diff --git a/Bank_second_part/dataset_deal/video_list_split.py b/Bank_second_part/dataset_deal/video_list_split.py
new file mode 100644
index 0000000..efb41a3
--- /dev/null
+++ b/Bank_second_part/dataset_deal/video_list_split.py
@@ -0,0 +1,44 @@
+import os
+
+def save_file_paths_with_labels(folder_path, train_ratio, valid_ratio, test_ratio, label):
+    # 获取文件夹下所有文件的路径
+    file_paths = []
+    for root, dirs, files in os.walk(folder_path):
+        for file in files:
+            file_path = os.path.join(root, file)
+            file_paths.append(file_path)
+
+    # 计算每个集合的文件数目
+    total_files = len(file_paths)
+    train_files = int(total_files * train_ratio)
+    valid_files = int(total_files * valid_ratio)
+    test_files = int(total_files * test_ratio)
+
+    # 根据比例拆分文件路径列表
+    train_paths = file_paths[:train_files]
+    valid_paths = file_paths[train_files:train_files + valid_files]
+    test_paths = file_paths[train_files + valid_files:train_files + valid_files + test_files]
+
+    # 为文件路径添加标签
+    train_paths_labeled = [path + ' ' + str(label) for path in train_paths]
+    valid_paths_labeled = [path + ' ' + str(label) for path in valid_paths]
+    test_paths_labeled = [path + ' ' + str(label) for path in test_paths]
+
+    # 将文件路径保存到txt文件
+    save_to_txt(train_paths_labeled, 'train.txt')
+    save_to_txt(valid_paths_labeled, 'valid.txt')
+    save_to_txt(test_paths_labeled, 'test.txt')
+
+def save_to_txt(file_paths, filename):
+    with open(filename, 'w') as file:
+        for file_path in file_paths:
+            file.write(file_path + '\n')
+
+# 示例用法
+folder_path = 'dataset/video_seg_re_hand'  # 替换为实际的文件夹路径
+train_ratio = 0.8  # 训练集比例
+valid_ratio = 0.2  # 验证集比例
+test_ratio = 0.0  # 测试集比例
+label = '1'  # 替换为实际的标签
+
+save_file_paths_with_labels(folder_path, train_ratio, valid_ratio, test_ratio, label)
\ No newline at end of file
diff --git a/Bank_second_part/dataset_deal/video_model.py b/Bank_second_part/dataset_deal/video_model.py
new file mode 100644
index 0000000..efa8da5
--- /dev/null
+++ b/Bank_second_part/dataset_deal/video_model.py
@@ -0,0 +1,179 @@
+import numpy as np
+import cv2
+import os
+import time
+from tqdm import tqdm
+from ultralytics import YOLO
+from ultralytics.yolo.utils.plotting import Annotator
+
+from yolov8_det import analysis_yolov8
+
+model_yolo = YOLO("E:/Bank_files/Bank_02/model_files/all_labels.pt")
+
+
+# 图像文件夹
+def get_video_list(path):
+    video_ext = [".mp4", ".avi",".MP4"]
+    video_names = []
+    for maindir, subdir, file_name_list in os.walk(path):
+        for filename in file_name_list:
+            apath = os.path.join(maindir, filename)
+            ext = os.path.splitext(apath)[1]
+            if ext in video_ext:
+                video_names.append(apath)
+    return video_names
+
+
+# 截取裁剪需要的视频帧
+def save_seg_video(video_name,frameToStart,frametoStop,videoWriter,bbox):
+
+    cap = cv2.VideoCapture(video_name)
+    count = 0
+
+    while True:
+
+        success, frame = cap.read()
+
+        if success:
+
+            count += 1
+            if count <= frametoStop and count > frameToStart:  # 选取起始帧
+                print('correct= ', count)
+                
+                #裁剪视频画面
+                frame_target = frame[int(bbox[1]):int(bbox[3]), int(bbox[0]):int(bbox[2])]  # (split_height, split_width)
+
+                videoWriter.write(frame_target)
+                
+        if not success or count >= frametoStop:
+            break
+
+        print('end')  
+
+
+
+# 对视频的操作
