diff --git a/YOLOv8/yolov8_detector.py b/YOLOv8/yolov8_detector.py
index fd5e318..484b827 100644
--- a/YOLOv8/yolov8_detector.py
+++ b/YOLOv8/yolov8_detector.py
@@ -1,11 +1,14 @@
 # yolov8_inference_with_colors.py
 import os
-
+import time
 import numpy as np
 import sophon_chakcy.sail as sail
 from .postprocess_numpy import PostProcess
 from sqlite_vfs.core import SQLiteVFS
 from dataclasses import dataclass, field
+from typing import Optional
+import threading
+
 
 @dataclass
 class YOLOv8Config:
@@ -149,37 +152,17 @@ class Detector:
         
         return img_bgr_planar
     
-    def detect_single_image(self, image_path, output_dir="./detection_results"):
+    def preprocess(self, bmimg: sail.BMImage):
         """
-        检测单张图像
-        
+        预处理图像
+
         Args:
-            image_path: 图像路径
-            output_dir: 输出目录
-        
+            image: 输入图像 (HWC, BGR格式)
+
         Returns:
-            检测结果列表
+            (预处理后的BMImage, 原始尺寸, 缩放比例, 填充偏移)
         """
-        # 创建输出目录
-        os.makedirs(output_dir, exist_ok=True)
-        
-        print(f"\n处理图像: {image_path}")
-        
-        # 1. 解码图像
-        decoder = sail.Decoder(image_path, True, self.dev_id)
-        bmimg = sail.BMImage()
-        ret = decoder.read(self.handle, bmimg)
-        
-        if ret != 0:
-            print(f"错误: 无法解码图像 {image_path}")
-            return []
-        
-        orig_width = bmimg.width()
-        orig_height = bmimg.height()
-        print(f"图像大小: {orig_width}x{orig_height}")
-        
-        # 2. 预处理
-        # 转换为RGB格式
+        # 转换为RGB
         rgb_img = sail.BMImage(self.handle, bmimg.height(), bmimg.width(),
                                sail.Format.FORMAT_RGB_PLANAR, sail.DATA_TYPE_EXT_1N_BYTE)
         self.bmcv.convert_format(bmimg, rgb_img)
@@ -217,6 +200,16 @@ class Detector:
                              (self.ab[2], self.ab[3]), 
                              (self.ab[4], self.ab[5])))
         
+        return preprocessed_img, r, tx1, ty1
+
+    def detect(self, bmimg: sail.BMImage):
+        orig_width = bmimg.width()
+        orig_height = bmimg.height()
+        print(f"图像大小: {orig_width}x{orig_height}")
+        
+        # 2. 预处理
+        preprocessed_img, r, tx1, ty1 = self.preprocess(bmimg)
+
         # 3. 准备输入张量
         input_tensor = sail.Tensor(self.handle, self.input_shape, self.input_dtype, False, False)
         self.bmcv.bm_image_to_tensor(preprocessed_img, input_tensor)
@@ -245,6 +238,38 @@ class Detector:
         
         # 执行后处理
         detections = self.postprocess([pred_with_batch], org_size_list, ratios_batch, txy_batch)
+        return detections
+
+    def detect_single_image(self, image_path, output_dir="./detection_results"):
+        """
+        检测单张图像
+        
+        Args:
+            image_path: 图像路径
+            output_dir: 输出目录
+        
+        Returns:
+            检测结果列表
+        """
+        # 创建输出目录
+        os.makedirs(output_dir, exist_ok=True)
+        
+        print(f"\n处理图像: {image_path}")
+        
+        # 1. 解码图像
+        decoder = sail.Decoder(image_path, True, self.dev_id)
+        bmimg = sail.BMImage()
+        ret = decoder.read(self.handle, bmimg)
+        
+        if ret != 0:
+            print(f"错误: 无法解码图像 {image_path}")
+            return []
+        
+        orig_width = bmimg.width()
+        orig_height = bmimg.height()
+        print(f"图像大小: {orig_width}x{orig_height}")
+        
+        detections = self.detect(bmimg)
         
