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