+def get_seg_video(video_file,video_save_path,dertTime):
+
+
+    # 检查路径
+    print("frame image save path：{}".format(video_save_path))
+    os.makedirs(video_save_path, exist_ok=True)
+    
+    if os.path.isdir(video_file):
+        files = get_video_list(video_file)
+    else:
+        files = [video_file]
+
+    files.sort()
+    video_num = len(files)
+
+    for num in range(video_num):
+
+        # 视频名字
+        video_name = files[num]
+
+        print(video_name)
+        video_basename = os.path.basename(video_name).split('.')[0]
+
+        cap = cv2.VideoCapture(video_name)
+        #帧率
+        fps = cap.get(cv2.CAP_PROP_FPS)
+
+        success,frame = cap.read()
+
+        count_fps = 0
+        write_fps = 0
+        dertTime = 2
+        # 每段帧率
+        dertF = dertTime * fps
+
+        # while True:
+
+        # 前后帧信息保存
+
+        # result_list = []
+
+        # count_result_num = 0
+
+        while success:
+
+                count_fps  += 1
+
+                # 调用模型，逐帧检测
+                results_img = analysis_yolov8(frame=frame,
+                                            model_coco=model_yolo,
+                                            confidence=0.1)
+                
+
+                # result_list.append({count_fps:results_img})
+
+                # if len(result_list) == 5:
+
+                #     result_list.clear()
+
+                
+                # num = len(results_img)
+
+                # # 如果只检测到一个人
+                if num == 1:
+
+                    # 起始帧
+                    write_fps = count_fps
+
+                    stop_fps = write_fps + dertF
+
+                    # 目标检测结果
+
+                    bbox = list(results_img[0].values())[0]
+                    w = bbox[2] -bbox[0]
+                    h = bbox[3] -bbox[1]
+                    size = [int(w),int(h)]
+                    # 保存截取视频
+                    video_name_save = video_save_path + '/' +  video_basename + '_' +str(write_fps) + '.avi'
+
+                    videoWriter =cv2.VideoWriter(video_name_save,cv2.VideoWriter_fourcc('X','V','I','D'),fps,size)                    
+
+                    save_seg_video(video_name,write_fps,stop_fps,videoWriter,bbox)
+
+                    # result_dict = {count_fps:bbox}
+
+                    # result_list.append(result_dict)
+                    
+                    # print(count_fps,write_fps,stop_fps,video_name,bbox)
+
+                    break
+
+                # if num == 0:
+
+                #     continue
+
+                # if num > 1:
+
+                #     # print()
+                #     pass
+
+
+
+if __name__ == '__main__':  
+     
+
+    # 每个视频的时长（单位秒）
+    dertTime = 5
+
+    video = "E:/Bank_files/Bank_02/dataset/vlc_0711/0711-1.mp4"
+    video_save = 'videos_codes_2'
+
+    get_seg_video(video_file=video,video_save_path=video_save,dertTime=dertTime)
+
+
+
+    
+
+
+
+
+
+
+
+
diff --git a/Bank_second_part/dataset_deal/video_resize_xy.py b/Bank_second_part/dataset_deal/video_resize_xy.py
new file mode 100644
index 0000000..c4ac974
--- /dev/null
+++ b/Bank_second_part/dataset_deal/video_resize_xy.py
@@ -0,0 +1,92 @@
+import os.path
+import cv2
+import glob
+
+
+def get_video_list(path):
+    video_ext = [".mp4", ".avi",".MP4"]
+    video_names = []
+    for maindir, subdir, file_name_list in os.walk(path):
+        for filename in file_name_list:
+            apath = os.path.join(maindir, filename)
+            ext = os.path.splitext(apath)[1]
+            if ext in video_ext:
+                video_names.append(apath)
