删除不必要代码

app.py

@@ -1,7 +1,6 @@
 import threading
 import time
 from flask import Flask, jsonify,send_from_directory
-from welding_wearing_detect import start_wearing_detection,init_wearing_detection
 from globals import inference_thread, stop_event,lock,redis_client
 
 #焊接考核的穿戴
@@ -9,42 +8,33 @@ app = Flask(__name__)
 
 
 # Define the /wearing_detection endpoint
-@app.route('/wearing_detection', methods=['GET'])
-def wearing_detection():
+@app.route('/compressed_oxygen_detection', methods=['GET'])
+def compressed_oxygen_detection():
     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():
         stop_event.clear()#stop_event不用global声明，因为不需要重新赋值，他只是调用了其方法，并没有重新赋值
         
         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_wearing_detection,args=(start_events,))
+        inference_thread = threading.Thread(target=start_compressed_oxygen_detection,args=(start_events,))
         inference_thread.start()
-        init_wearing_detection()
+        init_compressed_oxygen_detection()
 
         # 等待所有YOLO线程开始检测，两个线程检测完毕时，才返回SUCCESS
         for event in start_events:
             event.wait()
 
-        app.logger.info('start_wearing_detection')
+        app.logger.info('start_compressed_oxygen_detection')
         return jsonify({"status": "SUCCESS"}), 200
     
     else:
-        app.logger.info("start_wearing_detection already running")   
+        app.logger.info("start_compressed_oxygen_detection already running")   
         return jsonify({"status": "ALREADY_RUNNING"}), 200
     
 
-@app.route('/human_postion_status', methods=['GET']) 
-def human_postion_status():#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
-    #global inference_thread
-    if redis_client.get("welding_wearing_human_in_postion")=='False':
-        app.logger.info('NOT_IN_POSTION')
-        return jsonify({"status": "NOT_IN_POSTION"}), 200
-    else:
-        app.logger.info('IN_POSTION')
-        return jsonify({"status": "IN_POSTION"}), 200
 
-@app.route('/wearing_status', methods=['GET']) 
-def wearing_status():#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
+@app.route('/compressed_oxygen_status', methods=['GET']) 
+def compressed_oxygen_status():#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
     #global inference_thread
     with lock:   
         #TODO 若出现异常再发送FAIL.
@@ -67,9 +57,9 @@ def wearing_status():#开始登录时，检测是否需要复位，若需要，
         return jsonify({"status": "SUCCESS","data":json_array,"image":image}), 200
 
                
-@app.route('/end_wearing_exam', methods=['GET'])
+@app.route('/end_compressed_oxygen_detection', methods=['GET'])
 def end_wearing_exam():
-    init_wearing_detection()
+    init_compressed_oxygen_detection()
     return jsonify({"status": "SUCCESS"}), 200
 
     

config.py

@@ -7,187 +7,14 @@ SAVE_IMG_PATH = '/mnt/xcd/code/ai_test/static/images'  # 图片保存在服务
 
 POST_IMG_PATH1 = 'http://172.16.20.163:5001/images'  # 通过端口映射post发送能够访问的位置 焊接考核科目1
 POST_IMG_PATH2 = 'http://172.16.20.163:5002/images' #焊接考核科目2
-POST_IMG_PATH3 = 'http://172.16.20.163:5003/images' #平台搭设科目1，劳保穿戴
-POST_IMG_PATH4 = 'http://172.16.20.163:5004/images' #平台搭设科目2，搭建和拆除
-POST_IMG_PATH5 = 'http://172.16.20.163:5005/images'#吊篮清洗
-POST_IMG_PATH6 = 'http://172.16.20.163:5006/images'#吊具清洗
 
