678 lines
23 KiB
Python
678 lines
23 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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多GPU多模态检索系统 - Web应用
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专为双GPU部署优化
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"""
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import os
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import json
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import time
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from flask import Flask, render_template, request, jsonify, send_file, url_for
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from werkzeug.utils import secure_filename
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from PIL import Image
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import base64
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import io
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import logging
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import traceback
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import glob
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# 设置环境变量优化GPU内存
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os.environ['PYTORCH_CUDA_ALLOC_CONF'] = 'expandable_segments:True'
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# 配置日志
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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app = Flask(__name__)
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app.config['SECRET_KEY'] = 'multigpu_multimodal_retrieval_2024'
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app.config['MAX_CONTENT_LENGTH'] = 16 * 1024 * 1024 # 16MB max file size
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# 配置上传文件夹
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UPLOAD_FOLDER = 'uploads'
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SAMPLE_IMAGES_FOLDER = 'sample_images'
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TEXT_DATA_FOLDER = 'text_data'
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ALLOWED_EXTENSIONS = {'png', 'jpg', 'jpeg', 'gif', 'bmp', 'webp'}
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# 确保文件夹存在
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os.makedirs(UPLOAD_FOLDER, exist_ok=True)
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os.makedirs(SAMPLE_IMAGES_FOLDER, exist_ok=True)
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os.makedirs(TEXT_DATA_FOLDER, exist_ok=True)
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# 全局检索系统实例
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retrieval_system = None
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def allowed_file(filename):
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"""检查文件扩展名是否允许"""
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return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
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def image_to_base64(image_path):
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"""将图片转换为base64编码"""
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try:
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with open(image_path, "rb") as img_file:
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return base64.b64encode(img_file.read()).decode('utf-8')
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except Exception as e:
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logger.error(f"图片转换失败: {e}")
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return None
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@app.route('/')
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def index():
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"""主页"""
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return render_template('index.html')
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@app.route('/api/status')
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def get_status():
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"""获取系统状态"""
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global retrieval_system
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status = {
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'initialized': retrieval_system is not None,
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'gpu_count': 0,
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'model_loaded': False
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}
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try:
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import torch
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if torch.cuda.is_available():
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status['gpu_count'] = torch.cuda.device_count()
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if retrieval_system and retrieval_system.model:
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status['model_loaded'] = True
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status['device_ids'] = retrieval_system.device_ids
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except Exception as e:
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logger.error(f"获取状态失败: {e}")
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return jsonify(status)
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@app.route('/api/init', methods=['POST'])
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def initialize_system():
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"""初始化多GPU检索系统"""
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global retrieval_system
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try:
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logger.info("正在初始化多GPU检索系统...")
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# 导入多GPU检索系统
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from multimodal_retrieval_multigpu import MultiGPUMultimodalRetrieval
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# 初始化系统
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retrieval_system = MultiGPUMultimodalRetrieval()
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if retrieval_system.model is None:
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raise Exception("模型加载失败")
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logger.info("✅ 多GPU系统初始化成功")
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return jsonify({
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'success': True,
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'message': '多GPU系统初始化成功',
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'device_ids': retrieval_system.device_ids,
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'gpu_count': len(retrieval_system.device_ids)
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})
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except Exception as e:
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error_msg = f"系统初始化失败: {str(e)}"
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logger.error(error_msg)
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logger.error(traceback.format_exc())
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return jsonify({
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'success': False,
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'message': error_msg
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}), 500
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@app.route('/api/search/text_to_text', methods=['POST'])
