diff --git a/CMakeLists.txt b/CMakeLists.txt
index 549d7b708..44ff6c786 100755
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -240,12 +240,12 @@ if(ENABLE_PADDLE_BACKEND)
   add_definitions(-DENABLE_PADDLE_BACKEND)
   list(APPEND ALL_DEPLOY_SRCS ${DEPLOY_PADDLE_SRCS})
   include(${PROJECT_SOURCE_DIR}/cmake/paddle_inference.cmake)
-  if(NOT APPLE)
-    list(APPEND DEPEND_LIBS external_paddle_inference external_dnnl external_omp)
-  else()
-    # no third parties libs(mkldnn and omp) need to
-    # link into paddle_inference on MacOS OSX.
-    list(APPEND DEPEND_LIBS external_paddle_inference)
+  list(APPEND DEPEND_LIBS external_paddle_inference)
+  if(external_dnnl_FOUND)
+    list(APPEND DEPEND_LIBS external_dnnl external_omp)
+  endif()
+  if(external_ort_FOUND)
+    list(APPEND DEPEND_LIBS external_p2o external_ort)
   endif()
 endif()
 
@@ -387,9 +387,9 @@ if(ENABLE_TRT_BACKEND)
     find_package(Python COMPONENTS Interpreter Development REQUIRED)
     message(STATUS "Copying ${TRT_DIRECTORY}/lib to ${CMAKE_CURRENT_BINARY_DIR}/third_libs/install/tensorrt/lib ...")
     execute_process(COMMAND ${Python_EXECUTABLE} ${PROJECT_SOURCE_DIR}/scripts/copy_directory.py ${TRT_DIRECTORY}/lib ${CMAKE_CURRENT_BINARY_DIR}/third_libs/install/tensorrt/lib)
-    file(GLOB_RECURSE TRT_STAIC_LIBS ${CMAKE_CURRENT_BINARY_DIR}/third_libs/install/tensorrt/lib/*.a)
+    file(GLOB_RECURSE TRT_STATIC_LIBS ${CMAKE_CURRENT_BINARY_DIR}/third_libs/install/tensorrt/lib/*.a)
     if(TRT_STATIC_LIBS)
-      file(REMOVE ${TRT_STAIC_LIBS})
+      file(REMOVE ${TRT_STATIC_LIBS})
     endif()
     if(UNIX AND (NOT APPLE) AND (NOT ANDROID))
       execute_process(COMMAND sh -c "ls *.so*" WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/third_libs/install/tensorrt/lib
diff --git a/FastDeploy.cmake.in b/FastDeploy.cmake.in
index 456a4d321..83114e901 100755
--- a/FastDeploy.cmake.in
+++ b/FastDeploy.cmake.in
@@ -74,10 +74,9 @@ if(ENABLE_PADDLE_BACKEND)
     set(DNNL_LIB "${CMAKE_CURRENT_LIST_DIR}/third_libs/install/paddle_inference/third_party/install/mkldnn/lib/libmkldnn.so.0")
     set(IOMP_LIB "${CMAKE_CURRENT_LIST_DIR}/third_libs/install/paddle_inference/third_party/install/mklml/lib/libiomp5.so")
   endif()
-  if(NOT APPLE)
-    list(APPEND FASTDEPLOY_LIBS ${PADDLE_LIB} ${DNNL_LIB} ${IOMP_LIB})
-  else()
-    list(APPEND FASTDEPLOY_LIBS ${PADDLE_LIB})
+  list(APPEND FASTDEPLOY_LIBS ${PADDLE_LIB})
+  if(EXISTS "${DNNL_LIB}")
+    list(APPEND FASTDEPLOY_LIBS ${DNNL_LIB} ${IOMP_LIB})
   endif()
 endif()
 
diff --git a/benchmark/benchmark_uie.py b/benchmark/benchmark_uie.py
new file mode 100644
index 000000000..44c562d7e
--- /dev/null
+++ b/benchmark/benchmark_uie.py
@@ -0,0 +1,321 @@
+import numpy as np
+import os
+import time
+import distutils.util
+import sys
+import json
+
+import fastdeploy as fd
+from fastdeploy.text import UIEModel, SchemaLanguage
+
+
+def parse_arguments():
+    import argparse
+    import ast
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--model_dir",
+        required=True,
+        help="The directory of model and tokenizer.")
+    parser.add_argument(
+        "--data_path", required=True, help="The path of uie data.")
+    parser.add_argument(
+        "--device",
+        type=str,
+        default='cpu',
+        choices=['gpu', 'cpu'],
+        help="Type of inference device, support 'cpu' or 'gpu'.")
+    parser.add_argument(
+        "--backend",
+        type=str,
+        default='paddle',
+        choices=['ort', 'paddle', 'trt', 'paddle_trt', 'ov'],
+        help="The inference runtime backend.")
+    parser.add_argument(
+        "--device_id", type=int, default=0, help="device(gpu) id")
+    parser.add_argument(
+        "--batch_size", type=int, default=1, help="The batch size of data.")
