55 lines
1.8 KiB
Python
55 lines
1.8 KiB
Python
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# 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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# pylint: disable=doc-string-missing
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from paddle_serving_client import Client
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import sys
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import numpy as np
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import base64
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import os
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import cv2
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from paddle_serving_app.reader import Sequential, URL2Image, ResizeByFactor
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from paddle_serving_app.reader import Div, Normalize, Transpose
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from ocr_reader import OCRReader
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client = Client()
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# TODO:load_client need to load more than one client model.
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# this need to figure out some details.
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client.load_client_config(sys.argv[1:])
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client.connect(["127.0.0.1:9293"])
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import paddle
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test_img_dir = "test_img/"
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ocr_reader = OCRReader(char_dict_path="../../ppocr/utils/ppocr_keys_v1.txt")
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def cv2_to_base64(image):
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return base64.b64encode(image).decode(
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'utf8') #data.tostring()).decode('utf8')
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for img_file in os.listdir(test_img_dir):
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with open(os.path.join(test_img_dir, img_file), 'rb') as file:
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image_data = file.read()
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image = cv2_to_base64(image_data)
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res_list = []
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fetch_map = client.predict(
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feed={"x": image}, fetch=["save_infer_model/scale_0.tmp_1"], batch=True)
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one_batch_res = ocr_reader.postprocess(fetch_map, with_score=True)
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for res in one_batch_res:
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res_list.append(res[0])
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res = {"res": str(res_list)}
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print(res)
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