diff --git a/deploy/pipeline/cfg_utils.py b/deploy/pipeline/cfg_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..1e42b29c04068a55fe09d5c16c92fcc25b1fb7cd
--- /dev/null
+++ b/deploy/pipeline/cfg_utils.py
@@ -0,0 +1,204 @@
+import ast
+import yaml
+import copy
+import argparse
+from argparse import ArgumentParser, RawDescriptionHelpFormatter
+
+
+class ArgsParser(ArgumentParser):
+    def __init__(self):
+        super(ArgsParser, self).__init__(
+            formatter_class=RawDescriptionHelpFormatter)
+        self.add_argument(
+            "-o", "--opt", nargs='*', help="set configuration options")
+
+    def parse_args(self, argv=None):
+        args = super(ArgsParser, self).parse_args(argv)
+        assert args.config is not None, \
+            "Please specify --config=configure_file_path."
+        args.opt = self._parse_opt(args.opt)
+        return args
+
+    def _parse_opt(self, opts):
+        config = {}
+        if not opts:
+            return config
+        for s in opts:
+            s = s.strip()
+            k, v = s.split('=', 1)
+            if '.' not in k:
+                config[k] = yaml.load(v, Loader=yaml.Loader)
+            else:
+                keys = k.split('.')
+                if keys[0] not in config:
+                    config[keys[0]] = {}
+                cur = config[keys[0]]
+                for idx, key in enumerate(keys[1:]):
+                    if idx == len(keys) - 2:
+                        cur[key] = yaml.load(v, Loader=yaml.Loader)
+                    else:
+                        cur[key] = {}
+                        cur = cur[key]
+        return config
+
+
+def argsparser():
+    parser = ArgsParser()
+
+    parser.add_argument(
+        "--config",
+        type=str,
+        default=None,
+        help=("Path of configure"),
+        required=True)
+    parser.add_argument(
+        "--image_file", type=str, default=None, help="Path of image file.")
+    parser.add_argument(
+        "--image_dir",
+        type=str,
+        default=None,
+        help="Dir of image file, `image_file` has a higher priority.")
+    parser.add_argument(
+        "--video_file",
+        type=str,
+        default=None,
+        help="Path of video file, `video_file` or `camera_id` has a highest priority."
+    )
+    parser.add_argument(
+        "--video_dir",
+        type=str,
+        default=None,
+        help="Dir of video file, `video_file` has a higher priority.")
+    parser.add_argument(
+        "--camera_id",
+        type=int,
+        default=-1,
+        help="device id of camera to predict.")
+    parser.add_argument(
+        "--output_dir",
+        type=str,
+        default="output",
+        help="Directory of output visualization files.")
+    parser.add_argument(
+        "--run_mode",
+        type=str,
+        default='paddle',
+        help="mode of running(paddle/trt_fp32/trt_fp16/trt_int8)")
+    parser.add_argument(
+        "--device",
+        type=str,
+        default='cpu',
+        help="Choose the device you want to run, it can be: CPU/GPU/XPU, default is CPU."
+    )
+    parser.add_argument(
+        "--enable_mkldnn",
+        type=ast.literal_eval,
+        default=False,
+        help="Whether use mkldnn with CPU.")
+    parser.add_argument(
+        "--cpu_threads", type=int, default=1, help="Num of threads with CPU.")
+    parser.add_argument(
+        "--trt_min_shape", type=int, default=1, help="min_shape for TensorRT.")
+    parser.add_argument(
+        "--trt_max_shape",
+        type=int,
+        default=1280,
+        help="max_shape for TensorRT.")
+    parser.add_argument(
+        "--trt_opt_shape",
+        type=int,
+        default=640,
+        help="opt_shape for TensorRT.")
+    parser.add_argument(
+        "--trt_calib_mode",
+        type=bool,
+        default=False,
+        help="If the model is produced by TRT offline quantitative "
+        "calibration, trt_calib_mode need to set True.")
+    parser.add_argument(
+        "--do_entrance_counting",
+        action='store_true',
+        help="Whether counting the numbers of identifiers entering "
+        "or getting out from the entrance. Note that only support single-class MOT."
+    )
+    parser.add_argument(
+        "--do_break_in_counting",
+        action='store_true',
+        help="Whether counting the numbers of identifiers break in "
+        "the area. Note that only support single-class MOT and "
+        "the video should be taken by a static camera.")
+    parser.add_argument(
+        "--region_type",
+        type=str,
+        default='horizontal',
+        help="Area type for entrance counting or break in counting, 'horizontal' and "
+        "'vertical' used when do entrance counting. 'custom' used when do break in counting. "
+        "Note that only support single-class MOT, and the video should be taken by a static camera."
+    )
+    parser.add_argument(
+        '--region_polygon',
+        nargs='+',
+        type=int,
+        default=[],
+        help="Clockwise point coords (x0,y0,x1,y1...) of polygon of area when "
+        "do_break_in_counting. Note that only support single-class MOT and "
+        "the video should be taken by a static camera.")
+    parser.add_argument(
+        "--secs_interval",
+        type=int,
+        default=2,
+        help="The seconds interval to count after tracking")
+    parser.add_argument(
+        "--draw_center_traj",
+        action='store_true',
+        help="Whether drawing the trajectory of center")
+
+    return parser
+
+
+def merge_cfg(args):
+    # load config
+    with open(args.config) as f:
+        pred_config = yaml.safe_load(f)
+
+    def merge(cfg, arg):
+        # update cfg from arg directly
+        merge_cfg = copy.deepcopy(cfg)
+        for k, v in cfg.items():
+            if k in arg:
+                merge_cfg[k] = arg[k]
+            else:
+                if isinstance(v, dict):
+                    merge_cfg[k] = merge(v, arg)
+
+        return merge_cfg
+
+    def merge_opt(cfg, arg):
+        merge_cfg = copy.deepcopy(cfg)
+        # merge opt
+        if 'opt' in arg.keys() and arg['opt']:
+            for name, value in arg['opt'].items(
+            ):  # example: {'MOT': {'batch_size': 3}}