+    parser.add_argument(
+        "--max_length",
+        type=int,
+        default=128,
+        help="The max length of sequence.")
+    parser.add_argument(
+        "--cpu_num_threads",
+        type=int,
+        default=8,
+        help="The number of threads when inferring on cpu.")
+    parser.add_argument(
+        "--enable_trt_fp16",
+        type=distutils.util.strtobool,
+        default=False,
+        help="whether enable fp16 in trt backend")
+    parser.add_argument(
+        "--epoch", type=int, default=1, help="The epoch of test")
+    parser.add_argument(
+        "--enable_collect_memory_info",
+        type=ast.literal_eval,
+        default=False,
+        help="whether enable collect memory info")
+    return parser.parse_args()
+
+
+def build_option(args):
+    option = fd.RuntimeOption()
+    if args.device == 'cpu':
+        option.use_cpu()
+        option.set_cpu_thread_num(args.cpu_num_threads)
+    else:
+        option.use_gpu(args.device_id)
+    if args.backend == 'paddle':
+        option.use_paddle_backend()
+    elif args.backend == 'ort':
+        option.use_ort_backend()
+    elif args.backend == 'ov':
+        option.use_openvino_backend()
+    else:
+        option.use_trt_backend()
+        if args.backend == 'paddle_trt':
+            option.enable_paddle_to_trt()
+            option.enable_paddle_trt_collect_shape()
+        trt_file = os.path.join(args.model_dir, "infer.trt")
+        option.set_trt_input_shape(
+            'input_ids',
+            min_shape=[1, 1],
+            opt_shape=[args.batch_size, args.max_length // 2],
+            max_shape=[args.batch_size, args.max_length])
+        option.set_trt_input_shape(
+            'token_type_ids',
+            min_shape=[1, 1],
+            opt_shape=[args.batch_size, args.max_length // 2],
+            max_shape=[args.batch_size, args.max_length])
+        option.set_trt_input_shape(
+            'pos_ids',
+            min_shape=[1, 1],
+            opt_shape=[args.batch_size, args.max_length // 2],
+            max_shape=[args.batch_size, args.max_length])
+        option.set_trt_input_shape(
+            'att_mask',
+            min_shape=[1, 1],
+            opt_shape=[args.batch_size, args.max_length // 2],
+            max_shape=[args.batch_size, args.max_length])
+        if args.enable_trt_fp16:
+            option.enable_trt_fp16()
+            trt_file = trt_file + ".fp16"
+        option.set_trt_cache_file(trt_file)
+    return option
+
+
+class StatBase(object):
+    """StatBase"""
+    nvidia_smi_path = "nvidia-smi"
+    gpu_keys = ('index', 'uuid', 'name', 'timestamp', 'memory.total',
+                'memory.free', 'memory.used', 'utilization.gpu',
+                'utilization.memory')
+    nu_opt = ',nounits'
+    cpu_keys = ('cpu.util', 'memory.util', 'memory.used')
+
+
+class Monitor(StatBase):
+    """Monitor"""
+
+    def __init__(self, use_gpu=False, gpu_id=0, interval=0.1):
+        self.result = {}
+        self.gpu_id = gpu_id
+        self.use_gpu = use_gpu
+        self.interval = interval
+        self.cpu_stat_q = multiprocessing.Queue()
+
+    def start(self):
+        cmd = '%s --id=%s --query-gpu=%s --format=csv,noheader%s -lms 50' % (
+            StatBase.nvidia_smi_path, self.gpu_id, ','.join(StatBase.gpu_keys),
+            StatBase.nu_opt)
+        if self.use_gpu:
+            self.gpu_stat_worker = subprocess.Popen(
+                cmd,
+                stderr=subprocess.STDOUT,
+                stdout=subprocess.PIPE,
+                shell=True,
+                close_fds=True,
+                preexec_fn=os.setsid)
+        # cpu stat
+        pid = os.getpid()
+        self.cpu_stat_worker = multiprocessing.Process(
+            target=self.cpu_stat_func,
+            args=(self.cpu_stat_q, pid, self.interval))
+        self.cpu_stat_worker.start()
+
+    def stop(self):
+        try:
+            if self.use_gpu:
+                os.killpg(self.gpu_stat_worker.pid, signal.SIGUSR1)
+            # os.killpg(p.pid, signal.SIGTERM)
+            self.cpu_stat_worker.terminate()
+            self.cpu_stat_worker.join(timeout=0.01)
+        except Exception as e:
+            print(e)
+            return
+
+        # gpu
+        if self.use_gpu:
+            lines = self.gpu_stat_worker.stdout.readlines()
+            lines = [
+                line.strip().decode("utf-8") for line in lines
+                if line.strip() != ''
+            ]
+            gpu_info_list = [{
+                k: v
+                for k, v in zip(StatBase.gpu_keys, line.split(', '))
+            } for line in lines]
+            if len(gpu_info_list) == 0:
+                return
+            result = gpu_info_list[0]
