新分支

.idea/encodings.xml

@@ -5,6 +5,7 @@
     <file url="file://$PROJECT_DIR$/Test/img_data_insert.py" charset="UTF-8" />
     <file url="file://$PROJECT_DIR$/Test/img_score_and_insert.py" charset="UTF-8" />
     <file url="file://$PROJECT_DIR$/Test/img_score_and_insert2.py" charset="UTF-8" />
+    <file url="file://$PROJECT_DIR$/Test/img_score_and_insert2_单背面.py" charset="UTF-8" />
     <file url="file://$PROJECT_DIR$/Test/img_score_and_insert2_环光面.py" charset="UTF-8" />
     <file url="file://$PROJECT_DIR$/Test/test.json" charset="UTF-8" />
     <file url="file://$PROJECT_DIR$/Test/test01.py" charset="GBK" />

Test/img_score_and_insert2_单背面.py

@@ -0,0 +1,306 @@
+import asyncio
+import aiohttp
+import aiofiles
+import json
+import os
+from typing import Dict, Any, Tuple, List
+from datetime import datetime
+
+# --- 配置区域 (可根据需要修改) ---
+INFERENCE_SERVICE_URL = "http://192.168.77.249:7744"
+STORAGE_SERVICE_URL = "http://192.168.77.249:7745"
+
+# 固定的处理类型映射
+SCORE_TYPES = [
+    "front_corner_edge",
+    "front_face",
+    "back_corner_edge",
+    "back_face"
+]
+
+SCORE_TO_IMAGE_TYPE_MAP = {
+    "front_corner_edge": "front_edge",
+    "front_face": "front_face",
+    "back_corner_edge": "back_edge",
+    "back_face": "back_face"
+}
+
+
+# --- 辅助功能函数 (内部逻辑) ---
+
+async def call_api_with_file(
+        session: aiohttp.ClientSession,
+        url: str,
+        file_path: str,
+        params: Dict[str, Any] = None,
+        form_fields: Dict[str, Any] = None
+) -> Tuple[int, bytes]:
+    """通用的文件上传API调用函数"""
+    form_data = aiohttp.FormData()
+
+    if form_fields:
+        for key, value in form_fields.items():
+            form_data.add_field(key, str(value))
+
+    # 这里的 file_path 必须保证有效，否则 open 会报错
+    async with aiofiles.open(file_path, 'rb') as f:
+        content = await f.read()
+        form_data.add_field(
+            'file',
+            content,
+            filename=os.path.basename(file_path),
+            content_type='image/jpeg'
+        )
+
+    try:
+        async with session.post(url, data=form_data, params=params) as response:
+            response_content = await response.read()
+            if not response.ok:
+                print(f"错误: 调用 {url} 失败, 状态码: {response.status}")
+            return response.status, response_content
+    except aiohttp.ClientConnectorError as e:
+        print(f"错误: 无法连接到服务 {url} - {e}")
+        return 503, b"Connection Error"
+
+
+async def process_single_image(
+        session: aiohttp.ClientSession,
+        image_path: str,
+        score_type: str,
+        is_reflect_card: str
+) -> Dict[str, Any]:
+    """处理单张图片：获取转正图和分数JSON"""
+    print(f"  正在处理图片: {os.path.basename(image_path)} ({score_type})")
+
+    # 1. 获取转正后的图片
+    rectify_url = f"{INFERENCE_SERVICE_URL}/api/card_inference/card_rectify_and_center"
+    rectify_status, rectified_image_bytes = await call_api_with_file(
+        session, url=rectify_url, file_path=image_path
+    )
+    if rectify_status >= 300:
+        raise Exception(f"获取转正图失败: {image_path}")
+
+    # 2. 获取分数JSON
+    score_url = f"{INFERENCE_SERVICE_URL}/api/card_score/score_inference"
+    score_params = {
+        "score_type": score_type,
+        "is_reflect_card": is_reflect_card
+    }
+    score_status, score_json_bytes = await call_api_with_file(
+        session,
+        url=score_url,