+                if name not in merge_cfg.keys():
+                    print("No", name, "in config file!")
+                    continue
+                for sub_k, sub_v in value.items():
+                    if sub_k not in merge_cfg[name].keys():
+                        print("No", sub_k, "in config file of", name, "!")
+                        continue
+                    merge_cfg[name][sub_k] = sub_v
+
+        return merge_cfg
+
+    args_dict = vars(args)
+    pred_config = merge(pred_config, args_dict)
+    pred_config = merge_opt(pred_config, args_dict)
+
+    return pred_config
+
+
+def print_arguments(cfg):
+    print('-----------  Running Arguments -----------')
+    buffer = yaml.dump(cfg)
+    print(buffer)
+    print('------------------------------------------')
diff --git a/deploy/pipeline/config/examples/infer_cfg_calling.yml b/deploy/pipeline/config/examples/infer_cfg_calling.yml
new file mode 100644
index 0000000000000000000000000000000000000000..8d74712aa0b8c9f16d7b89aec5307d16253438c3
--- /dev/null
+++ b/deploy/pipeline/config/examples/infer_cfg_calling.yml
@@ -0,0 +1,17 @@
+crop_thresh: 0.5
+visual: True
+warmup_frame: 50
+
+MOT:
+  model_dir: https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip
+  tracker_config: deploy/pipeline/config/tracker_config.yml
+  batch_size: 1
+  enable: True
+
+ID_BASED_CLSACTION:
+  model_dir: https://bj.bcebos.com/v1/paddledet/models/pipeline/PPHGNet_tiny_calling_halfbody.zip
+  batch_size: 8
+  threshold: 0.8
+  display_frames: 80
+  skip_frame_num: 2
+  enable: True
diff --git a/deploy/pipeline/config/examples/infer_cfg_fall_down.yml b/deploy/pipeline/config/examples/infer_cfg_fall_down.yml
new file mode 100644
index 0000000000000000000000000000000000000000..5dc38bb23b161cb7e84e027a3a4dd381da3d246b
--- /dev/null
+++ b/deploy/pipeline/config/examples/infer_cfg_fall_down.yml
@@ -0,0 +1,22 @@
+crop_thresh: 0.5
+kpt_thresh: 0.2
+visual: True
+warmup_frame: 50
+
+MOT:
+  model_dir: https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip
+  tracker_config: deploy/pipeline/config/tracker_config.yml
+  batch_size: 1
+  enable: True
+
+KPT:
+  model_dir: https://bj.bcebos.com/v1/paddledet/models/pipeline/dark_hrnet_w32_256x192.zip
+  batch_size: 8
+
+SKELETON_ACTION:
+  model_dir: https://bj.bcebos.com/v1/paddledet/models/pipeline/STGCN.zip
+  batch_size: 1
+  max_frames: 50
+  display_frames: 80
+  coord_size: [384, 512]
+  enable: True
diff --git a/deploy/pipeline/config/examples/infer_cfg_fight_recognition.yml b/deploy/pipeline/config/examples/infer_cfg_fight_recognition.yml
new file mode 100644
index 0000000000000000000000000000000000000000..76826ebaa45c0345e94d5ab8218293844cc96697
--- /dev/null
+++ b/deploy/pipeline/config/examples/infer_cfg_fight_recognition.yml
@@ -0,0 +1,11 @@
+visual: True
+warmup_frame: 50
+
+VIDEO_ACTION:
+  model_dir: https://videotag.bj.bcebos.com/PaddleVideo-release2.3/ppTSM_fight.zip
+  batch_size: 1
+  frame_len: 8
+  sample_freq: 7
+  short_size: 340
+  target_size: 320
+  enable: True
diff --git a/deploy/pipeline/config/examples/infer_cfg_human_attr.yml b/deploy/pipeline/config/examples/infer_cfg_human_attr.yml
new file mode 100644
index 0000000000000000000000000000000000000000..b4de76b3be2b4113c327c88ced7838224ced125b
--- /dev/null
+++ b/deploy/pipeline/config/examples/infer_cfg_human_attr.yml
@@ -0,0 +1,15 @@
+crop_thresh: 0.5
+attr_thresh: 0.5
+visual: True
+warmup_frame: 50
+
+MOT:
+  model_dir: https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip
+  tracker_config: deploy/pipeline/config/tracker_config.yml
+  batch_size: 1
+  enable: True
+
+ATTR:
+  model_dir:  https://bj.bcebos.com/v1/paddledet/models/pipeline/PPLCNet_x1_0_person_attribute_945_infer.zip
+  batch_size: 8
+  enable: True
diff --git a/deploy/pipeline/config/examples/infer_cfg_human_mot.yml b/deploy/pipeline/config/examples/infer_cfg_human_mot.yml
new file mode 100644
index 0000000000000000000000000000000000000000..7b9e739d4aa9139055c732728370fc414f31cfee
--- /dev/null
+++ b/deploy/pipeline/config/examples/infer_cfg_human_mot.yml
@@ -0,0 +1,9 @@
+crop_thresh: 0.5
+visual: True
+warmup_frame: 50
+
+MOT:
+  model_dir: https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip
+  tracker_config: deploy/pipeline/config/tracker_config.yml
+  batch_size: 1
+  enable: True
diff --git a/deploy/pipeline/config/examples/infer_cfg_reid.yml b/deploy/pipeline/config/examples/infer_cfg_reid.yml
new file mode 100644
index 0000000000000000000000000000000000000000..42c7f6f20d7c194aa03b8d54df81958211b72452
--- /dev/null
+++ b/deploy/pipeline/config/examples/infer_cfg_reid.yml
@@ -0,0 +1,14 @@
+crop_thresh: 0.5
+visual: True
+warmup_frame: 50
+
+MOT:
+  model_dir: https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip
+  tracker_config: deploy/pipeline/config/tracker_config.yml
+  batch_size: 1
+  enable: True
+
+REID:
+  model_dir:  https://bj.bcebos.com/v1/paddledet/models/pipeline/reid_model.zip
+  batch_size: 16
+  enable: True
diff --git a/deploy/pipeline/config/examples/infer_cfg_smoking.yml b/deploy/pipeline/config/examples/infer_cfg_smoking.yml
new file mode 100644
index 0000000000000000000000000000000000000000..41a1475303ee25fe6f35c58d39891a868d9cecab
--- /dev/null
+++ b/deploy/pipeline/config/examples/infer_cfg_smoking.yml
@@ -0,0 +1,17 @@
+crop_thresh: 0.5
+visual: True
+warmup_frame: 50
+
+MOT:
+  model_dir: https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip
+  tracker_config: deploy/pipeline/config/tracker_config.yml
+  batch_size: 1
+  enable: True
+
+ID_BASED_DETACTION:
+  model_dir:  https://bj.bcebos.com/v1/paddledet/models/pipeline/ppyoloe_crn_s_80e_smoking_visdrone.zip
+  batch_size: 8
+  threshold: 0.6
+  display_frames: 80
+  skip_frame_num: 2
+  enable: True
diff --git a/deploy/pipeline/config/infer_cfg_pphuman.yml b/deploy/pipeline/config/infer_cfg_pphuman.yml
index 80e8a5e0a3950593ed3c2e8548b45aa9e729a411..a75c3222946691e50c8cba086e013feaaf718539 100644
--- a/deploy/pipeline/config/infer_cfg_pphuman.yml
+++ b/deploy/pipeline/config/infer_cfg_pphuman.yml
@@ -12,7 +12,6 @@ MOT:
   model_dir: https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip
   tracker_config: deploy/pipeline/config/tracker_config.yml
   batch_size: 1
-  basemode: "idbased"
   enable: False
 
