0731更新前后帧判断逻辑，固定时长剪辑逻辑

Bank_second_part/detect_process/video_process.py

@@ -3,14 +3,17 @@ import cv2
 import os
 import time
 
-from ultralytics import yolo
+from ultralytics import YOLO 
 import queue
 
 import threading
 from config import Q_SZ
 
 from ModelDet.personDet import analysis_yolov8
-from ModelDet.holisticDet import MediapipeProcess
+from tools import Process_tools
+# from ModelDet.holisticDet import MediapipeProcess
+
+
 
 class DealVideo():
 
@@ -36,6 +39,7 @@ class DealVideo():
         #线程
         self.get_video_listThread = threading.Thread(target=self.get_video_list)
         self.get_video_frameThread = threading.Thread(target=self.get_video_frame)
+        self.person_detThread = threading.Thread(target=self.person_det)
         self.write_videoThread = threading.Thread(target=self.write_video)
         
 
@@ -80,7 +84,7 @@ class DealVideo():
                     while cap.isOpened():
                         success, frame = cap.read()
                         if not success:
-                            print("Ignoring empty camera frame.")
+                            print(video_path,"Ignoring empty camera frame.")
                             break
                         count_fps  += 1
 
@@ -95,21 +99,84 @@ class DealVideo():
 
     def person_det(self):
 
+        '''
+        从队列中获取视频帧frame，进行第一步人员的检测
+        '''
+
         while True: 
 
             if ~self.frameQueue.empty():
 
-                video_dict = self.frameQueue.get()
+                video_frame_dict = self.frameQueue.get()
+
+                frame_list = video_frame_dict['frame_list']
+
+                frame_result_contact = []
+
+                for i in range(len(frame_list)):
 
-                person_det = analysis_yolov8(frame=video_dict,model_coco=self.person_model,confidence_set=0.5)
+                    if frame_list[i]["fps"] == i + 1:                
 
+                        person_det = analysis_yolov8(frame=frame_list[i]['frame'],
+                                                     model_coco=self.person_model,
+                                                     confidence_set=0.5)
+                        
+                        # 当前帧检测的结果列表，只包含bboxlist
+                        person_list = Process_tools.get_dict_values(person_det)
 
-        # pass
+                        # 保存第一帧结果为对比坐标
+                        if not frame_result_contact:
 
+                            bbox_list_all = Process_tools.change_list_dict(fps1=frame_list[i]["fps"],re_list=person_list)
 
-    def write_video(self):
+                            frame_result_contact = bbox_list_all
+                            print("frame_result_contact:",frame_result_contact)
 
-        '''
+                        else:
+
+                            example_dict_list = frame_result_contact
+
+                            cut_list,example_lst,re_dict_lst = Process_tools.analysis_re01_list(example_list=example_dict_list,
+                                                                                                              result_list=person_list)
+                            
+                            print('cut_list:',cut_list)
+                            print('example_sorted_lst:',example_lst)
+                            print('re_dict_sorted_lst:',re_dict_lst)
+
+
+                            # 统计截止时间
+                            time_out_list = Process_tools.statistics_fps(fps_now=frame_list[i]["fps"],re_list=frame_result_contact)
+                            
+                            if time_out_list:
+
+                                # bbox_list = Process_tools.change_dict_list(time_out_list)
+
+                                # 裁剪保存视频
+                                # cut_dict = {"start_fps":time_out_list[0]['fps'],"stop_fps":frame_list[i]["fps"],'bbox_list':bbox_list}
+
+                                frame_result_contact = [item for item in frame_result_contact if item not in time_out_list]
+                        
+                            # 有目标减少情况
+                            if example_lst:
+
+                                # cut_dict = {"start_fps":frame_result_contact[0]['fps'],"stop_fps":frame_list[i]["fps"],'bbox_list':example_lst}
+
+                                frame_result_contact = [item for item in frame_result_contact if item not in example_lst]
+                                
+                            # 有新添加目标情况
+                            if re_dict_lst:
+
+                                
+                                update_list = Process_tools.change_list_dict(fps1=frame_list[i]["fps"],re_list=re_dict_lst)
+
+                                frame_result_contact = frame_result_contact + update_list
+
+                        print('frame_result_contact:',frame_result_contact)
+                      
+
+    def write_video(self): 
+
+        '''  
         保存成视频
         '''
 
@@ -147,11 +214,8 @@ class DealVideo():
 
         self.get_video_listThread.start()
         self.get_video_frameThread.start()
-        self.write_videoThread.start()
-
-
-
-
+        self.person_detThread.start()
+        # self.write_videoThread.start()
 
 
 
@@ -161,11 +225,13 @@ if __name__ == '__main__':
     # 每个视频的时长（单位秒）
     dertTime = 5
 
-    video = "E:/Bank_files/Bank_02/dataset/video_person/after_1/"
+    video = "E:/Bank_files/Bank_02/dataset/video_test"
     video_save = 'videos_codes_2'
 
+    person_model = YOLO("model_file/yolov8x_person.pt")
+
     # get_seg_video(video_file=video,video_save_path=video_save,dertTime=dertTime)
-    deal = DealVideo(video_file=video,video_save_file=video_save)
+    deal = DealVideo(video_file=video,video_save_file=video_save,person_model=person_model,mediapipe_model='model_file/yolov8x_person.pt',pptsmv2_model='model_file/yolov8x_person.pt')
     deal.run()