+VIDEO_SOURCE = '/mnt/xcd/code/ai_test/static/videos/1.mp4'  # 视频源路径
 #焊接考核视频流
 # Define paths to RTSP streams
-WELDING_CH1_RTSP = 'rtsp://admin:yaoan1234@172.16.22.230/cam/realmonitor?channel=1&subtype=0'#焊机开关视频
-WELDING_CH2_RTSP = 'rtsp://admin:yaoan1234@172.16.22.231/cam/realmonitor?channel=1&subtype=0'#焊台视频
-WELDING_CH3_RTSP = 'rtsp://admin:yaoan1234@172.16.22.233/cam/realmonitor?channel=1&subtype=0'#检查油桶视频
-WELDING_CH4_RTSP = 'rtsp://admin:yaoan1234@172.16.22.232/cam/realmonitor?channel=1&subtype=0'#检查总开关视频
-WELDING_CH5_RTSP = 'rtsp://admin:yaoan1234@172.16.22.234/cam/realmonitor?channel=1&subtype=0'#检查面具手套接地线视频
-WELDING_CH6_RTSP = 'rtsp://admin:yaoan1234@172.16.22.235/cam/realmonitor?channel=1&subtype=0'#劳保用品穿戴视频
 
-WELDING_CH1_MODEL="/mnt/xcd/code/ai_test/weights/ch1_welding_switch_813.pt"
-WELDING_CH2_MODEL="/mnt/xcd/code/ai_test/weights/ch2_welding_desk_cls_813.pt"
-WELDING_CH3_MODEL="/mnt/xcd/code/ai_test/weights/ch3_oil_barrel_detect_813.pt"
-WELDING_CH4_MODEL="/mnt/xcd/code/ai_test/weights/ch4_main_switch_cls_813.pt"
-WELDING_CH5_MODEL="/mnt/xcd/code/ai_test/weights/ch5_mask_gloves_wire_detect_813.pt"
-WELDING_CH6_MODEL='/mnt/xcd/code/ai_test/weights/ch6_wearing_detect_813.pt'
 
-HUMAN_DETECTION_MODEL="/mnt/xcd/code/ai_test/weights/yolov8n.pt"#人体检测模型
+MODEL_PATH="/mnt/xcd/code/ai_test/weights/ch1_welding_switch_813.pt"
 
-# Define paths to models
-WELDING_MODEL_PATHS = [
-    WELDING_CH1_MODEL,
-    WELDING_CH2_MODEL,
-    WELDING_CH3_MODEL,
-    WELDING_CH4_MODEL,
-    WELDING_CH5_MODEL
-]
 
-WELDING_VIDEO_SOURCES = [
-    WELDING_CH1_RTSP,
-    WELDING_CH2_RTSP,
-    WELDING_CH3_RTSP,
-    WELDING_CH4_RTSP,
-    WELDING_CH5_RTSP
-]
 