 KPT:
@@ -22,7 +21,6 @@ KPT:
 ATTR:
   model_dir:  https://bj.bcebos.com/v1/paddledet/models/pipeline/PPLCNet_x1_0_person_attribute_945_infer.zip
   batch_size: 8
-  basemode: "idbased"
   enable: False
 
 VIDEO_ACTION:
@@ -32,7 +30,6 @@ VIDEO_ACTION:
   sample_freq: 7
   short_size: 340
   target_size: 320
-  basemode: "videobased"
   enable: False
 
 SKELETON_ACTION:
@@ -41,13 +38,11 @@ SKELETON_ACTION:
   max_frames: 50
   display_frames: 80
   coord_size: [384, 512]
-  basemode: "skeletonbased"
   enable: False
 
 ID_BASED_DETACTION:
   model_dir:  https://bj.bcebos.com/v1/paddledet/models/pipeline/ppyoloe_crn_s_80e_smoking_visdrone.zip
   batch_size: 8
-  basemode: "idbased"
   threshold: 0.6
   display_frames: 80
   skip_frame_num: 2
@@ -56,7 +51,6 @@ ID_BASED_DETACTION:
 ID_BASED_CLSACTION:
   model_dir: https://bj.bcebos.com/v1/paddledet/models/pipeline/PPHGNet_tiny_calling_halfbody.zip
   batch_size: 8
-  basemode: "idbased"
   threshold: 0.8
   display_frames: 80
   skip_frame_num: 2
@@ -65,5 +59,4 @@ ID_BASED_CLSACTION:
 REID:
   model_dir:  https://bj.bcebos.com/v1/paddledet/models/pipeline/reid_model.zip
   batch_size: 16
-  basemode: "idbased"
   enable: False
diff --git a/deploy/pipeline/config/infer_cfg_ppvehicle.yml b/deploy/pipeline/config/infer_cfg_ppvehicle.yml
index 170266510518aca845ac3012e56c6be81b21772d..87d84dee9a16908bfbec258a0f0531ac6a4f692c 100644
--- a/deploy/pipeline/config/infer_cfg_ppvehicle.yml
+++ b/deploy/pipeline/config/infer_cfg_ppvehicle.yml
@@ -10,7 +10,6 @@ MOT:
   model_dir: output_inference/mot_ppyoloe_l_36e_ppvehicle/
   tracker_config: deploy/pipeline/config/tracker_config.yml
   batch_size: 1
-  basemode: "idbased"
   enable: False
 
 VEHICLE_PLATE:
@@ -21,13 +20,11 @@ VEHICLE_PLATE:
   rec_image_shape: [3, 48, 320]
   rec_batch_num: 6
   word_dict_path: deploy/pipeline/ppvehicle/rec_word_dict.txt
-  basemode: "idbased"
   enable: False
 
