import re import threading import time from flask import Flask, jsonify,send_from_directory from basket_cleaning_detect import start_basket_cleaning_detection,init_basket_cleaning_detection from globals import inference_thread, stop_event,redis_client app = Flask(__name__) # Define the /wearing_detection endpoint @app.route('/basket_cleaning_detection', methods=['GET']) def basket_cleaning_detection():#开启平台搭设检测 global inference_thread#当全局变量需要重新赋值时,需要用global关键字声明 if inference_thread is None or not inference_thread.is_alive():#防止重复开启检测服务 #redis_client.set("log_in_flag",'False') stop_event.clear() start_events = []#给每个线程一个事件,让我知道某个线程是否开始检测 inference_thread = threading.Thread(target=start_basket_cleaning_detection,args=(start_events,)) inference_thread.start() app.logger.info('start_platform_setup_detection') init_basket_cleaning_detection() # 等待所有YOLO线程开始检测 for event in start_events: event.wait() return jsonify({"status": "SUCCESS"}), 200 else: app.logger.info("reset_detection already running") return jsonify({"status": "ALREADY_RUNNING"}), 200 @app.route('/basket_cleaning_status', methods=['GET']) def basket_cleaning_status():#获取平台搭设状态状态 if not redis_client.exists('basket_cleaning_order'):#平台搭设步骤还没有一个完成 app.logger.info('basket_cleaning_order is none') return jsonify({"status": "NONE"}), 200 else: basket_cleaning_order = redis_client.lrange("basket_cleaning_order", 0, -1) json_array = [] for value in basket_cleaning_order: match = re.search(r'basket_step_(\d+)', value) step_number = match.group(1) json_object = {"step": step_number, "image": redis_client.get(f"basket_step_{step_number}")} json_array.append(json_object) return jsonify({"status": "SUCCESS","data":json_array}), 200 @app.route('/basket_cleaning_finish', methods=['GET']) def basket_cleaning_finish():#开始登录时,检测是否需要复位,若需要,则发送复位信息,否则开始焊接检测 stop_inference_internal() app.logger.info('basket_cleaning_order') return jsonify({"status": "SUCCESS"}), 200 def stop_inference_internal(): global inference_thread if inference_thread is not None and inference_thread.is_alive(): stop_event.set() # 设置停止事件标志,通知推理线程停止运行 inference_thread.join() # 等待推理线程结束 inference_thread = None # 释放线程资源 app.logger.info('detection stopped') return True else: app.logger.info('No inference stopped') return False @app.route('/stop_detection', methods=['GET']) def stop_inference(): #global inference_thread if stop_inference_internal(): app.logger.info('detection stopped') return jsonify({"status": "DETECTION_STOPPED"}), 200 else: app.logger.info('No_detection_running') return jsonify({"status": "No_detection_running"}), 200 @app.route('/images/') def get_image(filename): app.logger.info('get_image'+filename) return send_from_directory('static/images', filename) if __name__ == '__main__': # Start the Flask server app.run(debug=False, host='172.16.20.163', port=5005)