 
-
-WELDING_WEARING_MODEL=[
-    HUMAN_DETECTION_MODEL,
-    WELDING_CH6_MODEL
-]
-
-WELDING_WEARING_VIDEO_SOURCES= WELDING_CH6_RTSP
-
-#WEAR_DETECTION_VIDEO_SOURCES= "/home/dxc/special_test/ch1.mp4"
-
-# 劳保用品 指定要检测的区域 (xmin, ymin, xmax, ymax)
-WEAR_DETECTION_AREA = (350, 0, 1400, 1080)
-
-
-# 头盔检测区域(xmin, ymin, xmax, ymax)
-
-WELDING_REGION1=(1499,339,1839,723)
-# 油桶危险区域（多边形）
-
-WELDING_REGION2 = np.array([[607, 555], [454, 0], [2560, 0], [2560, 1440], [430, 1440]], np.int32)
-
-# 搭铁夹连接焊台位置
-
-WELDING_REGION3 = np.array([[1613, 627], [1601, 658], [1697, 987], [1710, 962]], np.int32)
-
-
-####平台搭设视频流
-PLATFORM_CH1_RTSP='rtsp://admin:yaoan1234@172.16.22.241/cam/realmonitor?channel=1&subtype=0'#检测穿戴
-
-PLATFORM_CH2_RTSP='rtsp://admin:yaoan1234@172.16.22.240/cam/realmonitor?channel=1&subtype=0'#脚手架搭建
-# PLATFORM_CH3_RTSP='rtsp://admin:yaoan1234@172.16.22.243/cam/realmonitor?channel=1&subtype=0'#脚手架搭建
-PLATFORM_CH4_RTSP='rtsp://admin:yaoan1234@172.16.22.233/cam/realmonitor?channel=1&subtype=0'#脚手架搭建
-
-PLATFORM_CH1_MODEL='/mnt/xcd/code/ai_test/weights/platform_ch1_wearing.pt'
-
-PLATFORM_SETUP_MODEL='/mnt/xcd/code/ai_test/weights/obb_9_2.pt'
-PLATFORM_SETUP_VIDEO_SOURCES=[PLATFORM_CH2_RTSP,
-                              #PLATFORM_CH3_RTSP,
-                              PLATFORM_CH4_RTSP
-]
-
-PLATFORM_WEARING_MODEL=[
-    HUMAN_DETECTION_MODEL,
-    PLATFORM_CH1_MODEL    
-]
-
-PLATFORM_WEARING_VIDEO_SOURCES=PLATFORM_CH1_RTSP
-
-#PLATFORM_CH2_MODEL='/mnt/xcd/code/ai_test/weights/high_work_obb_final.pt'
-
-# Define paths to input videos
-
-
-#焊接劳保检测相关参数
-
-#################平台搭设检测相关参数
-
-# PLATFORM_SETUP_VIDEO_SOURCES=PLATFORM_CH2_RTSP
-# PLATFORM_SETUP_MODEL=PLATFORM_SETUP_MODEL
-
-#吊篮清洗
-
-
-BASKET_CLEANING_CH4_POSE_MODEL='/mnt/xcd/code/ai_test/weights/yolov8s-pose1.pt'
-BASKET_CLEANING_CH5_DETECT_MODEL='/mnt/xcd/code/ai_test/weights/yolov8s1.pt'
-BASKET_CLEANING_CH6_POSE_MODEL='/mnt/xcd/code/ai_test/weights/yolov8s-pose2.pt'
-BASKET_CLEANING_CH6_DETECT_MODEL='/mnt/xcd/code/ai_test/weights/ch6detect_basket.pt'
-BASKET_CLEANING_CH6_SEG_MODEL='/mnt/xcd/code/ai_test/weights/basket_seg.pt'
-
-BASKET_CLEANING_CH4_RTSP='rtsp://admin:yaoan1234@172.16.22.237/cam/realmonitor?channel=1&subtype=0'
-#BASKET_CLEANING_CH5_RTSP='rtsp://admin:yaoan1234@172.16.22.239/cam/realmonitor?channel=1&subtype=0'
-BASKET_CLEANING_CH6_RTSP='rtsp://admin:yaoan1234@172.16.22.242/cam/realmonitor?channel=1&subtype=0'
-
-BASKET_CLEANING_VIDEO_SOURCES=[BASKET_CLEANING_CH4_RTSP,
-                               #BASKET_CLEANING_CH5_RTSP,
-                               BASKET_CLEANING_CH6_RTSP,
-                               BASKET_CLEANING_CH6_RTSP,
-                               BASKET_CLEANING_CH6_RTSP]
-
-BASKET_CLEANING_MODEL_SOURCES=[BASKET_CLEANING_CH4_POSE_MODEL,
