# 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(__dir__) sys.path.append(os.path.abspath(os.path.join(__dir__, '..'))) sys.path.append(os.path.abspath(os.path.join(__dir__, '../../'))) from ppocr.utils.utility import initial_logger logger = initial_logger() import cv2 import numpy as np import time from PIL import Image from ppocr.utils.utility import get_image_file_list from tools.infer.utility import draw_ocr, draw_boxes import requests import json import base64 def cv2_to_base64(image): return base64.b64encode(image).decode('utf8') def draw_server_result(image_file, res): img = cv2.imread(image_file) image = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB)) if len(res) == 0: return np.array(image) keys = res[0].keys() if 'text_region' not in keys: # for rec or clas, draw function is invalid logger.info("draw function is invalid for rec or clas!") return None elif 'text' not in keys: # for ocr_det logger.info("draw text boxes only!") boxes = [] for dno in range(len(res)): boxes.append(res[dno]['text_region']) boxes = np.array(boxes) draw_img = draw_boxes(image, boxes) return draw_img else: # for ocr_system logger.info("draw boxes and texts!") boxes = [] texts = [] scores = [] for dno in range(len(res)): boxes.append(res[dno]['text_region']) texts.append(res[dno]['text']) scores.append(res[dno]['confidence']) boxes = np.array(boxes) scores = np.array(scores) draw_img = draw_ocr(image, boxes, texts, scores, drop_score=0.5, font_path="../../doc/simfang.ttf") return draw_img def main(image_path): image_file_list = get_image_file_list(image_path) is_visualize = True headers = {"Content-type": "application/json"} url = "http://127.0.0.1:9292/ocr/prediction" cnt = 0 total_time = 0 for image_file in image_file_list: img = open(image_file, 'rb').read() if img is None: logger.info("error in loading image:{}".format(image_file)) continue # 发送HTTP请求 starttime = time.time() data = {"feed": [{"image": cv2_to_base64(img)}], "fetch": ["res"]} r = requests.post(url=url, headers=headers, data=json.dumps(data)) elapse = time.time() - starttime total_time += elapse logger.info("Predict time of %s: %.3fs" % (image_file, elapse)) res = r.json()['result'] logger.info(res) if is_visualize: draw_img = draw_server_result(image_file, res) if draw_img is not None: draw_img_save = "./server_results/" if not os.path.exists(draw_img_save): os.makedirs(draw_img_save) cv2.imwrite( os.path.join(draw_img_save, os.path.basename(image_file)), draw_img[:, :, ::-1]) logger.info("The visualized image saved in {}".format( os.path.join(draw_img_save, os.path.basename(image_file)))) cnt += 1 if cnt % 100 == 0: logger.info("{} processed".format(cnt)) logger.info("avg time cost: {}".format(float(total_time) / cnt)) if __name__ == '__main__': if len(sys.argv) != 2: logger.info("Usage: %s image_path" % sys.argv[0]) else: image_path = sys.argv[1] main(image_path)