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https://github.com/RapidAI/RapidOCR.git
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75 lines
2.8 KiB
Python
75 lines
2.8 KiB
Python
# Copyright (c) 2020 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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import warnings
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import yaml
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from onnxruntime import (get_available_providers, get_device,
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SessionOptions, InferenceSession)
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class OrtInferSession(object):
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def __init__(self, config):
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sess_opt = SessionOptions()
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sess_opt.log_severity_level = 4
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sess_opt.enable_cpu_mem_arena = False
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cuda_ep = 'CUDAExecutionProvider'
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cpu_ep = 'CPUExecutionProvider'
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EP_list = []
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if config['use_cuda'] and get_device() == 'GPU' \
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and cuda_ep in get_available_providers():
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EP_list = [(cuda_ep, config[cuda_ep])]
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EP_list.append(cpu_ep)
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self.session = InferenceSession(config['model_path'],
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sess_options=sess_opt,
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providers=EP_list)
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if config['use_cuda'] and cuda_ep not in self.session.get_providers():
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warnings.warn(f'{cuda_ep} is not avaiable for current env, the inference part is automatically shifted to be executed under {cpu_ep}.\n'
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'Please ensure the installed onnxruntime-gpu version matches your cuda and cudnn version, '
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'you can check their relations from the offical web site: '
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'https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html',
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RuntimeWarning)
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def get_input_name(self, input_idx=0):
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return self.session.get_inputs()[input_idx].name
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def get_output_name(self, output_idx=0):
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return self.session.get_outputs()[output_idx].name
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def read_yaml(yaml_path):
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with open(yaml_path, 'rb') as f:
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data = yaml.load(f, Loader=yaml.Loader)
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return data
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class ClsPostProcess(object):
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""" Convert between text-label and text-index """
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def __init__(self, label_list):
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super(ClsPostProcess, self).__init__()
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self.label_list = label_list
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def __call__(self, preds, label=None):
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pred_idxs = preds.argmax(axis=1)
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decode_out = [(self.label_list[idx], preds[i, idx])
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for i, idx in enumerate(pred_idxs)]
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if label is None:
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return decode_out
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label = [(self.label_list[idx], 1.0) for idx in label]
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return decode_out, label |