         if len(detections) > 0:
             detections = detections[0]  # 取第一个batch的结果
diff --git a/main.py b/main.py
index a8a18ff..cf7c2c3 100644
--- a/main.py
+++ b/main.py
@@ -1,6 +1,19 @@
-import os
 import argparse
 from sophon_chakcy.get_detector import get_detector
+from sophon_chakcy.utils.detect_video_stream import DetectVideoStream
+from threading import Thread
+
+
+def detector_task(args):
+    detector_class, model_config = get_detector(args.name, True)
+    detector = detector_class(model_config, True, dev_id=args.dev_id, conf_thresh=args.conf_thresh, nms_thresh=args.nms_thresh)
+    detect_video_stream = DetectVideoStream([detector], args.input)
+    t = Thread(target=detect_video_stream.run_task)
+    t.start()
+    import time
+    time.sleep(5)
+    detect_video_stream.stop_task()
+    t.join()
 
 
 def main():
@@ -12,22 +25,9 @@ def main():
     parser.add_argument('--nms_thresh', type=float, default=0.7, help='NMS阈值')
     
     args = parser.parse_args()
-    
-    detector_class, model_config = get_detector(args.name)
 
-    # 初始化检测器
-    detector = detector_class(model_config, False, dev_id=args.dev_id, conf_thresh=args.conf_thresh, nms_thresh=args.nms_thresh)
-    
-    # 根据输入类型进行处理
-    if os.path.isfile(args.input):
-        # 单张图像
-        detector.detect_single_image(args.input)
+    detector_task(args)
 
-    elif os.path.isdir(args.input):
-        # 图像目录
-        detector.detect_images_in_directory(args.input)
-    else:
-        print(f"错误: {args.input} 既不是文件也不是目录")
 
 if __name__ == "__main__":
-    main()
\ No newline at end of file
+    main()
diff --git a/public/main.py b/public/main.py
index 9713396..836c083 100644
--- a/public/main.py
+++ b/public/main.py
@@ -2,27 +2,15 @@ import os
 import argparse
 from sophon_chakcy.get_detector import get_detector
 from module_bank import PythonToSQLite
+from multiprocessing import Process
 
 # 安装导入器
 packer = PythonToSQLite("plugins.mbank")
 finder = packer.install_importer()
 
-
-def main():
-    parser = argparse.ArgumentParser(description="YOLOv8目标检测")
-    parser.add_argument('--name', type=str, required=True, help='算法名称')
-    parser.add_argument('--input', type=str, required=True, help='输入图像或目录路径')
-    parser.add_argument('--dev_id', type=int, default=0, help='设备ID')
-    parser.add_argument('--conf_thresh', type=float, default=0.25, help='置信度阈值')
-    parser.add_argument('--nms_thresh', type=float, default=0.7, help='NMS阈值')
-    
-    args = parser.parse_args()
-    
+def detector_task(args):
     detector_class, model_config = get_detector(args.name, True)
-
-    # 初始化检测器
     detector = detector_class(model_config, True, dev_id=args.dev_id, conf_thresh=args.conf_thresh, nms_thresh=args.nms_thresh)
-    
     # 根据输入类型进行处理
     if os.path.isfile(args.input):
         # 单张图像
@@ -34,5 +22,37 @@ def main():
     else:
         print(f"错误: {args.input} 既不是文件也不是目录")
 
