重构，精简相关代码，更新ddddocr

Beijng_Daxuexi.py

@@ -1,29 +1,21 @@
 import json
 import re
 import time
-import traceback
-
 import requests
-
 from utility import encrypt, cap_recognize
-
+def study(username,password):
-
+    # 返回1:成功
-def study(username, password, ua):
+    # 返回0:失败
-    # return 1:success;0:fail
-    url = ''
     tryTime = 0
+    url = ''
     while tryTime < 4:
         try:
-            bjySession = requests.session()
+            bjySession = requests.session() # 创建会话
-            bjySession.timeout = 5  # set session timeout
+            bjySession.timeout = 5  # 设置会话超时
-            bjySession.headers.update({"User-Agent": ua, })
+            bjySession.headers.update({"User-Agent": 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36', })
             touch = bjySession.get(url="https://m.bjyouth.net/site/login")
-            capUrl = "https://m.bjyouth.net" + re.findall(
+            capUrl = "https://m.bjyouth.net" + re.findall(r'src="(/site/captcha.+)" alt=', touch.text)[0]
-                r'src="(/site/captcha.+)" alt=', touch.text)[0]
-            if "MIGfMA0GCSqGSIb3DQEBAQUAA4GNADCBiQKBgQD5uIDebA2qU746e/NVPiQSBA0Q" not in touch.text:
-                print("记录的公钥没有出现")
             capText = cap_recognize(bjySession.get(url=capUrl).content)
-            # print(f'验证码识别: {capText}')
             login_r = bjySession.post('https://m.bjyouth.net/site/login',
                                       data={
                                           '_csrf_mobile': bjySession.cookies.get_dict()['_csrf_mobile'],
@@ -31,7 +23,6 @@ def study(username, password, ua):
                                           'Login[username]': encrypt(username),
                                           'Login[verifyCode]': capText
                                       })
-
             if login_r.text == '8':
                 print('Login:识别的验证码错误')
                 continue
@@ -40,9 +31,9 @@ def study(username, password, ua):
                 raise Exception('Login:账号密码错误')
             print('登录成功')
             r = json.loads(bjySession.get("https://m.bjyouth.net/dxx/course").text)
-            # "rize" LOL
             if 'newCourse' not in r:
                 print(r)
+            # newCourse滞后于course中的课程，所以这里用course中的最新课程
             url = r['data']['data'][0]['url']
             title = r['data']['data'][0]['title']
             courseId = r['data']['data'][0]['id']
@@ -50,51 +41,38 @@ def study(username, password, ua):
         except:
             time.sleep(3)
             tryTime += 1
-            print(traceback.format_exc())
 
     if not url:
         print('登入失败,退出')
         return 0
 
-    orgIdTemp = ''
+    info = bjySession.get('https://m.bjyouth.net/dxx/my').json()['data']
-    orgPattern = re.compile(r'\(|（\s*(\d+)\s*）|\)')  # 组织id应该是被括号包的
+    name = info['name'].split('(')[0]
-    learnedInfo = 'https://m.bjyouth.net/dxx/my-study?page=1&limit=15&year=' + time.strftime("%Y", time.localtime())
+    org = info['org'].split('(')[0]
-    haveLearned = bjySession.get(learnedInfo).json()
+    print(f'当前用户: {name} {org}')
-
-    orgID = ""
-    try:
-        orgIdTemp = orgPattern.search(haveLearned['data'][0]['orgname'])
-        orgID = orgIdTemp.group(1)
-    except:
-        print('获取组织id-2')
-        orgIdTemp = orgPattern.search(bjySession.get('https://m.bjyouth.net/dxx/my').json()['data']['org'])
-        if orgIdTemp:
-            orgID = orgIdTemp.group(1)
-
-    if not orgID:
-        orgID = '172442'
-        print(f"无法获取orgID")
 
     nOrgID = int(bjySession.get('https://m.bjyouth.net/dxx/is-league').text)
 