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def search_text_to_text():
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"""文本搜索文本"""
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return handle_search('text_to_text')
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@app.route('/api/search/text_to_image', methods=['POST'])
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def search_text_to_image():
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"""文本搜索图片"""
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return handle_search('text_to_image')
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@app.route('/api/search/image_to_text', methods=['POST'])
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def search_image_to_text():
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"""图片搜索文本"""
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return handle_search('image_to_text')
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@app.route('/api/search/image_to_image', methods=['POST'])
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def search_image_to_image():
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"""图片搜索图片"""
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return handle_search('image_to_image')
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@app.route('/api/search', methods=['POST'])
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def search():
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"""通用搜索接口（兼容旧版本）"""
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mode = request.form.get('mode') or request.json.get('mode', 'text_to_text')
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return handle_search(mode)
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def handle_search(mode):
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"""处理搜索请求的通用函数"""
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global retrieval_system
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if not retrieval_system:
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return jsonify({
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'success': False,
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'message': '系统未初始化，请先点击初始化按钮'
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}), 400
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try:
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top_k = int(request.form.get('top_k', 5))
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if mode in ['text_to_text', 'text_to_image']:
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# 文本查询
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query = request.form.get('query') or request.json.get('query', '')
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if not query.strip():
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return jsonify({
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'success': False,
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'message': '请输入查询文本'
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}), 400
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logger.info(f"执行{mode}搜索: {query}")
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# 执行搜索
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if mode == 'text_to_text':
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raw_results = retrieval_system.search_text_to_text(query, top_k=top_k)
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# 格式化文本搜索结果
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results = []
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for text, score in raw_results:
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results.append({
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'text': text,
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'score': float(score)
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})
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else: # text_to_image
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raw_results = retrieval_system.search_text_to_image(query, top_k=top_k)
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# 格式化图像搜索结果
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results = []
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for image_path, score in raw_results:
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try:
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# 读取图像并转换为base64
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with open(image_path, 'rb') as img_file:
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image_data = img_file.read()
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image_base64 = base64.b64encode(image_data).decode('utf-8')
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results.append({
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'filename': os.path.basename(image_path),
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'image_path': image_path,
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'image_base64': image_base64,
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'score': float(score)
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})
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except Exception as e:
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logger.error(f"读取图像失败 {image_path}: {e}")
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results.append({
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'filename': os.path.basename(image_path),
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'image_path': image_path,
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'image_base64': '',
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'score': float(score)
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})
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return jsonify({
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'success': True,
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'mode': mode,
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'query': query,
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'results': results,
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'result_count': len(results)
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})
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elif mode in ['image_to_text', 'image_to_image']:
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# 图片查询
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if 'image' not in request.files:
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return jsonify({
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'success': False,
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'message': '请上传查询图片'
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}), 400
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file = request.files['image']
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if file.filename == '' or not allowed_file(file.filename):
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return jsonify({
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'success': False,
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'message': '请上传有效的图片文件'
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}), 400
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# 保存上传的图片
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filename = secure_filename(file.filename)
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timestamp = str(int(time.time()))
