import os import json import asyncio import aiohttp from typing import Dict, Any, Tuple, Optional, Union from fastapi import APIRouter, HTTPException, Request, UploadFile, File, Form from app.core.config import settings from app.core.logger import get_logger from app.utils.scheme import CardType logger = get_logger(__name__) router = APIRouter() # --- 内部辅助函数 --- async def call_api_with_bytes( session: aiohttp.ClientSession, url: str, file_bytes: bytes, filename: str, params: Dict[str, Any] = None, form_fields: Dict[str, Any] = None, file_field_name: str = 'file' ) -> Tuple[int, bytes]: """通用的文件上传API调用函数 (接收字节数据)""" form_data = aiohttp.FormData() if form_fields: for key, value in form_fields.items(): form_data.add_field(key, str(value)) # 直接将内存中的字节数据添加到表单 form_data.add_field( file_field_name, file_bytes, filename=filename or 'image.jpg', 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: logger.error( f"[API Error] {url} -> Status: {response.status}, Msg: {response_content.decode('utf-8', errors='ignore')[:100]}") return response.status, response_content except Exception as e: logger.error(f"[Conn Error] {url} -> {e}") raise e async def process_main_image( session: aiohttp.ClientSession, file_bytes: bytes, filename: str, score_type: str, is_reflect_card: str ) -> Dict[str, Any]: """调用推理服务，处理主图片""" logger.info(f"处理主图: {score_type} -> {filename}") inference_base_url = settings.SCORE_UPDATE_SERVER_URL # 1. 获取转正后的图片 rectify_url = f"{inference_base_url}/api/card_inference/card_rectify_and_center" rectify_status, rectified_image_bytes = await call_api_with_bytes( session, url=rectify_url, file_bytes=file_bytes, filename=filename ) if rectify_status >= 300: raise HTTPException(status_code=500, detail=f"图片转正失败: {score_type}") # 2. 获取分数JSON score_url = f"{inference_base_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_bytes( session, url=score_url, file_bytes=file_bytes, filename=filename, params=score_params ) if score_status >= 300: raise HTTPException(status_code=500, detail=f"推理分数失败: {score_type}") return { "image_type": score_type, "rectified_image": rectified_image_bytes, "score_json": json.loads(score_json_bytes) } async def create_card_record(session: aiohttp.ClientSession, base_url: str, card_name: str, cardNo: Optional[str], card_type: CardType) -> int: """调用自身服务创建新的卡牌记录""" url = f"{base_url}{settings.API_PREFIX}/cards/created" params = {'card_name': card_name, 'card_type': card_type.value} if cardNo: params['cardNo'] = cardNo async with session.post(url, params=params) as response: if response.status == 201: data = await response.json() return data.get('id') else: text = await response.text() raise HTTPException(status_code=response.status, detail=f"创建卡牌记录失败: {text}") async def upload_main_image(session: aiohttp.ClientSession, base_url: str, card_id: int, processed_data: Dict[str, Any]): """将处理后的主图和JSON上传到自身服务""" image_type = processed_data['image_type'] url = f"{base_url}{settings.API_PREFIX}/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=f'{image_type}_rectified.jpg', content_type='image/jpeg' ) async with session.post(url, data=form_data) as response: if response.status != 201: logger.error(f"[主图上传失败] {image_type} code={response.status}") raise HTTPException(status_code=500, detail=f"主图保存失败: {image_type}") async def upload_gray_image(session: aiohttp.ClientSession, base_url: str, card_id: int, image_type: str, file_bytes: bytes, filename: str): """将灰度图源文件上传到自身服务""" url = f"{base_url}{settings.API_PREFIX}/images/insert/gray/{card_id}" form_fields = {'image_type': image_type} status, _ = await call_api_with_bytes( session, url=url, file_bytes=file_bytes, filename=filename, form_fields=form_fields, file_field_name='image' ) if status != 201: logger.error(f"[灰度图上传失败] {image_type} code={status}") raise HTTPException(status_code=500, detail=f"灰度图保存失败: {image_type}") # --- 暴露的API接口 --- @router.post("/process_and_import", summary="自动化处理并导入卡牌数据") async def auto_import_script_api( request: Request, card_name: str = Form(..., description="卡牌名称"), cardNo: Optional[str] = Form(None, description="卡牌编号"), card_type: CardType = Form(CardType.pokemon, description="卡牌类型"), is_reflect_card: bool = Form(True, description="是否是反光卡"), strict_mode: bool = Form(False, description="如果为True，必须提供所有4张主图"), front_ring: Union[UploadFile, str, None] = File(None, description="正面环光图文件"), front_coaxial: Union[UploadFile, str, None] = File(None, description="正面同轴光图文件"), back_ring: Union[UploadFile, str, None] = File(None, description="背面环光图文件"), back_coaxial: Union[UploadFile, str, None] = File(None, description="背面同轴光图文件"), front_gray: Union[UploadFile, str, None] = File(None, description="正面灰度图文件"), back_gray: Union[UploadFile, str, None] = File(None, description="背面灰度图文件") ): local_base_url = str(request.base_url).rstrip('/') main_inputs = { "front_ring": front_ring, "front_coaxial": front_coaxial, "back_ring": back_ring, "back_coaxial": back_coaxial } gray_inputs = { "front_gray": front_gray, "back_gray": back_gray } # 【改动点2】过滤文件时，增加 isinstance(v, UploadFile) 的判断，剔除空字符串 valid_main_files = { k: v for k, v in main_inputs.items() if (v is not None) and v.filename } valid_gray_files = { k: v for k, v in gray_inputs.items() if (v is not None) and v.filename } provided_main_count = len(valid_main_files) if strict_mode and provided_main_count != 4: raise HTTPException(status_code=400, detail=f"严格模式开启，必须提供所有4张主图。") if not strict_mode and provided_main_count == 0 and not valid_gray_files: raise HTTPException(status_code=400, detail="未提供任何图片文件，无法创建。") is_reflect_str = "true" if is_reflect_card else "false" async with aiohttp.ClientSession() as session: try: # 读取所有图片至内存 main_bytes_data = {k: (await v.read(), v.filename) for k, v in valid_main_files.items()} gray_bytes_data = {k: (await v.read(), v.filename) for k, v in valid_gray_files.items()} # Step 1: 主图顺序推理 (防止瞬间塞爆推理服务器) logger.info(f"--- 开始自动导入任务: {card_name} ---") processed_results = [] for img_type, (f_bytes, f_name) in main_bytes_data.items(): if len(f_bytes) == 0: raise HTTPException(status_code=400, detail=f"图片文件 {f_name} 内容为空") res = await process_main_image(session, f_bytes, f_name, img_type, is_reflect_str) processed_results.append(res) # Step 2: 在自身数据库创建卡片记录 card_id = await create_card_record( session, local_base_url, card_name, cardNo, card_type ) logger.info(f"卡片记录创建成功，ID: {card_id}") # Step 3: 并发调用自身的图片保存接口 upload_tasks = [] for res in processed_results: upload_tasks.append(upload_main_image(session, local_base_url, card_id, res)) for img_type, (f_bytes, f_name) in gray_bytes_data.items(): upload_tasks.append(upload_gray_image(session, local_base_url, card_id, img_type, f_bytes, f_name)) if upload_tasks: await asyncio.gather(*upload_tasks) logger.info(f"--- 自动导入流程结束, Card ID: {card_id} ---") return { "message": "导入成功", "card_id": card_id, "card_name": card_name, "cardNo": cardNo } except HTTPException: raise except Exception as e: logger.error(f"[流程终止] 发生异常: {e}") raise HTTPException(status_code=500, detail=f"自动化处理异常: {str(e)}")