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Dockerfile

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+FROM python:3.8-slim-buster
+
+RUN mkdir /app
+
+COPY ./*.txt ./*.py ./*.sh ./*.onnx /app/
+
+
+RUN cd /app \
+    && python3 -m pip install --upgrade pip\
+    && pip3 install --no-cache-dir -r requirements.txt\
+    && rm -rf /tmp/* && rm -rf /root/.cache/* \
+    && apt-get --allow-releaseinfo-change update && apt install libgl1-mesa-glx libglib2.0-0 -y
+
+WORKDIR /app
+
+CMD ["python3", "ocr_server.py", "--port", "9898", "--ocr", "--det"]

LICENSE

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README.md

@@ -1,9 +1,85 @@
----
-title: ocr
-emoji: 🏆
-colorFrom: gray
-colorTo: red
-sdk: docker
-pinned: false
----
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# ocr_api_server
+使用ddddocr的最简api搭建项目，支持docker
+
+**建议python版本3.7-3.9 64位**
+
+再有不好好看文档的我就不管了啊！！！
+
+# 运行方式
+
+## 最简单运行方式
+
+```shell
+# 安装依赖
+pip install -r requirements.txt -i https://pypi.douban.com/simple
+
+# 运行  可选参数如下
+# --port 9898 指定端口,默认为9898
+# --ocr 开启ocr模块 默认开启
+# --old 只有ocr模块开启的情况下生效 默认不开启
+# --det 开启目标检测模式
+
+# 最简单运行方式，只开启ocr模块并以新模型计算
+python ocr_server.py --port 9898 --ocr
+
+# 开启ocr模块并使用旧模型计算
+python ocr_server.py --port 9898 --ocr --old
+
+# 只开启目标检测模块
+python ocr_server.py --port 9898  --det
+
+# 同时开启ocr模块以及目标检测模块
+python ocr_server.py --port 9898 --ocr --det
+
+# 同时开启ocr模块并使用旧模型计算以及目标检测模块
+python ocr_server.py --port 9898 --ocr --old --det
+
+```
+
+## docker运行方式(目测只能在Linux下部署)
+
+```shell
+git clone https://github.com/sml2h3/ocr_api_server.git
+# docker怎么安装？百度吧
+
+cd ocr_api_server
+
+# 修改entrypoint.sh中的参数，具体参数往上翻，默认9898端口，同时开启ocr模块以及目标检测模块
+
+# 编译镜像
+docker build -t ocr_server:v1 .
+
+# 运行镜像
+docker run -p 9898:9898 -d ocr_server:v1
+
+```
+
+# 接口
+
+**具体请看test_api.py文件**
+
+```python
+# 1、测试是否启动成功，可以通过直接GET访问http://{host}:{port}/ping来测试，如果返回pong则启动成功
+
+# 2、OCR/目标检测请求接口格式：
+
+# http://{host}:{port}/{opt}/{img_type}/{ret_type}
+# opt：操作类型 ocr=OCR det=目标检测 slide=滑块（match和compare两种算法，默认为compare)
+# img_type: 数据类型 file=文件上传方式 b64=base64(imgbyte)方式 默认为file方式
+# ret_type: 返回类型 json=返回json（识别出错会在msg里返回错误信息） text=返回文本格式（识别出错时回直接返回空文本）
+
+# 例子：
+
+# OCR请求
+# resp = requests.post("http://{host}:{port}/ocr/file", files={'image': image_bytes})
+# resp = requests.post("http://{host}:{port}/ocr/b64/text", data=base64.b64encode(file).decode())
+
+# 目标检测请求
+# resp = requests.post("http://{host}:{port}/det/file", files={'image': image_bytes})
+# resp = requests.post("http://{host}:{port}/det/b64/json", data=base64.b64encode(file).decode())
+
+# 滑块识别请求
+# resp = requests.post("http://{host}:{port}/slide/match/file", files={'target_img': target_bytes, 'bg_img': bg_bytes})
+# jsonstr = json.dumps({'target_img': target_b64str, 'bg_img': bg_b64str})
+# resp = requests.post("http://{host}:{port}/slide/compare/b64", files=base64.b64encode(jsonstr.encode()).decode())
+```