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filename = f"query_{timestamp}_{filename}"
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filepath = os.path.join(UPLOAD_FOLDER, filename)
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file.save(filepath)
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logger.info(f"执行{mode}搜索，图片: {filename}")
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# 执行搜索
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if mode == 'image_to_text':
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raw_results = retrieval_system.search_image_to_text(filepath, top_k=top_k)
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# 格式化文本搜索结果
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results = []
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for text, score in raw_results:
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results.append({
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'text': text,
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'score': float(score)
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})
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else: # image_to_image
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raw_results = retrieval_system.search_image_to_image(filepath, top_k=top_k)
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# 格式化图像搜索结果
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results = []
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for image_path, score in raw_results:
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try:
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# 读取图像并转换为base64
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with open(image_path, 'rb') as img_file:
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image_data = img_file.read()
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image_base64 = base64.b64encode(image_data).decode('utf-8')
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results.append({
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'filename': os.path.basename(image_path),
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'image_path': image_path,
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'image_base64': image_base64,
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'score': float(score)
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})
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except Exception as e:
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logger.error(f"读取图像失败 {image_path}: {e}")
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results.append({
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'filename': os.path.basename(image_path),
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'image_path': image_path,
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'image_base64': '',
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'score': float(score)
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})
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# 转换查询图片为base64
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query_image_b64 = image_to_base64(filepath)
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return jsonify({
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'success': True,
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'mode': mode,
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'query_image': query_image_b64,
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'results': results,
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'result_count': len(results)
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})
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else:
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return jsonify({
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'success': False,
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'message': f'不支持的搜索模式: {mode}'
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}), 400
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except Exception as e:
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error_msg = f"搜索失败: {str(e)}"
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logger.error(error_msg)
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logger.error(traceback.format_exc())
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return jsonify({
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'success': False,
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'message': error_msg
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}), 500
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@app.route('/api/upload/images', methods=['POST'])
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def upload_images():
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"""批量上传图片"""
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try:
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uploaded_files = []
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if 'images' not in request.files:
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return jsonify({'success': False, 'message': '没有选择文件'}), 400
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files = request.files.getlist('images')
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for file in files:
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if file and file.filename != '' and allowed_file(file.filename):
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filename = secure_filename(file.filename)
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timestamp = str(int(time.time()))
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filename = f"{timestamp}_{filename}"
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filepath = os.path.join(SAMPLE_IMAGES_FOLDER, filename)
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file.save(filepath)
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uploaded_files.append(filename)
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return jsonify({
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'success': True,
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'message': f'成功上传 {len(uploaded_files)} 个图片文件',
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'uploaded_count': len(uploaded_files),
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'files': uploaded_files
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})
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except Exception as e:
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return jsonify({
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'success': False,
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'message': f'上传失败: {str(e)}'
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}), 500
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@app.route('/api/upload/texts', methods=['POST'])
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def upload_texts():
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"""批量上传文本数据"""
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try:
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data = request.get_json()
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if not data or 'texts' not in data:
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return jsonify({'success': False, 'message': '没有提供文本数据'}), 400
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texts = data['texts']
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if not isinstance(texts, list):
