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index aaa1c5b1..00000000 --- a/python/examples/ocr_detection/text_det_client.py +++ /dev/null @@ -1,47 +0,0 @@ -# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. - -import os -from paddle_serving_client import Client -from paddle_serving_app.reader import Sequential, File2Image, ResizeByFactor -from paddle_serving_app.reader import Div, Normalize, Transpose -from paddle_serving_app.reader import DBPostProcess, FilterBoxes - -client = Client() -client.load_client_config("ocr_det_client/serving_client_conf.prototxt") -client.connect(["127.0.0.1:9494"]) - -read_image_file = File2Image() -preprocess = Sequential([ - ResizeByFactor(32, 960), Div(255), - Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]), Transpose( - (2, 0, 1)) -]) -post_func = DBPostProcess({ - "thresh": 0.3, - "box_thresh": 0.5, - "max_candidates": 1000, - "unclip_ratio": 1.5, - "min_size": 3 -}) -filter_func = FilterBoxes(10, 10) - -img = read_image_file(name) -ori_h, ori_w, _ = img.shape -img = preprocess(img) -new_h, new_w, _ = img.shape -ratio_list = [float(new_h) / ori_h, float(new_w) / ori_w] -outputs = client.predict(feed={"image": img}, fetch=["concat_1.tmp_0"]) -dt_boxes_list = post_func(outputs["concat_1.tmp_0"], [ratio_list]) -dt_boxes = filter_func(dt_boxes_list[0], [ori_h, ori_w]) -- GitLab