-                               #BASKET_CLEANING_CH5_DETECT_MODEL,
-                               BASKET_CLEANING_CH6_POSE_MODEL,
-                               BASKET_CLEANING_CH6_DETECT_MODEL,
-                               BASKET_CLEANING_CH6_SEG_MODEL]
-
-#
-
-#悬挂机构区域，分为四个区域 D4
-BASKET_SUSPENSION_REGION = np.array([
-    [[668, 310], [800, 310], [800, 1070], [668, 1070]],
-    [[1690, 310], [1750, 310], [1750, 710], [1690, 710]],
-    [[1350, 340], [1405, 340], [1405, 720], [1350, 720]],
-    [[550, 385], [635, 385], [635, 880], [550, 880]]
-], np.int32)
-
-BASKET_STEEL_WIRE_REGION = np.array([
-    [(374, 846), (601, 970), (630, 900), (441, 786)],  # 右一多边形区域
-    [(1518, 736), (1649, 945), (2005, 917), (1888, 677)]  # 右二多边形区域
-    # [(1293, 0), (1867, 935), (1904, 906), (1354, 9)],  # 左边多边形区域
-], np.int32)#钢丝绳区域，暂时没有钢丝绳的区域
-
-BASKET_PLATFORM_REGION = np.array([], np.int32)
-BASKET_LIFTING_REGION = np.array([]
-,np.int32)
-
-BASKET_SAFETY_LOCK_REGION = np.array([
-    [[1635, 813], [1742, 927], [1955, 910], [1906, 747]],
-    [[650, 944], [800, 1000], [800, 923], [680, 872]]
-    ], np.int32)
-BASKET_ELECTRICAL_SYSTEM_REGION = np.array([], np.int32)
-BASKET_CLEANING_OPERATION_REGION = np.array([[8, 1038], [14, 1423], [1910, 1432], [1894, 1129]], np.int32)
-BASKET_EMPTY_LOAD_REGION = np.array([(752, 855), (712, 969), (836, 1020), (896, 918)], np.int32)
-
-
-#单人吊具
-EQUIPMENT_CLEANING_CH3_RTSP='rtsp://admin:yaoan1234@172.16.22.238/cam/realmonitor?channel=1&subtype=0'
-EQUIPMENT_CLEANING_CH8_RTSP='rtsp://admin:yaoan1234@172.16.22.44/cam/realmonitor?channel=1&subtype=0'
-
-
-EQUIPMENT_CLEANING_CH3_DETECT_MODEL='/mnt/xcd/code/ai_test/weights/ch6detect_basket.pt'
-EQUIPMENT_CLEANING_CH8_POSE_MODEL='/mnt/xcd/code/ai_test/weights/yolov8s-pose2.pt'
-EQUIPMENT_CLEANING_CH8_DETECT_MODEL='/mnt/xcd/code/ai_test/weights/ch6detect_basket.pt'
-
-EQUIPMENT_CLEANING_VIDEO_SOURCES=[EQUIPMENT_CLEANING_CH3_RTSP,
-                                  EQUIPMENT_CLEANING_CH8_RTSP,
-                                  EQUIPMENT_CLEANING_CH8_RTSP
-]
-
-EQUIPMENT_CLEANING_MODEL_SOURCES=[EQUIPMENT_CLEANING_CH3_DETECT_MODEL,
-                                  EQUIPMENT_CLEANING_CH8_POSE_MODEL,
-                                  EQUIPMENT_CLEANING_CH8_DETECT_MODEL
-]
-
-EQUIPMENT_ANCHOR_DEVICE_REGION = np.array([
-    [[913, 6], [914, 520], [1350, 523], [1351, 9]],
-], np.int32)
-EQUIPMENT_WORK_ROPE_REGION = np.array([
-    [[1466, 1187], [1416, 1248], [2500, 1162], [2502, 1063]],
-], np.int32)
-EQUIPMENT_SAFETY_ROPE_REGION = np.array([
-    [[1466, 1187], [1416, 1248], [2500, 1162], [2502, 1063]],
-], np.int32)
-EQUIPMENT_CLEANING_OPERATION_REGION=np.array([[1697, 930], [1055, 1253], [2000, 1420], [2450, 1000]], np.int32)