 VEHICLE_ATTR:
   model_dir: output_inference/vehicle_attribute_infer/
   batch_size: 8
-  basemode: "idbased"
   color_threshold: 0.5
   type_threshold: 0.5
   enable: False
@@ -35,5 +32,4 @@ VEHICLE_ATTR:
 REID:
   model_dir: output_inference/vehicle_reid_model/
   batch_size: 16
-  basemode: "idbased"
   enable: False
diff --git a/deploy/pipeline/docs/tutorials/PPHuman_QUICK_STARTED.md b/deploy/pipeline/docs/tutorials/PPHuman_QUICK_STARTED.md
index 0e1ddb92c7b9c733b6f7f61679cee35b9edf3450..fad7845e469ecadc6cfd719a6d63bc1344fe8a81 100644
--- a/deploy/pipeline/docs/tutorials/PPHuman_QUICK_STARTED.md
+++ b/deploy/pipeline/docs/tutorials/PPHuman_QUICK_STARTED.md
@@ -69,7 +69,7 @@ PP-Human提供了目标检测、属性识别、行为识别、ReID预训练模
 
 ## 配置文件说明
 
-PP-Human相关配置位于```deploy/pipeline/config/infer_cfg_pphuman.yml```中，存放模型路径，完成不同功能需要设置不同的任务类型
+PP-Human相关配置位于```deploy/pipeline/config/infer_cfg_pphuman.yml```中，存放模型路径，该配置文件中包含了目前PP-Human支持的所有功能。如果想要查看某个单一功能的配置，请参见```deploy/pipeline/config/examples/```中相关配置。此外，配置文件中的内容可以通过```-o```命令行参数修改，如修改属性的模型目录，则可通过```-o ATTR.model_dir="DIR_PATH"```进行设置。
 
 功能及任务类型对应表单如下：
 
@@ -90,20 +90,17 @@ MOT:
   model_dir: output_inference/mot_ppyoloe_l_36e_pipeline/
   tracker_config: deploy/pipeline/config/tracker_config.yml
   batch_size: 1
-  basemode: "idbased"
   enable: True
 
 ATTR:
   model_dir: output_inference/strongbaseline_r50_30e_pa100k/
   batch_size: 8
-  basemode: "idbased"
   enable: True
 ```
 
 **注意：**
 
-- 如果用户需要实现不同任务，可以在配置文件对应enable选项设置为True, 其basemode类型会在代码中开启依赖的基础能力模型，比如跟踪模型。
-- 如果用户仅需要修改模型文件路径，可以在命令行中加入 `--model_dir det=ppyoloe/` 即可，也可以手动修改配置文件中的相应模型路径，详细说明参考下方参数说明文档。
+- 如果用户需要实现不同任务，可以在配置文件对应enable选项设置为True。
 
 
 ## 预测部署
@@ -117,7 +114,7 @@ python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pph
 
 # 行人跟踪，指定配置文件路径，模型路径和测试视频，在配置文件```deploy/pipeline/config/infer_cfg_pphuman.yml```中的MOT部分enable设置为```True```
 # 命令行中指定的模型路径优先级高于配置文件
-python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pphuman.yml --video_file=test_video.mp4 --device=gpu --model_dir det=ppyoloe/ [--run_mode trt_fp16]
+python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pphuman.yml --video_file=test_video.mp4 --device=gpu [--run_mode trt_fp16]
 
 # 行人属性识别，指定配置文件路径和测试视频，在配置文件```deploy/pipeline/config/infer_cfg_pphuman.yml```中的ATTR部分enable设置为```True```
 python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pphuman.yml --video_file=test_video.mp4 --device=gpu [--run_mode trt_fp16]
@@ -127,6 +124,10 @@ python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pph
 
 # 行人跨境跟踪，指定配置文件路径和测试视频列表文件夹，在配置文件```deploy/pipeline/config/infer_cfg_pphuman.yml```中的REID部分enable设置为```True```
 python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pphuman.yml --video_dir=mtmct_dir/ --device=gpu [--run_mode trt_fp16]
+
+# 行人跨境跟踪，指定配置文件路径和测试视频列表文件夹，直接使用```deploy/pipeline/config/examples/infer_cfg_reid.yml```配置文件，并利用```-o```命令修改跟踪模型路径
+python deploy/pipeline/pipeline.py --config deploy/pipeline/config/examples/infer_cfg_reid.yml --video_dir=mtmct_dir/ -o MOT.model_dir="mot_model_dir" --device=gpu [--run_mode trt_fp16]
+
 ```
 
 对rtsp流的支持，video_file后面的视频地址更换为rtsp流地址，示例如下：
@@ -140,7 +141,7 @@ python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pph
 | 参数 | 是否必须|含义 |
 |-------|-------|----------|
 | --config | Yes | 配置文件路径 |
-| --model_dir | Option | PP-Human中各任务模型路径，优先级高于配置文件, 例如`--model_dir det=better_det/ attr=better_attr/`|
+| -o | Option | 覆盖配置文件中对应的配置  |
 | --image_file | Option | 需要预测的图片 |
 | --image_dir  | Option |  要预测的图片文件夹路径   |
 | --video_file | Option | 需要预测的视频，或者rtsp流地址 |
diff --git a/deploy/pipeline/docs/tutorials/PPVehicle_QUICK_STARTED.md b/deploy/pipeline/docs/tutorials/PPVehicle_QUICK_STARTED.md
index aa228337ac7614dfc263c3df484e770caee28043..6a2f3d64a04f94c38a4b72322bc7255838ee78c0 100644
--- a/deploy/pipeline/docs/tutorials/PPVehicle_QUICK_STARTED.md
+++ b/deploy/pipeline/docs/tutorials/PPVehicle_QUICK_STARTED.md
@@ -62,7 +62,7 @@ PP-Vehicle相关配置位于```deploy/pipeline/config/infer_cfg_ppvehicle.yml```
 
