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+import asyncio
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+import aiohttp
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+import aiofiles
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+import json
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+import os
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+from typing import Dict, Any, Tuple, List
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+from datetime import datetime
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+
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+# --- 配置区域 (可根据需要修改) ---
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+INFERENCE_SERVICE_URL = "http://192.168.77.78:7744"
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+STORAGE_SERVICE_URL = "http://192.168.77.78:7745"
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+
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+# 固定的处理类型映射
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+SCORE_TYPES = [
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+ "front_corner_edge",
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+ "front_face",
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+ "back_corner_edge",
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+ "back_face"
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+]
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+
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+SCORE_TO_IMAGE_TYPE_MAP = {
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+ "front_corner_edge": "front_edge",
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+ "front_face": "front_face",
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+ "back_corner_edge": "back_edge",
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+ "back_face": "back_face"
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+}
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+
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+
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+# --- 辅助功能函数 (内部逻辑) ---
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+
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+async def call_api_with_file(
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+ session: aiohttp.ClientSession,
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+ url: str,
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+ file_path: str,
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+ params: Dict[str, Any] = None,
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+ form_fields: Dict[str, Any] = None
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+) -> Tuple[int, bytes]:
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+ """通用的文件上传API调用函数"""
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+ form_data = aiohttp.FormData()
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+
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+ if form_fields:
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+ for key, value in form_fields.items():
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+ form_data.add_field(key, str(value))
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+
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+ async with aiofiles.open(file_path, 'rb') as f:
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+ content = await f.read()
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+ form_data.add_field(
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+ 'file',
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+ content,
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+ filename=os.path.basename(file_path),
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+ content_type='image/jpeg'
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+ )
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+
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+ try:
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+ async with session.post(url, data=form_data, params=params) as response:
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+ response_content = await response.read()
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+ if not response.ok:
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+ print(f"错误: 调用 {url} 失败, 状态码: {response.status}")
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+ return response.status, response_content
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+ except aiohttp.ClientConnectorError as e:
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+ print(f"错误: 无法连接到服务 {url} - {e}")
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+ return 503, b"Connection Error"
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+
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+
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+async def process_single_image(
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+ session: aiohttp.ClientSession,
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+ image_path: str,
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+ score_type: str,
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+ is_reflect_card: str
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+) -> Dict[str, Any]:
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+ """处理单张图片:获取转正图和分数JSON"""
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+ print(f" 正在处理图片: {os.path.basename(image_path)} ({score_type})")
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+
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+ # 1. 获取转正后的图片
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+ rectify_url = f"{INFERENCE_SERVICE_URL}/api/card_inference/card_rectify_and_center"
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+ rectify_status, rectified_image_bytes = await call_api_with_file(
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+ session, url=rectify_url, file_path=image_path
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+ )
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+ if rectify_status >= 300:
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+ raise Exception(f"获取转正图失败: {image_path}")
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+
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+ # 2. 获取分数JSON
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+ score_url = f"{INFERENCE_SERVICE_URL}/api/card_score/score_inference"
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+ score_params = {
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+ "score_type": score_type,
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+ "is_reflect_card": is_reflect_card
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+ }
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+ score_status, score_json_bytes = await call_api_with_file(
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+ session,
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+ url=score_url,
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+ file_path=image_path,
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+ params=score_params
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+ )
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+ if score_status >= 300:
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+ raise Exception(f"获取分数JSON失败: {image_path}")
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+
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+ score_json = json.loads(score_json_bytes)
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+ return {
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+ "score_type": score_type,
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+ "rectified_image": rectified_image_bytes,
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+ "score_json": score_json
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+ }
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+
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+
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+async def create_card_set(session: aiohttp.ClientSession, card_name: str) -> int:
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+ """创建一个新的卡组并返回其ID"""
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+ url = f"{STORAGE_SERVICE_URL}/api/cards/created"
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+ params = {'card_name': card_name}
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+ print(f"\n[步骤 2] 创建卡组: '{card_name}'")
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+
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+ try:
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+ async with session.post(url, params=params) as response:
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+ if response.ok:
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+ data = await response.json()
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+ card_id = data.get('id')
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+ if card_id is not None:
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+ print(f" -> 成功创建卡组 ID: {card_id}")
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+ return card_id
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+ raise Exception("响应中未找到 'id' 字段")
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+ else:
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+ raise Exception(f"状态码: {response.status}")
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+ except Exception as e:
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+ raise Exception(f"创建卡组失败: {e}")
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+
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+
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+async def upload_processed_data(
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+ session: aiohttp.ClientSession,
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+ card_id: int,
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+ processed_data: Dict[str, Any]
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+):
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+ """上传单张转正图和对应的JSON"""
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+ score_type = processed_data['score_type']
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+ image_type = SCORE_TO_IMAGE_TYPE_MAP[score_type]
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+
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+ url = f"{STORAGE_SERVICE_URL}/api/images/insert/{card_id}"
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+
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+ form_data = aiohttp.FormData()
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+ form_data.add_field('image_type', image_type)