globals.py

@@ -9,85 +9,19 @@ inference_thread = None
 stop_event = threading.Event()
 lock=threading.Lock()
 
-#condition = threading.Condition()
 ###############焊接考核
 #为True时，表示某一步骤完成,并保存图片post
-step1=False #危险源排除
+step1=False 
 step2=False
 step3=False
 step4=False
 step5=False
-step6=False #危险源排除
-step7=False
-step8=False
-step9=False
-step10=False
-step11=False
-step12=False
-step13=False
+step6=False 
+# 压缩氧
+# 1 = 外壳去掉
+# 2 = 脖带戴好 
+# 3 = 咬口具
+# 4 = 氧气瓶开启
+# 5 = 补气
+# 6 = 带鼻夹
 
-steps = [False] * 13
-
-oil_barrel=None
-main_switch=None
-grounding_wire=None
-welding_machine_switch=None
-welding_components=None
-mask=None
-welding=None
-gloves=None
-sweep=None
-
-sweep_detect_num=0
-welding_detect_num=0
-###############
-
-
-
-
-###########检测物品是否复位
-oil_barrel_flag=False
-main_switch_flag=False
-ground_wire_flag=False
-welding_components_flag=False
-welding_machine_switch_flag=False
-
-oil_barrel_save_img=False
-main_switch_save_img=False
-ground_wire_save_img=False
-welding_components_save_img=False
-welding_machine_switch_save_img=False
-
-
-reset_all=None
-log_in_flag=False#登录标志，如前端未登录，不允许保存图片并post
-###############################
-###############平台搭设考核
-platform_setup_steps_detect_num=[0]*14
-platform_setup_final_result=[0]*14
-platform_setup_steps_img=[False]*14
-################平台拆除考核
-platform_remove_steps_detect_num=[0]*14
-platform_remove_final_result=[0]*14
-platform_remove_steps_img=[False]*14
-
-remove_detection_timers = [time.time()] * 14  # 初始化计时器
-remove_detection_status = [False]*14 # 初始化检
-
-#吊篮清洗
-basket_person_flag=False#吊篮区域是否存在人员
-basket_suspension_flag=False#吊篮悬挂机构
-basket_warning_zone_flag=False#吊篮警戒区
-basket_steel_wire_flag=False#吊篮钢丝绳
-basket_platform_flag=False#吊篮平台
-basket_lifting_flag=False#吊篮升降机构
-basket_safety_lock_flag=False#吊篮安全锁
-basket_electrical_system_flag=False#吊篮电气系统
-basket_empty_load_flag=False#吊篮空载
-basket_safety_belt_flag=False#吊篮安全带挂设
-
-basket_cleaning_operation_flag=False#吊篮清洗操作,检查刷子是否在指定区域
-basket_cleaning_up_flag=False#吊篮清理现场
-
-#单人吊具
-equipment_cleaning_flag=[False]*12

welding_wearing_detect.py

@@ -0,0 +1,69 @@
+import torch
+import cv2
+import threading
+from datetime import datetime
+from ultralytics import YOLO
+from globals import stop_event,redis_client
+from config import SAVE_IMG_PATH,POST_IMG_PATH1,VIDEO_SOURCE,MODEL_PATH
+
+
+def init_compressed_oxygen_detection():
+    pass
+
+def start_compressed_oxygen_detection(start_events):
+        
+    event = threading.Event()
+    start_events.append(event)
+    thread = threading.Thread(target=process_video, args=(MODEL_PATH,VIDEO_SOURCE,event))
+    thread.daemon=True
+    thread.start()
+    thread.join()
+
+
+def process_video(model_path, video_source, start_event):
+
+    
+    model = YOLO(model_path)
+    cap = cv2.VideoCapture(video_source)
+    while cap.isOpened():
+    # Read a frame from the video
+        success, frame = cap.read()
+        if stop_event.is_set():#控制停止推理
+            break
+        if success:
+            
+            if cap.get(cv2.CAP_PROP_POS_FRAMES) % 10 != 0:#跳帧检测，
+                continue
+
+
+            results = model.predict(frame,conf=0.6,verbose=False)
+
+            for r in results:
+                boxes = r.boxes.xyxy  # 提取所有检测到的边界框坐标
+                confidences = r.boxes.conf  # 提取所有检测到的置信度
+                classes = r.boxes.cls  # 提取所有检测到的类别索引
+
+                
+                for i in range(len(boxes)):
+                    x1, y1, x2, y2 = boxes[i].tolist()
+                    confidence = confidences[i].item()
+                    cls = int(classes[i].item())
+                    label = model.names[cls]
+                pass
+                
+                    
+                start_event.set()    
+
+
+        else:
+            # Break the loop if the end of the video is reached
+            break
+
+        # Release the video capture object and close the display window
+    cap.release()
+    
+    if torch.cuda.is_available():
+        torch.cuda.empty_cache()
+    del model
+
+