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return jsonify({'success': False, 'message': '文本数据格式错误'}), 400
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# 保存文本数据到文件
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timestamp = str(int(time.time()))
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filename = f"texts_{timestamp}.json"
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filepath = os.path.join(TEXT_DATA_FOLDER, filename)
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with open(filepath, 'w', encoding='utf-8') as f:
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json.dump(texts, f, ensure_ascii=False, indent=2)
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return jsonify({
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'success': True,
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'message': f'成功上传 {len(texts)} 条文本',
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'uploaded_count': len(texts)
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})
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except Exception as e:
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return jsonify({
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'success': False,
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'message': f'上传失败: {str(e)}'
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}), 500
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@app.route('/api/upload/file', methods=['POST'])
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def upload_single_file():
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"""上传单个文件"""
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if 'file' not in request.files:
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return jsonify({'success': False, 'message': '没有选择文件'}), 400
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file = request.files['file']
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if file.filename == '':
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return jsonify({'success': False, 'message': '没有选择文件'}), 400
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if file and allowed_file(file.filename):
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filename = secure_filename(file.filename)
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timestamp = str(int(time.time()))
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filename = f"{timestamp}_{filename}"
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filepath = os.path.join(SAMPLE_IMAGES_FOLDER, filename)
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file.save(filepath)
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return jsonify({
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'success': True,
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'message': '文件上传成功',
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'filename': filename
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})
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return jsonify({'success': False, 'message': '不支持的文件类型'}), 400
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@app.route('/api/data/list', methods=['GET'])
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def list_data():
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"""列出已上传的数据"""
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try:
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# 列出图片文件
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images = []
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if os.path.exists(SAMPLE_IMAGES_FOLDER):
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for filename in os.listdir(SAMPLE_IMAGES_FOLDER):
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if allowed_file(filename):
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filepath = os.path.join(SAMPLE_IMAGES_FOLDER, filename)
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stat = os.stat(filepath)
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images.append({
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'filename': filename,
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'size': stat.st_size,
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'modified': stat.st_mtime
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})
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# 列出文本文件
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texts = []
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if os.path.exists(TEXT_DATA_FOLDER):
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for filename in os.listdir(TEXT_DATA_FOLDER):
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if filename.endswith('.json'):
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filepath = os.path.join(TEXT_DATA_FOLDER, filename)
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stat = os.stat(filepath)
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texts.append({
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'filename': filename,
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'size': stat.st_size,
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'modified': stat.st_mtime
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})
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return jsonify({
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'success': True,
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'data': {
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'images': images,
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'texts': texts
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}
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})
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except Exception as e:
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return jsonify({
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'success': False,
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'message': f'获取数据列表失败: {str(e)}'
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}), 500
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@app.route('/api/gpu_status')
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def gpu_status():
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"""获取GPU状态"""
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try:
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from smart_gpu_launcher import get_gpu_memory_info
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gpu_info = get_gpu_memory_info()
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return jsonify({
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'success': True,
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'gpu_info': gpu_info
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})
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except Exception as e:
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return jsonify({
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'success': False,
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'message': f"获取GPU状态失败: {str(e)}"
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}), 500
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@app.route('/api/build_index', methods=['POST'])
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def build_index():
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"""构建检索索引"""
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global retrieval_system
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if not retrieval_system:
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return jsonify({
