rapidocr_api

简介 link

• 该包是将rapidocr_onnxruntime库做了API封装，采用FastAPI + uvicorn实现。
• 定位是一个快速调用rapidocr_onnxruntime的API接口，没有考虑多进程处理并发请求，如果有这需求的小伙伴，可以看看gunicorn等。

安装 link

  pip install rapidocr_api
  

启动服务端 link

• 用法:

    $ 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
    

• 启动:

    rapidocr_api -ip 0.0.0.0 -p 9003
    

调用 link

Curl调用 link

  curl -F image_file=@1.png http://0.0.0.0:9003/ocr
  

Python调用 link

  import requests

url = 'http://localhost:9003/ocr'
img_path = '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())
  

  import base64
import requests

url = 'http://localhost:9003/ocr'
img_path = '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}
response = requests.post(url, data=payload)

print(response.json())
  

API输出 link

• 输出结果说明：
  • 如果图像中存在文字，则会输出字典格式，具体介绍如下：

      {
    "0": {
        "rec_txt": "香港深圳抽血，",  # 识别的文本
        "dt_boxes": [  # 依次为左上角 → 右上角 → 右下角 → 左下角
            [265, 18],
            [472, 231],
            [431, 271],
            [223, 59]
        ],
        "score": "0.8175641223788261"  # 置信度
        }
    }
      

  • 如果没有检测到文字，则会输出空字典({})。
• 示例结果：

    {
      "0": {
          "rec_txt": "8月26日！",
          "dt_boxes": [
              [333.0, 72.0],
              [545.0, 40.0],
              [552.0, 90.0],
              [341.0, 122.0]
          ],
          "score": "0.7342076812471662"
      },
      "1": {
          "rec_txt": "澳洲名校招生信息",
          "dt_boxes": [
              [266.0, 163.0],
              [612.0, 116.0],
              [619.0, 163.0],
              [272.0, 210.0]
          ],
          "score": "0.8261737492349412"
      },
      "2": {
          "rec_txt": "解读！！",
          "dt_boxes": [
              [341.0, 187.0],
              [595.0, 179.0],
              [598.0, 288.0],
              [344.0, 296.0]
          ],
          "score": "0.6152311325073242"
      },
      "3": {
          "rec_txt": "Rules...",
          "dt_boxes": [
              [446.0, 321.0],
              [560.0, 326.0],
              [559.0, 352.0],
              [445.0, 347.0]
          ],
          "score": "0.8704230123096042"
      }
  }