+    return video_names
+
+
+
+def split_video(input_video, output_video,size_file):
+
+
+    print("frame image save path：{}".format(output_video))
+    os.makedirs(output_video, exist_ok=True)
+
+    if os.path.isdir(input_video):
+        files = get_video_list(input_video)
+    else:
+        files = [input_video]
+
+    files.sort()
+    video_num = len(files)
+
+    print('files',files)
+
+    for i in range(video_num):
+
+        video_name = files[i]
+        video_basename = os.path.basename(video_name)
+
+        print('video_name:',video_name)
+     
+        video_caputre = cv2.VideoCapture(video_name)
+
+        # get video parameters
+        fps = video_caputre.get(cv2.CAP_PROP_FPS)
+        # width = video_caputre.get(cv2.CAP_PROP_FRAME_WIDTH)
+        # height = video_caputre.get(cv2.CAP_PROP_FRAME_HEIGHT)
+
+        # print("fps:", fps)
+        # print("width:", width)
+        # print("height:", height)
+
+        # 定义截取尺寸,后面定义的每帧的h和w要于此一致，否则视频无法播放
+        split_width = int(size_file[2] - size_file[0])
+        split_height = int(size_file[3] - size_file[1])
+        size = (split_width, split_height)
+
+        print('size_file:',size_file)
+
+        fourcc = cv2.VideoWriter_fourcc('M', 'J', 'P', 'G')
+        # 创建视频写入对象
+        output_path = output_video + '/' + video_basename
+        videp_write = cv2.VideoWriter(output_path, fourcc, fps, size)
+
+        print('output_path:',output_path)
+
+        print('Start!!!')
+        # 读取视频帧
+        success, frame_src = video_caputre.read()  # (960, 2560, 3)  # (height, width, channel)
+        while success and not cv2.waitKey(1) == 27:  # 读完退出或者按下 esc 退出
+
+            # [width, height] 要与上面定义的size参数一致，注意参数的位置
+            # frame_target = frame_src[0:split_height, 0:split_width]  # (split_height, split_width)
+            frame_target = frame_src[size_file[1]:size_file[3], size_file[0]:size_file[2]]  # (split_height, split_width)
+            # print('size_file1:',size_file)
+            # 写入视频文件
+            videp_write.write(frame_target)
+            # 不断读取
+            success, frame_src = video_caputre.read()
+
+        print("Finished!!!")
+        video_caputre.release()
+
+if __name__ == '__main__':
+
+    
+    input_file = 'E:/Bank_files/Bank_02/dataset/video_seg_2s'
+    output_file = 'E:/Bank_files/Bank_02/dataset/dataset_01_set/video_seg_head'
+
+    #xmin,ymin,xmax,ymax
+    bbox = [500,350,900,700]
+    split_video(input_video=input_file, output_video=output_file,size_file=bbox)
diff --git a/Bank_second_part/dataset_deal/video_seg.py b/Bank_second_part/dataset_deal/video_seg.py
new file mode 100644
index 0000000..99be502
--- /dev/null
+++ b/Bank_second_part/dataset_deal/video_seg.py
@@ -0,0 +1,134 @@
+import numpy as np
+import cv2
+import os
+import time
+
+def get_video_list(path):
+    video_ext = [".mp4", ".avi",".MP4"]
+    video_names = []
+    for maindir, subdir, file_name_list in os.walk(path):
+        for filename in file_name_list:
+            apath = os.path.join(maindir, filename)
+            ext = os.path.splitext(apath)[1]
+            if ext in video_ext:
+                video_names.append(apath)
+    return video_names
+
+
+def save_seg_video(video_name,frameToStart,frametoStop,videoWriter):
+
+    cap = cv2.VideoCapture(video_name)
+    count = 0
+
+    while True:
+
+        success, frame = cap.read()
+
+        # count += 1
+        if success:
+    
+            print('frametoStop:',frametoStop,'frameToStart:',frameToStart)
+            print('correct2= ', count)