ocr_server.py

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+# encoding=utf-8
+import argparse
+import base64
+import json
+
+import ddddocr
+from flask import Flask, request
+
+parser = argparse.ArgumentParser(description="使用ddddocr搭建的最简api服务")
+parser.add_argument("-p", "--port", type=int, default=9898)
+parser.add_argument("--ocr", action="store_true", help="开启ocr识别")
+parser.add_argument("--old", action="store_true", help="OCR是否启动旧模型")
+parser.add_argument("--det", action="store_true", help="开启目标检测")
+
+args = parser.parse_args()
+
+app = Flask(__name__)
+
+
+class Server(object):
+    def __init__(self, ocr=True, det=False, old=False):
+        self.ocr_option = ocr
+        self.det_option = det
+        self.old_option = old
+        self.ocr = None
+        self.det = None
+        if self.ocr_option:
+            print("ocr模块开启")
+            if self.old_option:
+                print("使用OCR旧模型启动")
+                self.ocr = ddddocr.DdddOcr(old=True)
+            else:
+                print("使用OCR新模型启动，如需要使用旧模型，请额外添加参数  --old开启")
+                self.ocr = ddddocr.DdddOcr()
+        else:
+            print("ocr模块未开启，如需要使用，请使用参数  --ocr开启")
+        if self.det_option:
+            print("目标检测模块开启")
+            self.det = ddddocr.DdddOcr(det=True)
+        else:
+            print("目标检测模块未开启，如需要使用，请使用参数  --det开启")
+
+    def classification(self, img: bytes):
+        if self.ocr_option:
+            return self.ocr.classification(img)
+        else:
+            raise Exception("ocr模块未开启")
+
+    def detection(self, img: bytes):
+        if self.det_option:
+            return self.det.detection(img)
+        else:
+            raise Exception("目标检测模块模块未开启")
+
+    def slide(self, target_img: bytes, bg_img: bytes, algo_type: str):
+        dddd = self.ocr or self.det or ddddocr.DdddOcr(ocr=False)
+        if algo_type == 'match':
+            return dddd.slide_match(target_img, bg_img)
+        elif algo_type == 'compare':
+            return dddd.slide_comparison(target_img, bg_img)
+        else:
+            raise Exception(f"不支持的滑块算法类型: {algo_type}")
+
+server = Server(ocr=args.ocr, det=args.det, old=args.old)
+
+
+def get_img(request, img_type='file', img_name='image'):
+    if img_type == 'b64':
+        img = base64.b64decode(request.get_data()) # 
+        try: # json str of multiple images
+            dic = json.loads(img)
+            img = base64.b64decode(dic.get(img_name).encode())
+        except Exception as e: # just base64 of single image
+            pass
+    else:
+        img = request.files.get(img_name).read()
+    return img
+
+
+def set_ret(result, ret_type='text'):
+    if ret_type == 'json':
+        if isinstance(result, Exception):
+            return json.dumps({"status": 200, "result": "", "msg": str(result)})
+        else:
+            return json.dumps({"status": 200, "result": result, "msg": ""})
+        # return json.dumps({"succ": isinstance(result, str), "result": str(result)})
+    else:
+        if isinstance(result, Exception):
+            return ''
+        else:
+            return str(result).strip()
+
+
+@app.route('/<opt>/<img_type>', methods=['POST'])
+@app.route('/<opt>/<img_type>/<ret_type>', methods=['POST'])
+def ocr(opt, img_type='file', ret_type='text'):
+    try:
+        img = get_img(request, img_type)
+        if opt == 'ocr':
+            result = server.classification(img)
+        elif opt == 'det':
+            result = server.detection(img)
+        else:
+            raise f"<opt={opt}> is invalid"
+        return set_ret(result, ret_type)
+    except Exception as e:
+        return set_ret(e, ret_type)
+
+@app.route('/slide/<algo_type>/<img_type>', methods=['POST'])
+@app.route('/slide/<algo_type>/<img_type>/<ret_type>', methods=['POST'])
+def slide(algo_type='compare', img_type='file', ret_type='text'):
+    try:
+        target_img = get_img(request, img_type, 'target_img')
+        bg_img = get_img(request, img_type, 'bg_img')
+        result = server.slide(target_img, bg_img, algo_type)
+        return set_ret(result, ret_type)
+    except Exception as e:
+        return set_ret(e, ret_type)
+
+@app.route('/ping', methods=['GET'])
+def ping():
+    return "pong"
+
+
+if __name__ == '__main__':
+    app.run(host="0.0.0.0", port=args.port)