 **注意：**
 
-- 如果用户需要实现不同任务，可以在配置文件对应enable选项设置为True, 其basemode类型会在代码中开启依赖的基础能力模型，比如跟踪模型。
+- 如果用户需要实现不同任务，可以在配置文件对应enable选项设置为True。
 - 如果用户仅需要修改模型文件路径，可以在命令行中加入 `--model_dir det=ppyoloe/` 即可，也可以手动修改配置文件中的相应模型路径，详细说明参考下方参数说明文档。
 
 
diff --git a/deploy/pipeline/docs/tutorials/pphuman_action.md b/deploy/pipeline/docs/tutorials/pphuman_action.md
index 53b9f5f388622b66480020baff52bdadc22a4149..cf0c5af501b465de810d37813032bcb316e6fde5 100644
--- a/deploy/pipeline/docs/tutorials/pphuman_action.md
+++ b/deploy/pipeline/docs/tutorials/pphuman_action.md
@@ -46,7 +46,6 @@ SKELETON_ACTION: # 基于骨骼点的行为识别模型配置
   max_frames: 50 # 动作片段对应的帧数。在行人ID对应时序骨骼点结果时达到该帧数后，会通过行为识别模型判断该段序列的动作类型。与训练设置一致时效果最佳。
   display_frames: 80 # 显示帧数。当预测结果为摔倒时，在对应人物ID中显示状态的持续时间。
   coord_size: [384, 512] # 坐标统一缩放到的尺度大小。与训练设置一致时效果最佳。
-  basemode: "skeletonbased" # 模型基于的路线分支，是否需要skeleton作为输入
   enable: False # 是否开启该功能
 ```
 
@@ -112,7 +111,6 @@ python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pph
 ID_BASED_CLSACTION: # 基于分类的行为识别模型配置
   model_dir: output_inference/PPHGNet_tiny_calling_halfbody # 模型所在路径
   batch_size: 8 # 预测批大小
-  basemode: "idbased" # 模型基于的路线分支，是否基于跟踪获得的ID信息
   threshold: 0.45 #识别为对应行为的阈值
   display_frames: 80 # 显示帧数。当识别到对应动作时，在对应人物ID中显示状态的持续时间。
   enable: False # 是否开启该功能
@@ -168,7 +166,6 @@ python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pph
 ID_BASED_DETACTION: # 基于检测的行为识别模型配置
   model_dir: output_inference/ppyoloe_crn_s_80e_smoking_visdrone # 模型所在路径
   batch_size: 8  # 预测批大小
-  basemode: "idbased" # 模型基于的路线分支，是否基于跟踪获得的ID信息
   threshold: 0.4  # 识别为对应行为的阈值
   display_frames: 80 # 显示帧数。当识别到对应动作时，在对应人物ID中显示状态的持续时间。
   enable: False # 是否开启该功能
@@ -242,7 +239,6 @@ VIDEO_ACTION:  # 基于视频分类的行为识别模型配置
   sample_freq: 7 # 抽样频率，即间隔多少帧抽样一帧
   short_size: 340 # 视频帧尺度变换最小边的长度
   target_size: 320 # 目标视频帧的大小
-  basemode: "videobased"  # 模型基于的路线分支，是否直接使用视频进行输入
   enable: False # 是否开启该功能
 ```
 
diff --git a/deploy/pipeline/docs/tutorials/pphuman_action_en.md b/deploy/pipeline/docs/tutorials/pphuman_action_en.md
index 159e474897e023f90ae8087155030439ea36a442..943a5c5678997816f66941e785f4ac95256acf83 100644
--- a/deploy/pipeline/docs/tutorials/pphuman_action_en.md
+++ b/deploy/pipeline/docs/tutorials/pphuman_action_en.md
@@ -53,7 +53,6 @@ SKELETON_ACTION: # Config for skeleton-based action recognition model
     max_frames: 50 # The number of frames of action segments. When frames of time-ordered skeleton keypoints of each pedestrian ID achieve the max value,the action type will be judged by the action recognition model. If the setting is the same as the training, there will be an ideal inference result.
     display_frames: 80 # The number of display frames. When the inferred action type is falling down, the time length of the act will be displayed in the ID.
     coord_size: [384, 512] # The unified size of the coordinate, which is the best when it is the same as the training setting.
-    basemode: "skeletonbased" # The models which is based on，whether we need the skeleton model.
     enable: False # Whether to enable this function
 ```
 
@@ -115,7 +114,6 @@ Parameters related to action recognition in the [config file](../../config/infer
 ID_BASED_CLSACTION: # config for classfication-based action recognition model
     model_dir: output_inference/PPHGNet_tiny_calling_halfbody  # Path of the model
     batch_size: 8 # The size of the inference batch
-    basemode: "idbased" # the models which is based on, whether the id of each object obtained by tracking is needed.
     threshold: 0.45 # Threshold for corresponding behavior
     display_frames: 80 # The number of display frames. When the corresponding action is detected, the time length of the act will be displayed in the ID.
     enable: False # Whether to enable this function
@@ -162,7 +160,6 @@ Parameters related to action recognition in the [config file](../../config/infer
 ID_BASED_DETACTION: # Config for detection-based action recognition model
     model_dir: output_inference/ppyoloe_crn_s_80e_smoking_visdrone # Path of the model
     batch_size: 8  # The size of the inference batch
-    basemode: "idbased" # The models which is based on, whether the id of each object obtained by tracking is needed.
     threshold: 0.4  # Threshold for corresponding behavior.
     display_frames: 80 # The number of display frames. When the corresponding action is detected, the time length of the act will be displayed in the ID.
     enable: False # Whether to enable this function
@@ -220,7 +217,6 @@ VIDEO_ACTION:  # Config for detection-based action recognition model
     sample_freq: 7 # Sampling frequency. It means how many frames to sample one frame.
     short_size: 340 # The shortest length for video frame scaling transforms.
     target_size: 320 # Target size for input video
-    basemode: "videobased"  # The models which is based on, whether to use video as model input.
     enable: False # Whether to enable this function
 ```
 