+
+def main():
+    parser = argparse.ArgumentParser(description="YOLOv8目标检测")
+    parser.add_argument('--name', type=str, required=True, help='算法名称')
+    parser.add_argument('--input', type=str, required=True, help='输入图像或目录路径')
+    parser.add_argument('--dev_id', type=int, default=0, help='设备ID')
+    parser.add_argument('--conf_thresh', type=float, default=0.25, help='置信度阈值')
+    parser.add_argument('--nms_thresh', type=float, default=0.7, help='NMS阈值')
+    
+    args = parser.parse_args()
+
+    p = Process(target=detector_task,args=(args,))
+    p.start()
+    p.join()
+    
+    # detector_class, model_config = get_detector(args.name, True)
+    
+    # # 初始化检测器
+    # detector = detector_class(model_config, True, dev_id=args.dev_id, conf_thresh=args.conf_thresh, nms_thresh=args.nms_thresh)
+    
+    # # 根据输入类型进行处理
+    # if os.path.isfile(args.input):
+    #     # 单张图像
+    #     detector.detect_single_image(args.input)
+
+    # elif os.path.isdir(args.input):
+    #     # 图像目录
+    #     detector.detect_images_in_directory(args.input)
+    # else:
+    #     print(f"错误: {args.input} 既不是文件也不是目录")
+
+
 if __name__ == "__main__":
-    main()
\ No newline at end of file
+    main()
diff --git a/src/sophon_chakcy/__init__.py b/src/sophon_chakcy/__init__.py
index 9e00bbb..9109bbd 100644
--- a/src/sophon_chakcy/__init__.py
+++ b/src/sophon_chakcy/__init__.py
@@ -23,18 +23,3 @@ def get_config(json_path: str, is_vfs: bool = False, vfs_path: str="./applicatio
         with open(json_path, 'r') as file:
             data = json.load(file)
     return data
-
-
-def is_img(file_name):
-    """judge the file is available image or not
-    Args:
-        file_name (str): input file name
-    Returns:
-        (bool) : whether the file is available image
-    """
-    fmt = os.path.splitext(file_name)[-1]
-    if isinstance(fmt, str) and fmt.lower() in ['.jpg','.png','.jpeg','.bmp','.jpeg','.webp']:
-        return True
-    else:
-        return False
-
diff --git a/src/sophon_chakcy/utils/__init__.py b/src/sophon_chakcy/utils/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/src/sophon_chakcy/utils/detect_video_stream.py b/src/sophon_chakcy/utils/detect_video_stream.py
new file mode 100644
index 0000000..c63f547
--- /dev/null
+++ b/src/sophon_chakcy/utils/detect_video_stream.py
@@ -0,0 +1,154 @@
+import sophon_chakcy.sail as sail
+import threading
+import time
+
+
+class DetectVideoStream:
+    def __init__(self, 
+                 detectors, 
+                 video_path: str, 
+                 max_frames: int = 0, 
+                 frame_skip: int = 0, 
+                 reconnect_attempts: int = 3, 
+                 reconnect_delay: int = 5,
+                 is_save: bool = False):
+        """
+        处理视频流（视频文件或RTSP流）
+
+        Args:
+            detector: 检测器
+            video_path: 视频文件路径或 RTSP URL
+            max_frames: 最大处理帧数, 0表示处理所有帧
+            frame_skip: 跳帧处理, 0表示处理每一帧
+            reconnect_attempts: RTSP断流重连尝试次数
+            reconnect_delay: 重连延迟时间 (秒)
+        
+        Returns:
+            处理的帧数, 检测到的物体总数
+        """
+        self.detectors = detectors
+        self.dev_id = self.detectors[0].dev_id
+        self.handle = self.detectors[0].handle
+        self.video_path = video_path
+        self.max_frames = max_frames
+        self.frame_skip = frame_skip
+        if not video_path.startswith("rtsp"):
+            self.reconnect_attempts = 0
+        else:
+            self.reconnect_attempts = reconnect_attempts
+        self.reconnect_delay = reconnect_delay
+        self.decoder = sail.Decoder(video_path, True, self.dev_id)
+        self.stop_event = threading.Event()
+        self.is_save = is_save
+        if self.is_save:
+            import os
+            from pathlib import Path
+            import shutil
+
+            result_dir = r"results"
+             # 清理旧的目录
+            if os.path.exists(result_dir):
+                print(f"清理旧的构建目录: {result_dir}")
