123456789101112131415161718192021222324252627282930313233343536373839404142434445 |
- # 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.
- # -*- coding: utf-8 -*-
- import requests
- import json
- import cv2
- import base64
- import os, sys
- import time
- def cv2_to_base64(image):
- #data = cv2.imencode('.jpg', image)[1]
- return base64.b64encode(image).decode(
- 'utf8') #data.tostring()).decode('utf8')
- headers = {"Content-type": "application/json"}
- url = "http://127.0.0.1:9292/ocr/prediction"
- test_img_dir = "../../../doc/imgs/"
- for idx, img_file in enumerate(os.listdir(test_img_dir)):
- with open(os.path.join(test_img_dir, img_file), 'rb') as file:
- image_data1 = file.read()
- image = cv2_to_base64(image_data1)
- for i in range(1):
- data = {"feed": [{"image": image}], "fetch": ["save_infer_model/scale_0.tmp_1"]}
- r = requests.post(url=url, headers=headers, data=json.dumps(data))
- print(r.json())
- test_img_dir = "../../../doc/imgs/"
- print("==> total number of test imgs: ", len(os.listdir(test_img_dir)))
|