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+ form_data.add_field('json_data_str', json.dumps(processed_data['score_json'], ensure_ascii=False))
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+ form_data.add_field(
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+ 'image',
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+ processed_data['rectified_image'],
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+ filename='rectified.jpg',
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+ content_type='image/jpeg'
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+ )
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+
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+ try:
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+ async with session.post(url, data=form_data) as response:
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+ if response.status == 201:
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+ print(f" -> 上传成功: {image_type}")
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+ else:
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+ print(f" -> 上传失败 ({image_type}): {response.status}")
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+ except Exception as e:
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+ print(f" -> 上传异常 ({image_type}): {e}")
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+
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+
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+# --- 核心 API 函数 ---
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+
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+async def process_card_images(
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+ is_reflect: bool,
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+ front_face_path: str,
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+ front_edge_path: str,
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+ back_face_path: str,
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+ back_edge_path: str
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+) -> int:
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+ """
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+ 核心异步处理函数。
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+ :return: 成功创建的 card_id,如果失败返回 -1
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+ """
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+
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+ # 0. 数据准备
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+ is_reflect_str = "true" if is_reflect else "false"
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+
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+ # 注意:这里的顺序必须与全局 SCORE_TYPES 列表的顺序一一对应
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+ # SCORE_TYPES = ["front_corner_edge", "front_face", "back_corner_edge", "back_face"]
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+ path_list = [
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+ front_edge_path, # 对应 front_corner_edge
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+ front_face_path, # 对应 front_face
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+ back_edge_path, # 对应 back_corner_edge
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+ back_face_path # 对应 back_face
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+ ]
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+
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+ # 检查路径是否存在
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+ for p in path_list:
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+ if not os.path.exists(p):
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+ print(f"错误: 文件路径不存在 -> {p}")
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+ return -1
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+
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+ # 生成卡片名称
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+ card_name = f"卡 {datetime.now().strftime('%Y-%m-%d_%H:%M:%S')}"
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+
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+ async with aiohttp.ClientSession() as session:
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+ try:
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+ # 步骤 1: 并发处理图片 (转正 + 评分)
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+ print(f"--- 开始处理: {card_name} ---")
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+ print("[步骤 1] 并发图像处理...")
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+
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+ process_tasks = []
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+ for path, s_type in zip(path_list, SCORE_TYPES):
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+ task = process_single_image(session, path, s_type, is_reflect_str)
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+ process_tasks.append(task)
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+
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+ processed_results = await asyncio.gather(*process_tasks)
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+
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+ # 步骤 2: 创建卡组
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+ card_id = await create_card_set(session, card_name)
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+
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+ # 步骤 3: 并发上传结果
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+ print(f"\n[步骤 3] 上传数据到卡组 {card_id}...")
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+ upload_tasks = []
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+ for result in processed_results:
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+ task = upload_processed_data(session, card_id, result)
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+ upload_tasks.append(task)
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+
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+ await asyncio.gather(*upload_tasks)
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+
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+ print(f"--- 流程完成,卡组ID: {card_id} ---\n")
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+ return card_id
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+
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+ except Exception as e:
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+ print(f"\n流程执行中发生错误: {e}")
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+ return -1
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+
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+
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+# --- 同步封装函数 (方便直接调用) ---
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+
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+def run_card_processing_sync(
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+ is_reflect: bool,
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+ front_face_path: str,
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+ front_edge_path: str,
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+ back_face_path: str,
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+ back_edge_path: str
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+):
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+ """
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+ 同步包装函数,会自动处理 EventLoop。
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+ 如果你的代码不是异步的,直接调用这个函数即可。
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+ """
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+ if os.name == 'nt':
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+ asyncio.set_event_loop_policy(asyncio.WindowsProactorEventLoopPolicy())
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+
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+ return asyncio.run(process_card_images(
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+ is_reflect,
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+ front_face_path,
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+ front_edge_path,
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+ back_face_path,
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+ back_edge_path
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+ ))
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+
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+
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+# --- 使用示例 ---
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+
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+if __name__ == "__main__":
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+ # 准备参数
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+ # !!!!!🪸是否反光
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+ my_is_reflect = True
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+
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+ for img_num in range(13, 18):
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+ base_path = r"C:\Code\ML\Image\Card\_2025_1119_many_img\reflect2"
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+ p1 = os.path.join(base_path, f"{img_num}_front_coaxial_1_0.jpg")
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+ p2 = os.path.join(base_path, f"{img_num}_front_ring_0_1.jpg")
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+ p3 = os.path.join(base_path, f"{img_num}_back_coaxial_1_0.jpg")
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+ p4 = os.path.join(base_path, f"{img_num}_back_ring_0_1.jpg")
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+
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+ # 调用函数
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+ print("开始调用函数...")
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+
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+ final_card_id = run_card_processing_sync(
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+ is_reflect=my_is_reflect,
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+ front_face_path=p1,
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+ front_edge_path=p2,
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+ back_face_path=p3,
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+ back_edge_path=p4
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+ )
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+
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+ if final_card_id != -1:
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+ print(f"调用成功,生成的卡片ID是: {final_card_id}")
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+ else:
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+ print("调用失败")
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