diff --git a/deploy/pipeline/docs/tutorials/pphuman_attribute.md b/deploy/pipeline/docs/tutorials/pphuman_attribute.md
index 9055225fedf2b2dda13833289dfeb2ee54773cc2..16109606c0cbfbac9794512648bf34a7150d0cb7 100644
--- a/deploy/pipeline/docs/tutorials/pphuman_attribute.md
+++ b/deploy/pipeline/docs/tutorials/pphuman_attribute.md
@@ -27,7 +27,6 @@
 ATTR:                                                                     #模块名称
   model_dir: output_inference/PPLCNet_x1_0_person_attribute_945_infer/    #模型路径
   batch_size: 8                                                           #推理最大batchsize
-  basemode: "idbased"                                                     #流程类型，'idbased'表示基于跟踪模型
   enable: False                                                           #功能是否开启
 ```
 
diff --git a/deploy/pipeline/docs/tutorials/pphuman_attribute_en.md b/deploy/pipeline/docs/tutorials/pphuman_attribute_en.md
index 2e055971a42522983dcf6fdb94d88d2d3915cd98..70c55de0edea1a2c3b0574efd7835c10d94f74e6 100644
--- a/deploy/pipeline/docs/tutorials/pphuman_attribute_en.md
+++ b/deploy/pipeline/docs/tutorials/pphuman_attribute_en.md
@@ -24,7 +24,6 @@ The meaning of configs of `infer_cfg_pphuman.yml`：
 ATTR:                                                                     #module name
   model_dir: output_inference/PPLCNet_x1_0_person_attribute_945_infer/    #model path
   batch_size: 8                                                           #maxmum batchsize when inference
-  basemode: "idbased"                                                     #the routing type of pipeline，'idbased' means this model is based on tracking.
   enable: False                                                           #whether to enable this model
 ```
 
diff --git a/deploy/pipeline/pipe_utils.py b/deploy/pipeline/pipe_utils.py
index 4d9887106b0ed162433212317d9b160ea360529e..d4a6307525bb903cc7f09331dbbdbaba5c707fd6 100644
--- a/deploy/pipeline/pipe_utils.py
+++ b/deploy/pipeline/pipe_utils.py
@@ -15,7 +15,6 @@
 import time
 import os
 import ast
-import argparse
 import glob
 import yaml
 import copy
@@ -24,120 +23,6 @@ import numpy as np
 from python.keypoint_preprocess import EvalAffine, TopDownEvalAffine, expand_crop
 
 
-def argsparser():
-    parser = argparse.ArgumentParser(description=__doc__)
-    parser.add_argument(
-        "--config",
-        type=str,
-        default=None,
-        help=("Path of configure"),
-        required=True)
-    parser.add_argument(
-        "--image_file", type=str, default=None, help="Path of image file.")
-    parser.add_argument(
-        "--image_dir",
-        type=str,
-        default=None,
-        help="Dir of image file, `image_file` has a higher priority.")
-    parser.add_argument(
-        "--video_file",
-        type=str,
-        default=None,
-        help="Path of video file, `video_file` or `camera_id` has a highest priority."
-    )
-    parser.add_argument(
-        "--video_dir",
-        type=str,
-        default=None,
-        help="Dir of video file, `video_file` has a higher priority.")
-    parser.add_argument(
-        "--model_dir", nargs='*', help="set model dir in pipeline")
-    parser.add_argument(
-        "--camera_id",
-        type=int,
-        default=-1,
-        help="device id of camera to predict.")
-    parser.add_argument(
-        "--output_dir",
-        type=str,
-        default="output",
-        help="Directory of output visualization files.")
-    parser.add_argument(
-        "--run_mode",
-        type=str,
-        default='paddle',
-        help="mode of running(paddle/trt_fp32/trt_fp16/trt_int8)")
-    parser.add_argument(
-        "--device",
-        type=str,
-        default='cpu',
-        help="Choose the device you want to run, it can be: CPU/GPU/XPU, default is CPU."
-    )
-    parser.add_argument(
-        "--enable_mkldnn",
-        type=ast.literal_eval,
-        default=False,
-        help="Whether use mkldnn with CPU.")
-    parser.add_argument(
-        "--cpu_threads", type=int, default=1, help="Num of threads with CPU.")
-    parser.add_argument(
-        "--trt_min_shape", type=int, default=1, help="min_shape for TensorRT.")
-    parser.add_argument(
-        "--trt_max_shape",
-        type=int,
-        default=1280,
-        help="max_shape for TensorRT.")
-    parser.add_argument(
-        "--trt_opt_shape",
-        type=int,
-        default=640,
-        help="opt_shape for TensorRT.")
-    parser.add_argument(
-        "--trt_calib_mode",
-        type=bool,
-        default=False,
-        help="If the model is produced by TRT offline quantitative "
-        "calibration, trt_calib_mode need to set True.")
-    parser.add_argument(
-        "--do_entrance_counting",
-        action='store_true',
-        help="Whether counting the numbers of identifiers entering "
-        "or getting out from the entrance. Note that only support single-class MOT."
-    )
-    parser.add_argument(
-        "--do_break_in_counting",
-        action='store_true',
-        help="Whether counting the numbers of identifiers break in "
-        "the area. Note that only support single-class MOT and "
-        "the video should be taken by a static camera.")
-    parser.add_argument(
-        "--region_type",
-        type=str,
-        default='horizontal',
-        help="Area type for entrance counting or break in counting, 'horizontal' and "
-        "'vertical' used when do entrance counting. 'custom' used when do break in counting. "
-        "Note that only support single-class MOT, and the video should be taken by a static camera."
-    )
-    parser.add_argument(
-        '--region_polygon',
-        nargs='+',
-        type=int,
-        default=[],
-        help="Clockwise point coords (x0,y0,x1,y1...) of polygon of area when "
-        "do_break_in_counting. Note that only support single-class MOT and "
-        "the video should be taken by a static camera.")
-    parser.add_argument(
-        "--secs_interval",
-        type=int,
-        default=2,
-        help="The seconds interval to count after tracking")
-    parser.add_argument(
-        "--draw_center_traj",
-        action='store_true',
-        help="Whether drawing the trajectory of center")
-    return parser
-
-
 class Times(object):
     def __init__(self):
         self.time = 0.
@@ -233,49 +118,6 @@ class PipeTimer(Times):
         return dic
 