+    learnedInfo = 'https://m.bjyouth.net/dxx/my-study?page=1&limit=15&year=' + time.strftime("%Y", time.localtime())
+    haveLearned = bjySession.get(learnedInfo).json()
+
     if f"学习课程：《{title}》" in list(map(lambda x: x['text'], haveLearned['data'])):
         print(f'{title} 在运行前已完成,退出')
         return 1
     study_url = f"https://m.bjyouth.net/dxx/check"
     r = bjySession.post(study_url, json={"id": str(courseId), "org_id": int(nOrgID)})  # payload
-
     if r.text:
-        print(f'Unexpected response: {r.text}')
+        print(f'开始学习{title}')
         return 0
 
+    
     haveLearned = bjySession.get(learnedInfo).json()
-
-    if int(orgID) != nOrgID:
-        raise Exception('组织id不匹配，如果看到这个请开个issue说下')
-
     if f"学习课程：《{title}》" in list(map(lambda x: x['text'], haveLearned['data'])):
         print(f'{title} 成功完成学习')
         return 1
     else:
-        print(f'完成{title}, 但未在检查中确认')
+        print(f'完成{title}, 但未在已学习列表中找到, 请手动检查')
         return 0
+
+if __name__ == '__main__':
+    study('16634486740','Anye20031003')

ddddocr.py

@@ -5,11 +5,14 @@ warnings.filterwarnings('ignore')
 import io
 import os
 import base64
+import json
+import pathlib
 import onnxruntime
 from PIL import Image
 import numpy as np
 
 
+
 def base64_to_image(img_base64):
     img_data = base64.b64decode(img_base64)
     return Image.open(io.BytesIO(img_data))
@@ -21,24 +24,37 @@ def get_img_base64(single_image_path):
         return img_base64.decode()
 