+        file_path=image_path,
+        params=score_params
+    )
+    if score_status >= 300:
+        raise Exception(f"获取分数JSON失败: {image_path}")
+
+    score_json = json.loads(score_json_bytes)
+    return {
+        "score_type": score_type,
+        "rectified_image": rectified_image_bytes,
+        "score_json": score_json
+    }
+
+
+async def create_card_set(session: aiohttp.ClientSession, card_name: str) -> int:
+    """创建一个新的卡组并返回其ID"""
+    url = f"{STORAGE_SERVICE_URL}/api/cards/created"
+    params = {'card_name': card_name}
+    print(f"\n[步骤 2] 创建卡组: '{card_name}'")
+
+    try:
+        async with session.post(url, params=params) as response:
+            if response.ok:
+                data = await response.json()
+                card_id = data.get('id')
+                if card_id is not None:
+                    print(f"  -> 成功创建卡组 ID: {card_id}")
+                    return card_id
+                raise Exception("响应中未找到 'id' 字段")
+            else:
+                raise Exception(f"状态码: {response.status}")
+    except Exception as e:
+        raise Exception(f"创建卡组失败: {e}")
+
+
+async def upload_processed_data(
+        session: aiohttp.ClientSession,
+        card_id: int,
+        processed_data: Dict[str, Any]
+):
+    """上传单张转正图和对应的JSON"""
+    score_type = processed_data['score_type']
+    image_type = SCORE_TO_IMAGE_TYPE_MAP[score_type]
+
+    url = f"{STORAGE_SERVICE_URL}/api/images/insert/{card_id}"
+
+    form_data = aiohttp.FormData()
+    form_data.add_field('image_type', image_type)
+    form_data.add_field('json_data_str', json.dumps(processed_data['score_json'], ensure_ascii=False))
+    form_data.add_field(
+        'image',
+        processed_data['rectified_image'],
+        filename='rectified.jpg',
+        content_type='image/jpeg'
+    )
+
+    try:
+        async with session.post(url, data=form_data) as response:
+            if response.status == 201:
+                print(f"  -> 上传成功: {image_type} (CardID: {card_id})")
+            else:
+                print(f"  -> 上传失败 ({image_type}): {response.status}")
+    except Exception as e:
+        print(f"  -> 上传异常 ({image_type}): {e}")
+
+
+# --- 核心 API 函数 (已修改) ---
+
+async def process_card_images(
+        is_reflect: bool,
+        front_face_path: str | None,
+        front_edge_path: str | None,
+        back_face_path: str | None,
+        back_edge_path: str | None,
+        existing_card_id: int | None = None  # <--- 新增参数：指定现有ID
+) -> int:
+    """
+    核心异步处理函数。
+    :param existing_card_id: 如果不为None，则不创建新卡组，直接使用该ID上传图片。
+    :return: 成功操作的 card_id，如果失败返回 -1
+    """
+
+    # 0. 数据准备
+    is_reflect_str = "true" if is_reflect else "false"
+
+    # 注意列表顺序：[正面边缘, 正面面, 背面边缘, 背面面]
+    path_list = [
+        front_edge_path,  # 对应 front_corner_edge
+        front_face_path,  # 对应 front_face
+        back_edge_path,  # 对应 back_corner_edge
+        back_face_path  # 对应 back_face
+    ]
+
+    # 生成卡片名称 (如果需要新建的话)
+    card_name = f"单面补全测试-卡 {datetime.now().strftime('%Y-%m-%d_%H:%M:%S')}"
+
+    async with aiohttp.ClientSession() as session:
+        try:
+            # 步骤 1: 并发处理图片 (转正 + 评分)
+            target_desc = f"现有ID {existing_card_id}" if existing_card_id else "新建卡组"
+            print(f"--- 开始处理 ({target_desc}) ---")
+            print("[步骤 1] 并发图像处理...")