 
-def merge_model_dir(args, model_dir):
-    # set --model_dir DET=ppyoloe/ to overwrite the model_dir in config file
-    task_set = ['DET', 'ATTR', 'MOT', 'KPT', 'SKELETON_ACTION', 'REID']
-    if not model_dir:
-        return args
-    for md in model_dir:
-        md = md.strip()
-        k, v = md.split('=', 1)
-        k_upper = k.upper()
-        assert k_upper in task_set, 'Illegal type of task, expect task are: {}, but received {}'.format(
-            task_set, k)
-        args[k_upper].update({'model_dir': v})
-    return args
-
-
-def merge_cfg(args):
-    with open(args.config) as f:
-        pred_config = yaml.safe_load(f)
-
-    def merge(cfg, arg):
-        merge_cfg = copy.deepcopy(cfg)
-        for k, v in cfg.items():
-            if k in arg:
-                merge_cfg[k] = arg[k]
-            else:
-                if isinstance(v, dict):
-                    merge_cfg[k] = merge(v, arg)
-        return merge_cfg
-
-    args_dict = vars(args)
-    model_dir = args_dict.pop('model_dir')
-    pred_config = merge_model_dir(pred_config, model_dir)
-    pred_config = merge(pred_config, args_dict)
-    return pred_config
-
-
-def print_arguments(cfg):
-    print('-----------  Running Arguments -----------')
-    buffer = yaml.dump(cfg)
-    print(buffer)
-    print('------------------------------------------')
-
-
 def get_test_images(infer_dir, infer_img):
     """
     Get image path list in TEST mode
diff --git a/deploy/pipeline/pipeline.py b/deploy/pipeline/pipeline.py
index 7683da175b86dfbe429063b28c2438b7aa0e7ad2..3ea65c11391e5ba65272c131c2ffd9353c1860a3 100644
--- a/deploy/pipeline/pipeline.py
+++ b/deploy/pipeline/pipeline.py
@@ -28,7 +28,8 @@ from datacollector import DataCollector, Result
 parent_path = os.path.abspath(os.path.join(__file__, *(['..'] * 2)))
 sys.path.insert(0, parent_path)
 
-from pipe_utils import argsparser, print_arguments, merge_cfg, PipeTimer
+from cfg_utils import argsparser, print_arguments, merge_cfg
+from pipe_utils import PipeTimer
 from pipe_utils import get_test_images, crop_image_with_det, crop_image_with_mot, parse_mot_res, parse_mot_keypoint
 
 from python.infer import Detector, DetectorPicoDet
@@ -331,6 +332,18 @@ class PipePredictor(object):
             "skeletonbased": False
         }
 
+        self.basemode = {
+            "MOT": "idbased",
+            "ATTR": "idbased",
+            "VIDEO_ACTION": "videobased",
+            "SKELETON_ACTION": "skeletonbased",
+            "ID_BASED_DETACTION": "idbased",
+            "ID_BASED_CLSACTION": "idbased",
+            "REID": "idbased",
+            "VEHICLE_PLATE": "idbased",
+            "VEHICLE_ATTR": "idbased",
+        }
+
         self.is_video = is_video
         self.multi_camera = multi_camera
         self.cfg = cfg
@@ -363,7 +376,7 @@ class PipePredictor(object):
                 attr_cfg = self.cfg['ATTR']
                 model_dir = model_dir_dict['ATTR']
                 batch_size = attr_cfg['batch_size']
-                basemode = attr_cfg['basemode']
+                basemode = self.basemode['ATTR']
                 self.modebase[basemode] = True
                 self.attr_predictor = AttrDetector(
                     model_dir, device, run_mode, batch_size, trt_min_shape,
@@ -376,7 +389,7 @@ class PipePredictor(object):
                 batch_size = vehicleattr_cfg['batch_size']
                 color_threshold = vehicleattr_cfg['color_threshold']
                 type_threshold = vehicleattr_cfg['type_threshold']
-                basemode = vehicleattr_cfg['basemode']
+                basemode = self.basemode['VEHICLE_ATTR']
                 self.modebase[basemode] = True
                 self.vehicle_attr_predictor = VehicleAttr(
                     model_dir, device, run_mode, batch_size, trt_min_shape,
@@ -388,7 +401,7 @@ class PipePredictor(object):
                 attr_cfg = self.cfg['ATTR']
                 model_dir = model_dir_dict['ATTR']
                 batch_size = attr_cfg['batch_size']
-                basemode = attr_cfg['basemode']
+                basemode = self.basemode['ATTR']
                 self.modebase[basemode] = True
                 self.attr_predictor = AttrDetector(
                     model_dir, device, run_mode, batch_size, trt_min_shape,
@@ -398,7 +411,7 @@ class PipePredictor(object):
                 idbased_detaction_cfg = self.cfg['ID_BASED_DETACTION']
                 model_dir = model_dir_dict['ID_BASED_DETACTION']
                 batch_size = idbased_detaction_cfg['batch_size']
-                basemode = idbased_detaction_cfg['basemode']
+                basemode = self.basemode['ID_BASED_DETACTION']
                 threshold = idbased_detaction_cfg['threshold']
                 display_frames = idbased_detaction_cfg['display_frames']
                 skip_frame_num = idbased_detaction_cfg['skip_frame_num']
@@ -424,7 +437,7 @@ class PipePredictor(object):
                 idbased_clsaction_cfg = self.cfg['ID_BASED_CLSACTION']
                 model_dir = model_dir_dict['ID_BASED_CLSACTION']
                 batch_size = idbased_clsaction_cfg['batch_size']
-                basemode = idbased_clsaction_cfg['basemode']
+                basemode = self.basemode['ID_BASED_CLSACTION']
                 threshold = idbased_clsaction_cfg['threshold']
                 self.modebase[basemode] = True
                 display_frames = idbased_clsaction_cfg['display_frames']
@@ -453,7 +466,7 @@ class PipePredictor(object):
                 skeleton_action_frames = skeleton_action_cfg['max_frames']
                 display_frames = skeleton_action_cfg['display_frames']
                 self.coord_size = skeleton_action_cfg['coord_size']
-                basemode = skeleton_action_cfg['basemode']
+                basemode = self.basemode['SKELETON_ACTION']
                 self.modebase[basemode] = True
 
