A cross platform OCR API Library based on OnnxRuntime.
Project description
rapidocr-api
Use
-
Install
rapidocr_api
$ pip install rapidocr_api
-
Run
- Usage:
$ rapidocr_api -h usage: rapidocr_api [-h] [-ip IP] [-p PORT] optional arguments: -h, --help show this help message and exit -ip IP, --ip IP IP Address -p PORT, --port PORT IP port
- Example:
$ rapidocr_api -ip 0.0.0.0 -p 9003
- Usage:
-
Use
- with curl
$ curl -F image_file=@1.png http://0.0.0.0:9003/ocr
- with python
- Send image data by file format.
import requests url = 'http://localhost:9003/ocr' img_path = '../python/tests/test_files/ch_en_num.jpg' with open(img_path, 'rb') as f: file_dict = {'image_file': (img_path, f, 'image/png')} response = requests.post(url, files=file_dict, timeout=60) print(response.json())
- Send image data by base64 format.
import base64 import requests url = 'http://localhost:9003/ocr' img_path = '../python/tests/test_files/ch_en_num.jpg' with open(img_path, 'rb') as fa: img_str = base64.b64encode(fa.read()) payload = {'image_data': img_str} resp = requests.post(url, data=payload) print(resp.json())
- Send image data by file format.
- with curl
-
Output
Click to expand
{ "0": { "rec_txt": "香港深圳抽血,", "dt_boxes": [ [265, 18], [472, 231], [431, 271], [223, 59] ], "score": "0.8175641223788261" }, "1": { "rec_txt": "专业查性别", "dt_boxes": [ [388, 15], [636, 257], [587, 307], [339, 65] ], "score": "0.8293875356515249" }, "2": { "rec_txt": "专业鉴定B超单", "dt_boxes": [ [215, 84], [509, 413], [453, 463], [159, 134] ], "score": "0.8626169338822365" }, "3": { "rec_txt": "b超仪器查性别", "dt_boxes": [ [128, 135], [430, 478], [366, 534], [64, 192] ], "score": "0.8449362441897392" }, "4": { "rec_txt": "加微信eee", "dt_boxes": [ [58, 189], [268, 450], [209, 498], [0, 236] ], "score": "0.8176911813872201" }, "5": { "rec_txt": "可邮寄", "dt_boxes": [ [493, 261], [617, 384], [577, 423], [454, 300] ], "score": "0.7494261413812637" } }
See details for RapidOCR.
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