+
+            process_tasks = []
+
+            for path, s_type in zip(path_list, SCORE_TYPES):
+                if path is None:
+                    continue
+
+                if not os.path.exists(path):
+                    print(f"警告: 文件不存在，跳过 -> {path}")
+                    continue
+
+                task = process_single_image(session, path, s_type, is_reflect_str)
+                process_tasks.append(task)
+
+            if not process_tasks:
+                print("错误: 没有提供任何有效的图片路径，流程终止。")
+                return -1
+
+            processed_results = await asyncio.gather(*process_tasks)
+
+            # 步骤 2: 确定 Card ID
+            card_id = -1
+            if existing_card_id is not None:
+                # --- 修改逻辑：直接使用传入的ID ---
+                print(f"\n[步骤 2] 跳过创建，使用指定卡组 ID: {existing_card_id}")
+                card_id = existing_card_id
+            else:
+                # --- 原逻辑：创建新卡组 ---
+                card_id = await create_card_set(session, card_name)
+
+            # 步骤 3: 并发上传结果
+            print(f"\n[步骤 3] 上传数据到卡组 {card_id}...")
+            upload_tasks = []
+            for result in processed_results:
+                task = upload_processed_data(session, card_id, result)
+                upload_tasks.append(task)
+
+            await asyncio.gather(*upload_tasks)
+
+            print(f"--- 流程完成，卡组ID: {card_id} ---\n")
+            return card_id
+
+        except Exception as e:
+            print(f"\n流程执行中发生错误: {e}")
+            return -1
+
+
+# --- 同步封装函数 (已修改) ---
+
+def run_card_processing_sync(
+        is_reflect: bool,
+        front_face_path: str | None,
+        front_edge_path: str | None,
+        back_face_path: str | None,
+        back_edge_path: str | None,
+        existing_card_id: int | None = None  # <--- 同步透传
+):
+    if os.name == 'nt':
+        asyncio.set_event_loop_policy(asyncio.WindowsProactorEventLoopPolicy())
+
+    return asyncio.run(process_card_images(
+        is_reflect,
+        front_face_path,
+        front_edge_path,
+        back_face_path,
+        back_edge_path,
+        existing_card_id
+    ))
+
+
+# --- 使用示例 (针对你的需求修改) ---
+
+if __name__ == "__main__":
+    my_is_reflect = True
+
+    # 正面图所在的文件夹路径
+    front_base_path = r"C:\Code\ML\Image\Card\coaxial_front_20img"
+
+    # 循环 1 到 20 (对应文件名)
+    for img_num in range(2, 21):
+
+        # 1. 计算目标的 Card ID (你的ID是 101 到 120)
+        # img_num 1  -> 101
+        # img_num 20 -> 120
+        target_card_id = 100 + img_num
+
+        # 2. 构造正面图路径 (p1)
+        # 注意: 你的文件名格式是 big_one_img{img_num}.jpg
+        front_img_path = os.path.join(front_base_path, f"big_one_img{img_num}.jpg")
+
+        # 3. 设置参数
+        # p1 = 正面面 (front_face) -> 传入 front_img_path
+        # p3 = 背面面 (back_face)  -> 这次不需要了，传入 None
+
+        print(f"正在处理第 {img_num} 组 | 对应 CardID: {target_card_id} | 文件: {os.path.basename(front_img_path)}")
+
+        if not os.path.exists(front_img_path):
+            print(f"  -> 错误: 找不到文件 {front_img_path}")
+            continue
+
+        final_card_id = run_card_processing_sync(
+            is_reflect=my_is_reflect,
+            front_face_path=front_img_path,  # <--- p1: 正面面
+            front_edge_path=None,  # p2
+            back_face_path=None,  # p3: 背面这次不传
+            back_edge_path=None,  # p4
+            existing_card_id=target_card_id  # <--- 重点：指定 ID，不创建新卡组
+        )
+
+        if final_card_id != -1:
+            print(f"  -> 成功更新 ID: {final_card_id}")
+        else:
+            print(f"  -> 处理失败 ID: {target_card_id}")