                 self.skeleton_action_predictor = SkeletonActionRecognizer(
@@ -493,7 +506,7 @@ class PipePredictor(object):
                 vehicleplate_cfg = self.cfg['VEHICLE_PLATE']
                 self.vehicleplate_detector = PlateRecognizer(args,
                                                              vehicleplate_cfg)
-                basemode = vehicleplate_cfg['basemode']
+                basemode = self.basemode['VEHICLE_PLATE']
                 self.modebase[basemode] = True
 
             if self.with_vehicle_attr:
@@ -502,7 +515,7 @@ class PipePredictor(object):
                 batch_size = vehicleattr_cfg['batch_size']
                 color_threshold = vehicleattr_cfg['color_threshold']
                 type_threshold = vehicleattr_cfg['type_threshold']
-                basemode = vehicleattr_cfg['basemode']
+                basemode = self.basemode['VEHICLE_ATTR']
                 self.modebase[basemode] = True
                 self.vehicle_attr_predictor = VehicleAttr(
                     model_dir, device, run_mode, batch_size, trt_min_shape,
@@ -513,7 +526,7 @@ class PipePredictor(object):
                 reid_cfg = self.cfg['REID']
                 model_dir = model_dir_dict['REID']
                 batch_size = reid_cfg['batch_size']
-                basemode = reid_cfg['basemode']
+                basemode = self.basemode['REID']
                 self.modebase[basemode] = True
                 self.reid_predictor = ReID(
                     model_dir, device, run_mode, batch_size, trt_min_shape,
@@ -526,7 +539,7 @@ class PipePredictor(object):
                 model_dir = model_dir_dict['MOT']
                 tracker_config = mot_cfg['tracker_config']
                 batch_size = mot_cfg['batch_size']
-                basemode = mot_cfg['basemode']
+                basemode = self.basemode['MOT']
                 self.modebase[basemode] = True
                 self.mot_predictor = SDE_Detector(
                     model_dir,
@@ -550,7 +563,7 @@ class PipePredictor(object):
             if self.with_video_action:
                 video_action_cfg = self.cfg['VIDEO_ACTION']
 
-                basemode = video_action_cfg['basemode']
+                basemode = self.basemode['VIDEO_ACTION']
                 self.modebase[basemode] = True
 
                 video_action_model_dir = model_dir_dict['VIDEO_ACTION']
@@ -1087,7 +1100,7 @@ class PipePredictor(object):
 
 
 def main():
-    cfg = merge_cfg(FLAGS)
+    cfg = merge_cfg(FLAGS)  # use command params to update config
     print_arguments(cfg)
 
     pipeline = Pipeline(FLAGS, cfg)
@@ -1096,6 +1109,8 @@ def main():
 
 if __name__ == '__main__':
     paddle.enable_static()
+
+    # parse params from command
     parser = argsparser()
     FLAGS = parser.parse_args()
     FLAGS.device = FLAGS.device.upper()
diff --git a/deploy/pipeline/ppvehicle/vehicle_plate.py b/deploy/pipeline/ppvehicle/vehicle_plate.py
index 6a41be6f1ecd92da842cc7006bedad3e372ae92c..cfb831c55cc0a76e6bc26328636e978040054a80 100644
--- a/deploy/pipeline/ppvehicle/vehicle_plate.py
+++ b/deploy/pipeline/ppvehicle/vehicle_plate.py
@@ -31,7 +31,7 @@ from python.infer import get_test_images
 from python.preprocess import preprocess, NormalizeImage, Permute, Resize_Mult32
 from pipeline.ppvehicle.vehicle_plateutils import create_predictor, get_infer_gpuid, get_rotate_crop_image, draw_boxes
 from pipeline.ppvehicle.vehicleplate_postprocess import build_post_process
-from pipeline.pipe_utils import merge_cfg, print_arguments, argsparser
+from pipeline.cfg_utils import merge_cfg, print_arguments, argsparser
 
 
 class PlateDetector(object):