# 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 import sys __dir__ = os.path.dirname(os.path.abspath(__file__)) sys.path.append(os.path.abspath(os.path.join(__dir__, '../'))) import copy import cv2 import numpy as np from python.predict_rec import RecPredictor from python.predict_det import DetPredictor from utils import logger from utils import config from utils.get_image_list import get_image_list class SystemPredictor(object): def __init__(self, config): self.rec_predictor = RecPredictor(config) self.det_predictor = DetPredictor(config) def predict(self, img): output = [] results = self.det_predictor.predict(img) for result in results: print(result) xmin, xmax, ymin, ymax = result["bbox"].astype("int") crop_img = img[xmin:xmax, ymin:ymax, :].copy() rec_results = self.rec_predictor.predict(crop_img) result["featrue"] = rec_results output.append(result) return output def main(config): system_predictor = SystemPredictor(config) image_list = get_image_list(config["Global"]["infer_imgs"]) assert config["Global"]["batch_size"] == 1 for idx, image_file in enumerate(image_list): img = cv2.imread(image_file)[:, :, ::-1] output = system_predictor.predict(img) print(output) return if __name__ == "__main__": args = config.parse_args() config = config.get_config(args.config, overrides=args.override, show=True) main(config)