ -1287,24 +1287,26 @@ If `save_path` is specified, the visualization results will be saved under `save
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The command-line method is for quick testing. For project integration, you can achieve OCR inference with just a few lines of code:
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```python
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from paddleocr import PaddleOCR
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```python
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from paddleocr import PaddleOCR
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# Uses PP-OCRv6 models by default
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ocr = PaddleOCR(
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use_doc_orientation_classify=False, # Disables document orientation classification model via this parameter
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use_doc_unwarping=False, # Disables text image rectification model via this parameter
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use_textline_orientation=False, # Disables text line orientation classification model via this parameter
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)
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# ocr = PaddleOCR(lang="en") # Uses English model by specifying language parameter
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# ocr = PaddleOCR(ocr_version="PP-OCRv4") # Uses other PP-OCR versions via version parameter
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# ocr = PaddleOCR(ocr_version="PP-OCRv5") # Switches to PP-OCRv5 version via ocr_version parameter
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# ocr = PaddleOCR(ocr_version="PP-OCRv4") # Switches to PP-OCRv4 version via ocr_version parameter
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# ocr = PaddleOCR(device="gpu") # Enables GPU acceleration for model inference via device parameter
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# ocr = PaddleOCR(
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# text_detection_model_name="PP-OCRv5_mobile_det",
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# text_recognition_model_name="PP-OCRv5_mobile_rec",
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# use_doc_orientation_classify=False,
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# use_doc_unwarping=False,
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# use_textline_orientation=False,
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# ) # Switch to PP-OCRv5_mobile models
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# ) # Switch to PP-OCRv5 mobile models
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result = ocr.predict("./general_ocr_002.png")
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for res in result:
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res.print()
@@ -2625,14 +2627,16 @@ If you choose `transformers` as the inference engine, make sure the Transformers
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```python
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from paddleocr import PaddleOCR
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# Uses PP-OCRv6 models by default
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ocr = PaddleOCR(
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use_doc_orientation_classify=False, # Disable document orientation classification
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use_doc_unwarping=False, # Disable document unwarping
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use_textline_orientation=False, # Disable textline orientation classification
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engine="transformers",
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)
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# ocr = PaddleOCR(lang="en", engine="transformers") # Use the English model
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# ocr = PaddleOCR(ocr_version="PP-OCRv4", engine="transformers") # Use another PP-OCR version
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# ocr = PaddleOCR(ocr_version="PP-OCRv5", engine="transformers") # Switch to PP-OCRv5 version
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# ocr = PaddleOCR(ocr_version="PP-OCRv4", engine="transformers") # Switch to PP-OCRv4 version
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# ocr = PaddleOCR(device="gpu", engine="transformers") # Use GPU for inference
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# ocr = PaddleOCR(
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# text_detection_model_name="PP-OCRv5_server_det",
@@ -2641,7 +2645,7 @@ ocr = PaddleOCR(
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# use_doc_unwarping=False,
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# use_textline_orientation=False,
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# engine="transformers",
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# ) # Switch to the PP-OCRv5_server models
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# ) # Switch to PP-OCRv5 server models
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result = ocr.predict("./general_ocr_002.png")
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for res in result:
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res.print()
@@ -2654,14 +2658,16 @@ If you choose `onnxruntime` as the inference engine, make sure the ONNX Runtime
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```python
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from paddleocr import PaddleOCR
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# Uses PP-OCRv6 models by default
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ocr = PaddleOCR(
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use_doc_orientation_classify=False, # Disable document orientation classification
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use_doc_unwarping=False, # Disable document unwarping
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use_textline_orientation=False, # Disable textline orientation classification
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engine="onnxruntime",
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)
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# ocr = PaddleOCR(lang="en", engine="onnxruntime") # Use the English model
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# ocr = PaddleOCR(ocr_version="PP-OCRv4", engine="onnxruntime") # Use another PP-OCR version
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# ocr = PaddleOCR(ocr_version="PP-OCRv5", engine="onnxruntime") # Switch to PP-OCRv5 version
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# ocr = PaddleOCR(ocr_version="PP-OCRv4", engine="onnxruntime") # Switch to PP-OCRv4 version
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# ocr = PaddleOCR(device="gpu", engine="onnxruntime") # Use GPU for inference
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# ocr = PaddleOCR(
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# text_detection_model_name="PP-OCRv5_server_det",
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# use_doc_unwarping=False,
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# use_textline_orientation=False,
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# engine="onnxruntime",
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# ) # Switch to the PP-OCRv5_server models
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# ) # Switch to PP-OCRv5 server models
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result = ocr.predict("./general_ocr_002.png")
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for res in result:
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res.print()

