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82 lines
2.9 KiB
Python
82 lines
2.9 KiB
Python
# Copyright (c) 2026 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from typing import Any, Optional
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from ..base import Inference
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from ..shared.doc_parsing_result_adapters import parse_local_doc_parsing_result
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from ..shared.input_adapters import LOCAL_INPUT_ADAPTER, InputAdapter
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from ..shared.local_sync_runner import LocalSyncRunner
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from ..types import DocParsingResult, InferenceRequest
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from .params import PP_STRUCTUREV3_DEFAULT_PARAMS, PP_STRUCTUREV3_RUNTIME_PARAMS
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try:
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from paddleocr import PPStructureV3
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LOCAL_PPSTRUCTURE_AVAILABLE = True
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except ImportError:
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LOCAL_PPSTRUCTURE_AVAILABLE = False
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class PPStructureV3LocalInference(Inference):
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def __init__(self, config: Optional[str] = None, device: Optional[str] = None):
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self._config = config
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self._device = device
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self._inference: Optional[Any] = None
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self._wrapper: Optional[LocalSyncRunner] = None
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@property
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def input_adapter(self) -> InputAdapter:
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return LOCAL_INPUT_ADAPTER
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async def start(self) -> None:
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if not LOCAL_PPSTRUCTURE_AVAILABLE:
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raise RuntimeError("PPStructureV3 is not locally available")
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try:
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self._inference = PPStructureV3(
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paddlex_config=self._config, device=self._device
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)
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self._wrapper = LocalSyncRunner(self._inference)
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except Exception as e:
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raise RuntimeError(
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f"Failed to create PPStructureV3 inference: {str(e)}"
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) from e
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async def stop(self) -> None:
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if self._wrapper:
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await self._wrapper.close()
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self._wrapper = None
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async def predict(self, request: InferenceRequest) -> DocParsingResult:
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if not self._wrapper:
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raise RuntimeError("Inference not started")
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with self.input_adapter.prepare(request.input_data) as processed_input:
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result = await self._wrapper.call(
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self._wrapper.inference.predict,
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processed_input,
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**request.runtime_params,
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)
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return self._parse_result(result)
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def get_valid_params(self) -> set[str]:
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return set(PP_STRUCTUREV3_RUNTIME_PARAMS.keys())
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def get_default_params(self) -> dict[str, Any]:
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return PP_STRUCTUREV3_DEFAULT_PARAMS.copy()
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def _parse_result(self, result: Any) -> DocParsingResult:
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return parse_local_doc_parsing_result(result)
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