CardScoreDataServer/Test/img_score_and_insert2.py

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://192.168.77.78:7744"
STORAGE_SERVICE_URL = "http://192.168.77.78:7745"

# 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))

    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}")
            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 ---

async def process_card_images(
        is_reflect: bool,
        front_face_path: str,
        front_edge_path: str,
        back_face_path: str,
        back_edge_path: str
) -> int:
    """
    核心异步处理函数。
    :return: 成功创建的 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：这里的顺序必须与全局 SCORE_TYPES 列表的顺序一一对应
    # SCORE_TYPES = ["front_corner_edge", "front_face", "back_corner_edge", "back_face"]
    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
    ]

    # 检查路径是否存在
    for p in path_list:
        if not os.path.exists(p):
            print(f"错误: 文件路径不存在 -> {p}")
            return -1

    # 生成卡片名称
    card_name = f"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)
            print(f"--- 开始处理: {card_name} ---")
            print("[步骤 1] 并发图像处理...")

            process_tasks = []
            for path, s_type in zip(path_list, SCORE_TYPES):
                task = process_single_image(session, path, s_type, is_reflect_str)
                process_tasks.append(task)

            processed_results = await asyncio.gather(*process_tasks)

            # 步骤 2: 创建卡组
            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 (方便直接调用) ---

def run_card_processing_sync(
        is_reflect: bool,
        front_face_path: str,
        front_edge_path: str,
        back_face_path: str,
        back_edge_path: str
):
    """
    同步包装函数，会自动处理 EventLoop。
    如果你的代码不是异步的，直接调用这个函数即可。
    """
    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
    ))


# --- 使用示例 ---

if __name__ == "__main__":
    # 准备参数
    # !!!!!🪸是否反光
    my_is_reflect = True

    for img_num in range(10, 15):
        base_path = r"C:\Code\ML\Image\Card\_2025_1119_many_img\reflect2"
        p1 = os.path.join(base_path, f"{img_num}_front_coaxial_1_0.jpg")
        p2 = os.path.join(base_path, f"{img_num}_front_ring_0_1.jpg")
        p3 = os.path.join(base_path, f"{img_num}_back_coaxial_1_0.jpg")
        p4 = os.path.join(base_path, f"{img_num}_back_ring_0_1.jpg")

        # 调用函数
        print("开始调用函数...")

        final_card_id = run_card_processing_sync(
            is_reflect=my_is_reflect,
            front_face_path=p1,
            front_edge_path=p2,
            back_face_path=p3,
            back_edge_path=p4
        )

        if final_card_id != -1:
            print(f"调用成功，生成的卡片ID是: {final_card_id}")
        else:
            print("调用失败")