‎docs/version3.x/pipeline_usage/OCR.md‎

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@@ -1274,21 +1274,23 @@ paddleocr ocr -i https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_im
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```python
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from paddleocr import PaddleOCR
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# 默认使用 PP-OCRv6 模型
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ocr = PaddleOCR(
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use_doc_orientation_classify=False, # 通过 use_doc_orientation_classify 参数指定不使用文档方向分类模型
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use_doc_unwarping=False, # 通过 use_doc_unwarping 参数指定不使用文本图像矫正模型
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use_textline_orientation=False, # 通过 use_textline_orientation 参数指定不使用文本行方向分类模型
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)
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# ocr = PaddleOCR(lang="en") # 通过 lang 参数来使用英文模型
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# ocr = PaddleOCR(ocr_version="PP-OCRv4") # 通过 ocr_version 参数来使用 PP-OCR 其他版本
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# ocr = PaddleOCR(ocr_version="PP-OCRv5") # 通过 ocr_version 参数切换为 PP-OCRv5 版本
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# ocr = PaddleOCR(ocr_version="PP-OCRv4") # 通过 ocr_version 参数切换为 PP-OCRv4 版本
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# ocr = PaddleOCR(device="gpu") # 通过 device 参数使得在模型推理时使用 GPU
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# ocr = PaddleOCR(
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# text_detection_model_name="PP-OCRv5_server_det",
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# text_recognition_model_name="PP-OCRv5_server_rec",
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# use_doc_orientation_classify=False,
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# use_doc_unwarping=False,
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# use_textline_orientation=False,
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# ) # 更换 PP-OCRv5_server 模型
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# ) # 使用 PP-OCRv5 的 server 模型
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result = ocr.predict("./general_ocr_002.png")
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for res in result:
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res.print()
@@ -1303,14 +1305,16 @@ for res in result:
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```python
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from paddleocr import PaddleOCR
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# 默认使用 PP-OCRv6 模型
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ocr = PaddleOCR(
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use_doc_orientation_classify=False, # 通过 use_doc_orientation_classify 参数指定不使用文档方向分类模型
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use_doc_unwarping=False, # 通过 use_doc_unwarping 参数指定不使用文本图像矫正模型
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use_textline_orientation=False, # 通过 use_textline_orientation 参数指定不使用文本行方向分类模型
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engine="transformers",
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)
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# ocr = PaddleOCR(lang="en", engine="transformers") # 通过 lang 参数来使用英文模型
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# ocr = PaddleOCR(ocr_version="PP-OCRv4", engine="transformers") # 通过 ocr_version 参数来使用 PP-OCR 其他版本
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# ocr = PaddleOCR(ocr_version="PP-OCRv5", engine="transformers") # 通过 ocr_version 参数切换为 PP-OCRv5 版本
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# ocr = PaddleOCR(ocr_version="PP-OCRv4", engine="transformers") # 通过 ocr_version 参数切换为 PP-OCRv4 版本
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# ocr = PaddleOCR(device="gpu", engine="transformers") # 通过 device 参数使得在模型推理时使用 GPU
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# ocr = PaddleOCR(
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# text_detection_model_name="PP-OCRv5_server_det",
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# use_doc_unwarping=False,
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# use_textline_orientation=False,
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# engine="transformers",
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# ) # 更换 PP-OCRv5_server 模型
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# ) # 使用 PP-OCRv5 的 server 模型
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result = ocr.predict("./general_ocr_002.png")
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for res in result:
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res.print()
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```python
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from paddleocr import PaddleOCR
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# 默认使用 PP-OCRv6 模型
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ocr = PaddleOCR(
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use_doc_orientation_classify=False, # 通过 use_doc_orientation_classify 参数指定不使用文档方向分类模型
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use_doc_unwarping=False, # 通过 use_doc_unwarping 参数指定不使用文本图像矫正模型
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use_textline_orientation=False, # 通过 use_textline_orientation 参数指定不使用文本行方向分类模型
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engine="onnxruntime",
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)
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# ocr = PaddleOCR(lang="en", engine="onnxruntime") # 通过 lang 参数来使用英文模型
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# ocr = PaddleOCR(ocr_version="PP-OCRv4", engine="onnxruntime") # 通过 ocr_version 参数来使用 PP-OCR 其他版本
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# ocr = PaddleOCR(ocr_version="PP-OCRv5", engine="onnxruntime") # 通过 ocr_version 参数切换为 PP-OCRv5 版本
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# ocr = PaddleOCR(ocr_version="PP-OCRv4", engine="onnxruntime") # 通过 ocr_version 参数切换为 PP-OCRv4 版本
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# ocr = PaddleOCR(device="gpu", engine="onnxruntime") # 通过 device 参数使得在模型推理时使用 GPU
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# ocr = PaddleOCR(
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# text_detection_model_name="PP-OCRv5_server_det",
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# use_doc_unwarping=False,
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# use_textline_orientation=False,
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# engine="onnxruntime",
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# ) # 更换 PP-OCRv5_server 模型
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# ) # 使用 PP-OCRv5 的 server 模型
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result = ocr.predict("./general_ocr_002.png")
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for res in result:
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res.print()

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