+                shutil.rmtree(result_dir, ignore_errors=True)
+            
+            # 创建目录
+            result_dir_path = Path(result_dir)
+            if not result_dir_path.exists():
+                result_dir_path.mkdir(parents=True, exist_ok=True)
+
+            enc_params = f"width=1920:height=1080:bitrate=2000:gop=32:gop_preset=2:framerate=25"
+            self.encoder = sail.Encoder("results/output.mp4", self.dev_id, 'h264_bm', 'NV12', enc_params, 10)
+    
+    def run_task(self):     
+        if not self.decoder.is_opened():
+            print(f"错误: 无法打开视频流 {self.video_path}")
+            return 0, 0
+
+        frame_shape = self.decoder.get_frame_shape()
+        print(f"视频帧形状: {frame_shape}")
+
+        frame_count = 0
+        reconnect_count = 0
+
+        try:
+            while not self.stop_event.is_set():
+                if self.max_frames > 0 and frame_count >= self.max_frames:
+                    print(f"\n达到最大帧数限制: {self.max_frames}")
+                    break
+                    
+                # 读取一帧
+                bmimg = sail.BMImage()
+                ret = self.decoder.read(self.handle, bmimg)
+                if ret != 0:
+                    print(f"读取帧失败，错误码: {ret}")
+                    reconnect_count += 1
+
+                    if reconnect_count > self.reconnect_attempts:
+                        print("视频流无法继续读取")
+                        break
+
+                    print(f"尝试重连 ({reconnect_count}/{self.reconnect_attempts})...")
+                    time.sleep(self.reconnect_delay)
+                    self.decoder.release()
+                    decoder = sail.Decoder(self.video_path, True, self.dev_id)
+                    if decoder.is_opened():
+                        reconnect_count = 0
+                        print("重连成功，继续处理...")
+                        continue
+                    else:
+                        print("重连失败")
+                
+                if self.frame_skip > 0 and frame_count % (self.frame_skip + 1) != 0:
+                    frame_count += 1
+                    if self.is_save:
+                        self.encoder.video_write(bmimg)
+                    continue
+
+                # 开始处理当前帧
+                start_time = time.time()
+                frame_count += 1
+
+                if frame_count % 10 == 0:
+                    print(f"处理第 {frame_count} 帧...")
+                    
+                # 检测
+                for detector in self.detectors:
+                    detections = detector.detect(bmimg)
+
+                    if len(detections) > 0:
+                        detections = detections[0]
+
+                        filtered_detections = []
+                        for det in detections:
+                            if len(det) >= 6:
+                                x1, y1, x2, y2, conf, cls_id = det[:6]
+                                if conf > detector.conf_thresh:
+                                    filtered_detections.append([x1, y1, x2, y2, conf, cls_id])
+
+                        if len(filtered_detections) > 0:
+                            result_img = detector.draw_detections(bmimg, filtered_detections, None)
+                        else:
+                            result_img = bmimg
+                    else:
+                        result_img = bmimg
+                
+                if self.is_save:
+                    self.encoder.video_write(result_img)
+
+        except KeyboardInterrupt:
+            print("\n检测到键盘中断，停止处理")
+        except Exception as e:
+            print(f"处理视频流时发生错误: {e}")
+
+        finally:
+            # 清理资源
+            self.decoder.release()
+            if self.is_save:
+                self.encoder.release()
+            print("视频解码器已释放")
+
+    def stop_task(self):
+        print("提前关闭")
+        self.stop_event.set()
+
+
diff --git a/src/sophon_chakcy/utils/task_manger.py b/src/sophon_chakcy/utils/task_manger.py
new file mode 100644
index 0000000..e69de29