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'success': False,
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'message': '系统未初始化'
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}), 400
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try:
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# 获取所有图片和文本文件
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image_files = []
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text_data = []
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# 扫描图片文件
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for ext in ALLOWED_EXTENSIONS:
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pattern = os.path.join(SAMPLE_IMAGES_FOLDER, f"*.{ext}")
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image_files.extend(glob.glob(pattern))
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# 读取文本文件（支持.json和.txt格式）
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text_files = glob.glob(os.path.join(TEXT_DATA_FOLDER, "*.json"))
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text_files.extend(glob.glob(os.path.join(TEXT_DATA_FOLDER, "*.txt")))
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for text_file in text_files:
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try:
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if text_file.endswith('.json'):
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# 读取JSON格式的文本数据
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with open(text_file, 'r', encoding='utf-8') as f:
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data = json.load(f)
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if isinstance(data, list):
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text_data.extend([str(item).strip() for item in data if str(item).strip()])
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else:
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text_data.append(str(data).strip())
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else:
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# 读取TXT格式的文本数据
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with open(text_file, 'r', encoding='utf-8') as f:
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lines = [line.strip() for line in f.readlines() if line.strip()]
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text_data.extend(lines)
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except Exception as e:
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logger.warning(f"读取文本文件失败 {text_file}: {e}")
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# 检查是否有数据可以构建索引
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if not image_files and not text_data:
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return jsonify({
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'success': False,
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'message': '没有找到可用的图片或文本数据，请先上传数据'
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}), 400
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# 构建索引
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if image_files:
|
||
logger.info(f"构建图片索引，共 {len(image_files)} 张图片")
|
||
retrieval_system.build_image_index_parallel(image_files)
|
||
|
||
if text_data:
|
||
logger.info(f"构建文本索引，共 {len(text_data)} 条文本")
|
||
retrieval_system.build_text_index_parallel(text_data)
|
||
|
||
return jsonify({
|
||
'success': True,
|
||
'message': f'索引构建完成！图片: {len(image_files)} 张，文本: {len(text_data)} 条',
|
||
'image_count': len(image_files),
|
||
'text_count': len(text_data)
|
||
})
|
||
|
||
except Exception as e:
|
||
logger.error(f"构建索引失败: {str(e)}")
|
||
return jsonify({
|
||
'success': False,
|
||
'message': f'构建索引失败: {str(e)}'
|
||
}), 500
|
||
|
||
@app.route('/api/data/stats', methods=['GET'])
|
||
def get_data_stats():
|
||
"""获取数据统计信息"""
|
||
try:
|
||
# 统计图片文件
|
||
image_count = 0
|
||
for ext in ALLOWED_EXTENSIONS:
|
||
pattern = os.path.join(SAMPLE_IMAGES_FOLDER, f"*.{ext}")
|
||
image_count += len(glob.glob(pattern))
|
||
|
||
# 统计文本数据
|
||
text_count = 0
|
||
text_files = glob.glob(os.path.join(TEXT_DATA_FOLDER, "*.txt"))
|
||
for text_file in text_files:
|
||
try:
|
||
with open(text_file, 'r', encoding='utf-8') as f:
|
||
lines = [line.strip() for line in f.readlines() if line.strip()]
|
||
text_count += len(lines)
|
||
except Exception:
|
||
continue
|
||
|
||
return jsonify({
|
||
'success': True,
|
||
'image_count': image_count,
|
||
'text_count': text_count
|
||
})
|
||
|
||
except Exception as e:
|
||
logger.error(f"获取数据统计失败: {str(e)}")
|
||
return jsonify({
|
||
'success': False,
|
||
'message': f'获取统计失败: {str(e)}'
|
||
}), 500
|
||
|
||
@app.route('/api/data/clear', methods=['POST'])
|
||
def clear_data():
|
||
"""清空所有数据"""
|
||
try:
|
||
# 清空图片文件
|
||
for ext in ALLOWED_EXTENSIONS:
|
||
pattern = os.path.join(SAMPLE_IMAGES_FOLDER, f"*.{ext}")
|
||
for file_path in glob.glob(pattern):
|
||
try:
|
||
os.remove(file_path)
|
||
except Exception as e:
|
||
logger.warning(f"删除图片文件失败 {file_path}: {e}")
|
||
|
||
# 清空文本文件
|
||
text_files = glob.glob(os.path.join(TEXT_DATA_FOLDER, "*.txt"))
|
||
for text_file in text_files:
|
||
try:
|
||
os.remove(text_file)
|
||
except Exception as e:
|
||
logger.warning(f"删除文本文件失败 {text_file}: {e}")
|
||
|
||
# 重置索引
|
||
global retrieval_system
|
||
if retrieval_system:
|
||
retrieval_system.text_index = None
|
||
retrieval_system.image_index = None
|
||
retrieval_system.text_data = []
|
||
retrieval_system.image_data = []
|
||
|
||
return jsonify({
|
||
'success': True,
|
||
'message': '数据已清空'
|
||
})
|
||
|
||
except Exception as e:
|
||
logger.error(f"清空数据失败: {str(e)}")
|
||
return jsonify({
|
||
'success': False,
|
||
'message': f'清空数据失败: {str(e)}'
|
||
}), 500
|
||
|
||
@app.route('/uploads/<filename>')
|
||
def uploaded_file(filename):
|
||
"""提供上传文件的访问"""
|
||
return send_file(os.path.join(SAMPLE_IMAGES_FOLDER, filename))
|
||
|
||
def print_startup_info():
|
||
"""打印启动信息"""
|
||
print("🚀 启动多GPU多模态检索Web应用")
|
||
print("=" * 60)
|
||
print("访问地址: http://localhost:5000")
|
||
print("支持功能:")
|
||
print(" 📝 文搜文 - 文本查找相似文本")
|
||
print(" 🖼️ 文搜图 - 文本查找相关图片")
|
||
print(" 📝 图搜文 - 图片查找相关文本")
|
||
print(" 🖼️ 图搜图 - 图片查找相似图片")
|
||
print(" 📤 批量上传 - 图片和文本数据管理")
|
||
print("GPU配置:")
|
||
|
||
try:
|
||
import torch
|
||
if torch.cuda.is_available():
|
||
gpu_count = torch.cuda.device_count()
|
||
print(f" 🖥️ 检测到 {gpu_count} 个GPU")
|
||
for i in range(gpu_count):
|
||
name = torch.cuda.get_device_name(i)
|
||
props = torch.cuda.get_device_properties(i)
|
||
memory_gb = props.total_memory / 1024**3
|
||
print(f" GPU {i}: {name} ({memory_gb:.1f}GB)")
|
||
else:
|
||
print(" ❌ CUDA不可用")
|
||
except Exception as e:
|
||
print(f" ❌ GPU检查失败: {e}")
|
||
|
||
print("=" * 60)
|
||
|
||
def auto_initialize():
|
||
"""启动时自动初始化系统"""
|
||
global retrieval_system
|
||
|
||
try:
|
||
logger.info("🚀 启动时自动初始化多GPU检索系统...")
|
||
|
||
# 导入多GPU检索系统
|
||
from multimodal_retrieval_multigpu import MultiGPUMultimodalRetrieval
|
||
|
||
# 初始化系统
|
||
retrieval_system = MultiGPUMultimodalRetrieval()
|
||
|
||
if retrieval_system.model is None:
|
||
raise Exception("模型加载失败")
|
||
|
||
logger.info("✅ 系统自动初始化成功")
|
||
return True
|
||
|
||
except Exception as e:
|
||
logger.error(f"❌ 系统自动初始化失败: {str(e)}")
|
||
logger.error(traceback.format_exc())
|
||
return False
|
||
|
||
if __name__ == '__main__':
|
||
print_startup_info()
|
||
|
||
# 启动时自动初始化
|
||
auto_initialize()
|
||
|
||
# 启动Flask应用
|
||
app.run(
|
||
host='0.0.0.0',
|
||
port=5000,
|
||
debug=False,
|
||
threaded=True
|
||
)
|