 
+class TypeError(Exception):
+    pass
+
+
 class DdddOcr(object):
-    def __init__(self, use_gpu: bool = False, device_id: int = 0):
+    def __init__(self, ocr: bool = True, det: bool = False, use_gpu: bool = False,
+                 device_id: int = 0, import_onnx_path: str = "", charsets_path: str = ""):
+        if not hasattr(Image, 'ANTIALIAS'):
+            setattr(Image, 'ANTIALIAS', Image.LANCZOS)
+        self.use_import_onnx = False
+        self.__word = False
+        self.__resize = []
+        self.__channel = 1
+        if import_onnx_path != "":
+            det = False
+            ocr = False
+            self.__graph_path = import_onnx_path
+            with open(charsets_path, 'r', encoding="utf-8") as f:
+                info = json.loads(f.read())
+            self.__charset = info['charset']
+            self.__word = info['word']
+            self.__resize = info['image']
+            self.__channel = info['channel']
+            self.use_import_onnx = True
+
+        if det:
+            ocr = False
+            self.__graph_path = os.path.join(os.path.dirname(__file__), 'common_det.onnx')
+            self.__charset = []
+        if ocr:
                 self.__graph_path = os.path.join(os.path.dirname(__file__), 'common.onnx')
-        if use_gpu:
-            self.__providers = [
-                ('CUDAExecutionProvider', {
-                    'device_id': device_id,
-                    'arena_extend_strategy': 'kNextPowerOfTwo',
-                    'cuda_mem_limit': 2 * 1024 * 1024 * 1024,
-                    'cudnn_conv_algo_search': 'EXHAUSTIVE',
-                    'do_copy_in_default_stream': True,
-                }),
-            ]
-        else:
-            self.__providers = [
-                'CPUExecutionProvider',
-            ]
-        self.__ort_session = onnxruntime.InferenceSession(self.__graph_path, providers=self.__providers)
                 self.__charset = ["", "笤", "谴", "膀", "荔", "佰", "电", "臁", "矍", "同", "奇", "芄", "吠", "6",
                                   "曛", "荇", "砥", "蹅", "晃", "厄", "殣", "ｃ", "辱", "钋", "杻", "價", "眙", "鴿", "⒄", "裙",
                                   "训", "涛", "酉", "挞", "忙", "怍", "︰", "镍", "檐", "眯", "茓", "辖", "淩", "啟", "蜀", "芟",
@@ -553,20 +569,71 @@ class DdddOcr(object):
                                   "够", "璧", "晡", "擘", "毂", "御", "葚", "忱", "觞", "瑁", "唇", "罡", "剽", "殡", "沛", "帻",
                                   "举", "瞓", "谬", "溝", "言", "哽", "婿", "猿", "跗", "獴", "俜", "呙", "弗", "凿", "窭", "铌",
                                   "友", "唉", "怫", "荘"]
-
+        self.det = det
-    def classification(self, img_bytes: bytes = None, img_base64: str = None):
+        if use_gpu:
-        if img_bytes:
+            self.__providers = [
-            image = Image.open(io.BytesIO(img_bytes))
+                ('CUDAExecutionProvider', {
+                    'device_id': device_id,
+                    'arena_extend_strategy': 'kNextPowerOfTwo',
+                    'cuda_mem_limit': 2 * 1024 * 1024 * 1024,
+                    'cudnn_conv_algo_search': 'EXHAUSTIVE',
+                    'do_copy_in_default_stream': True,
+                }),
+            ]
         else:
-            image = base64_to_image(img_base64)
+            self.__providers = [
-        image = image.resize((int(image.size[0] * (64 / image.size[1])), 64), Image.LANCZOS).convert('L')
+                'CPUExecutionProvider',
+            ]
+        if ocr or det or self.use_import_onnx:
+            self.__ort_session = onnxruntime.InferenceSession(self.__graph_path, providers=self.__providers)
+
+    def classification(self, img):
+        if not isinstance(img, (bytes, str, pathlib.PurePath, Image.Image)):
+            raise TypeError("未知图片类型")
+        if isinstance(img, bytes):
+            image = Image.open(io.BytesIO(img))
+        elif isinstance(img, Image.Image):
+            image = img.copy()
+        elif isinstance(img, str):
+            image = base64_to_image(img)
+        else:
+            assert isinstance(img, pathlib.PurePath)
+            image = Image.open(img)
+        if not self.use_import_onnx:
+            image = image.resize((int(image.size[0] * (64 / image.size[1])), 64), Image.ANTIALIAS).convert('L')
+        else:
+            if self.__resize[0] == -1:
+                if self.__word:
+                    image = image.resize((self.__resize[1], self.__resize[1]), Image.ANTIALIAS)
+                else:
+                    image = image.resize((int(image.size[0] * (self.__resize[1] / image.size[1])), self.__resize[1]), Image.ANTIALIAS)
+            else:
+                image = image.resize((self.__resize[0], self.__resize[1]), Image.ANTIALIAS)
+            if self.__channel == 1:
+                image = image.convert('L')
+            else:
+                image = image.convert('RGB')
         image = np.array(image).astype(np.float32)
         image = np.expand_dims(image, axis=0) / 255.
+        if not self.use_import_onnx:
             image = (image - 0.5) / 0.5
-        ort_inputs = {'input1': np.array([image])}
+        else:
+            if self.__channel == 1:
+                image = (image - 0.456) / 0.224
+            else:
+                image = (image - np.array([0.485, 0.456, 0.406])) / np.array([0.229, 0.224, 0.225])
+                image = image[0]
+                image = image.transpose((2, 0, 1))
+
+        ort_inputs = {'input1': np.array([image]).astype(np.float32)}
         ort_outs = self.__ort_session.run(None, ort_inputs)
         result = []
+
         last_item = 0
+        if self.__word:
+            for item in ort_outs[1]:
+                result.append(self.__charset[item])
+        else:
             for item in ort_outs[0][0]:
                 if item == last_item:
                     continue

main.py

@@ -1,24 +0,0 @@
-import os
-import time
-import sys
-from study import study
-
-ua = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36'
-
-accounts=[('*********', '*********')]
-print(f'账号数量：{len(accounts)}')
-successful = 0
-count = 0
-for username, password in accounts:
-    if username=='********':
-        continue
-    count += 1
-    print(f'--User {count}--')
-    if study(username, password, ua):
-        successful += 1
-
-failed = count - successful
-print('--Summary--')
-print(f'成功：{successful}，失败：{failed}')
-if failed != 0:
-    raise Exception(f'有{failed}个失败！')