requirements.txt

@@ -0,0 +1,2 @@
+ddddocr>=1.4.7
+flask

test_api.py

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+#!/usr/bin/python3.6
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2021 #
+# @Time    : 2022/1/6 23:28
+# @Author  : sml2h3
+# @Email   : sml2h3@gmail.com
+# @File    : test_api.py
+# @Software: PyCharm
+import base64
+import json
+import requests
+
+print(' ')
+# ******************OCR识别部分开始******************
+host = "http://127.0.0.1:9898"
+# 目标检测就把ocr改成det,其他相同
+# 方式一
+file = open(r'test.jpg', 'rb').read()
+# file = open(r'test_calc.png', 'rb').read()
+
+
+api_url = f"{host}/ocr/file"
+resp = requests.post(api_url, files={'image': file})
+print(f"{api_url=}, {resp.text=}")
+
+api_url = f"{host}/ocr/file/json"
+resp = requests.post(api_url, files={'image': file})
+print(f"{api_url=}, {resp.text=}")
+
+api_url = f"{host}/ocr/b64"
+resp = requests.post(api_url, data=base64.b64encode(file).decode())
+print(f"{api_url=}, {resp.text=}")
+
+api_url = f"{host}/ocr/b64/json"
+resp = requests.post(api_url, data=base64.b64encode(file).decode())
+print(f"{api_url=}, {resp.text=}")
+
+api_url = f"{host}/det/file"
+resp = requests.post(api_url, files={'image': file})
+print(f"{api_url=}, {resp.text=}")
+
+api_url = f"{host}/det/file/json"
+resp = requests.post(api_url, files={'image': file})
+print(f"{api_url=}, {resp.text=}")
+
+# 滑块识别
+
+target_file = open(r'match_target.png', 'rb').read()
+bg_file = open(r'match_bg.png', 'rb').read()
+
+api_url = f"{host}/slide/match/file"
+resp = requests.post(api_url, files={'target_img': target_file, 'bg_img': bg_file})
+print(f"{api_url=}, {resp.text=}")
+
+api_url = f"{host}/slide/match/file/json"
+resp = requests.post(api_url, files={'target_img': target_file, 'bg_img': bg_file})
+print(f"{api_url=}, {resp.text=}")
+
+api_url = f"{host}/slide/match/b64"
+target_b64str = base64.b64encode(target_file).decode()
+bg_b64str = base64.b64encode(bg_file).decode()
+jsonstr = json.dumps({'target_img': target_b64str, 'bg_img': bg_b64str})
+resp = requests.post(api_url, data=base64.b64encode(jsonstr.encode()).decode())
+print(f"{api_url=}, {resp.text=}")
+
+api_url = f"{host}/slide/match/b64/json"
+resp = requests.post(api_url, data=base64.b64encode(jsonstr.encode()).decode())
+print(f"{api_url=}, {resp.text=}")
+
+target_file = open(r'compare_target.jpg', 'rb').read()
+bg_file = open(r'compare_bg.jpg', 'rb').read()
+
+api_url = f"{host}/slide/compare/file"
+resp = requests.post(api_url, files={'target_img': target_file, 'bg_img': bg_file})
+print(f"{api_url=}, {resp.text=}")
+
+api_url = f"{host}/slide/compare/file/json"
+resp = requests.post(api_url, files={'target_img': target_file, 'bg_img': bg_file})
+print(f"{api_url=}, {resp.text=}")
+
+api_url = f"{host}/slide/compare/b64"
+target_b64str = base64.b64encode(target_file).decode()
+bg_b64str = base64.b64encode(bg_file).decode()
+jsonstr = json.dumps({'target_img': target_b64str, 'bg_img': bg_b64str})
+resp = requests.post(api_url, data=base64.b64encode(jsonstr.encode()).decode())
+print(f"{api_url=}, {resp.text=}")
+
+api_url = f"{host}/slide/compare/b64/json"
+resp = requests.post(api_url, data=base64.b64encode(jsonstr.encode()).decode())
+print(f"{api_url=}, {resp.text=}")
+
+# 方式二
+
+# 获取验证码图片
+# headers = {
+#     "Content-Type": "application/x-www-form-urlencoded; charset=UTF-8",
+#     "User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4195.1 Safari/537.36"
+# }
+# resp = requests.get('https://data.gdcic.net/Dop/CheckCode.aspx?codemark=408.15173910730016', headers=headers, verify=False)
+# captcha_img = resp.content
+#
+# 识别
+# resp = requests.post(api_url, files={'image': captcha_img})
+# print('验证码结果', resp.text)
+#
+# # 保存验证码图片以供验证
+# with open('captcha.jpg', 'wb') as f:
+#     f.write(captcha_img)
+
+# ******************OCR识别部分开始******************