+            count += 1
+            if count <= frametoStop and count > frameToStart:  # 选取起始帧
+                print('correct= ', count)
+                videoWriter.write(frame)
+                
+        if not success or count >= frametoStop:
+            break
+
+        print('end')  
+
+
+def get_seg_video(video_file,video_save_path,dertTime):
+
+
+    # 检查路径
+    print("frame image save path：{}".format(video_save_path))
+    os.makedirs(video_save_path, exist_ok=True)
+    
+    if os.path.isdir(video_file):
+        files = get_video_list(video_file)
+    else:
+        files = [video_file]
+
+    files.sort()
+    video_num = len(files)
+
+    for num in range(video_num):
+
+        # 视频名字
+        video_name = files[num]
+        video_basename = os.path.basename(video_name).split('.')[0]
+
+        cap = cv2.VideoCapture(video_name)
+
+        #帧率
+        fps = cap.get(cv2.CAP_PROP_FPS)
+        fps = int(fps)
+
+        print(fps)
+
+        # 获得原视频尺寸
+        size = (int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)), int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)))
+
+        # 获取视频总帧数
+        total_frame = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))  
+
+        # 每段帧率
+        dertF = dertTime * fps
+
+        print('dertF:',dertF)
+
+        #帧率分段
+        n = total_frame/dertF
+
+        print(int(n))
+
+
+        for i in range(int(n) + 1):
+
+
+            video_name_save = video_save_path + '/' +  video_basename + '_' +str(i) + '.avi'
+
+            videoWriter =cv2.VideoWriter(video_name_save,cv2.VideoWriter_fourcc('X','V','I','D'),fps,size)
+
+            start_time = i * dertF
+
+            if i == int(n) + 1:
+
+                stop_time = total_frame
+            
+            else:
+                stop_time = start_time + dertF
+
+
+            print(video_name)
+
+            save_seg_video(video_name=video_name,frameToStart=start_time,frametoStop=stop_time,videoWriter=videoWriter)
+
+
+
+
+if __name__ == '__main__':  
+     
+
+    # 每个视频的时长（单位秒）
+    dertTime = 5
+
+    video = "dataset/video"
+    video_save = 'dataset/video_seg_5s'
+
+    get_seg_video(video_file=video,video_save_path=video_save,dertTime=dertTime)
+
+
+
+    
+
+
+
+
+
+
+
+
diff --git a/Bank_second_part/dataset_deal/yolov8_det.py b/Bank_second_part/dataset_deal/yolov8_det.py
new file mode 100644
index 0000000..25add17
--- /dev/null
+++ b/Bank_second_part/dataset_deal/yolov8_det.py
@@ -0,0 +1,47 @@
+
+
+
+def analysis_yolov8(frame, model_coco,confidence):
+
+    # 第一步：用COCO数据集推理
+    results_coco = model_coco(frame)
+    # print('results_coco:',results_coco)
+    if results_coco:
+
+        for r in results_coco:
+
+            boxes = r.boxes
+
+        re_dict_all = {}
+
+        re_list = []
+        idx = 0
+        for box in boxes:
+
+            idx += 1
+
+            b = box.xyxy[0]  # get box coordinates in (top, left, bottom, right) format
+            c = box.cls
+
+            # 保存标签和坐标值作为返回结果
+            blist = b.tolist()
+            labels_name = model_coco.names[int(c)]
+ 
+            confidence = float(box.conf)
+                    
+            confidence = round(confidence, 2)
+
+            # 过滤置信度0.5以下目标
+            if confidence < confidence:
+
+                continue
+            
+            # 一个结果字典
+            re_dict = [labels_name,blist]
+
+            re_list.append(re_dict)
+
+            # key = f"detection{idx}"
+            # re_dict_all[key] = re_dict
+
+    return re_list