+            for item in gpu_info_list:
+                for k in item.keys():
+                    if k not in ["name", "uuid", "timestamp"]:
+                        result[k] = max(int(result[k]), int(item[k]))
+                    else:
+                        result[k] = max(result[k], item[k])
+            self.result['gpu'] = result
+
+        # cpu
+        cpu_result = {}
+        if self.cpu_stat_q.qsize() > 0:
+            cpu_result = {
+                k: v
+                for k, v in zip(StatBase.cpu_keys, self.cpu_stat_q.get())
+            }
+        while not self.cpu_stat_q.empty():
+            item = {
+                k: v
+                for k, v in zip(StatBase.cpu_keys, self.cpu_stat_q.get())
+            }
+            for k in StatBase.cpu_keys:
+                cpu_result[k] = max(cpu_result[k], item[k])
+        cpu_result['name'] = cpuinfo.get_cpu_info()['brand_raw']
+        self.result['cpu'] = cpu_result
+
+    def output(self):
+        return self.result
+
+    def cpu_stat_func(self, q, pid, interval=0.0):
+        """cpu stat function"""
+        stat_info = psutil.Process(pid)
+        while True:
+            # pid = os.getpid()
+            cpu_util, mem_util, mem_use = stat_info.cpu_percent(
+            ), stat_info.memory_percent(), round(stat_info.memory_info().rss /
+                                                 1024.0 / 1024.0, 4)
+            q.put([cpu_util, mem_util, mem_use])
+            time.sleep(interval)
+        return
+
+
+def get_dataset(data_path, max_seq_len=512):
+    json_lines = []
+    with open(data_path, 'r', encoding='utf-8') as f:
+        for line in f:
+            json_line = json.loads(line)
+            content = json_line['content'].strip()
+            prompt = json_line['prompt']
+            # Model Input is aslike: [CLS] Prompt [SEP] Content [SEP]
+            # It include three summary tokens.
+            if max_seq_len <= len(prompt) + 3:
+                raise ValueError(
+                    "The value of max_seq_len is too small, please set a larger value"
+                )
+            json_lines.append(json_line)
+
+    return json_lines
+
+
+if __name__ == '__main__':
+    args = parse_arguments()
+    runtime_option = build_option(args)
+    model_path = os.path.join(args.model_dir, "inference.pdmodel")
+    param_path = os.path.join(args.model_dir, "inference.pdiparams")
+    vocab_path = os.path.join(args.model_dir, "vocab.txt")
+
+    gpu_id = args.device_id
+    enable_collect_memory_info = args.enable_collect_memory_info
+    dump_result = dict()
+    end2end_statis = list()
+    cpu_mem = list()
+    gpu_mem = list()
+    gpu_util = list()
+    if args.device == "cpu":
+        file_path = args.model_dir + "_model_" + args.backend + "_" + \
+            args.device + "_" + str(args.cpu_num_threads) + ".txt"
+    else:
+        if args.enable_trt_fp16:
+            file_path = args.model_dir + "_model_" + \
+                args.backend + "_fp16_" + args.device + ".txt"
+        else:
+            file_path = args.model_dir + "_model_" + args.backend + "_" + args.device + ".txt"
+    f = open(file_path, "w")
+    f.writelines("===={}====: \n".format(os.path.split(file_path)[-1][:-4]))
+
+    ds = get_dataset(args.data_path)
+    schema = ["时间"]
+    uie = UIEModel(
+        model_path,
+        param_path,
+        vocab_path,
+        position_prob=0.5,
+        max_length=args.max_length,
+        batch_size=args.batch_size,
+        schema=schema,
+        runtime_option=runtime_option,
+        schema_language=SchemaLanguage.ZH)
+
+    try:
+        if enable_collect_memory_info:
+            import multiprocessing
+            import subprocess
+            import psutil
+            import signal
+            import cpuinfo
+            enable_gpu = args.device == "gpu"
+            monitor = Monitor(enable_gpu, gpu_id)
+            monitor.start()
+        uie.enable_record_time_of_runtime()
+
+        for ep in range(args.epoch):
+            for i, sample in enumerate(ds):
+                curr_start = time.time()
+                uie.set_schema([sample['prompt']])
+                result = uie.predict([sample['content']])
+                end2end_statis.append(time.time() - curr_start)
+        runtime_statis = uie.print_statis_info_of_runtime()
+
+        warmup_iter = args.epoch * len(ds) // 5
+
+        end2end_statis_repeat = end2end_statis[warmup_iter:]
+        if enable_collect_memory_info:
+            monitor.stop()
+            mem_info = monitor.output()
+            dump_result["cpu_rss_mb"] = mem_info['cpu'][
+                'memory.used'] if 'cpu' in mem_info else 0
+            dump_result["gpu_rss_mb"] = mem_info['gpu'][
+                'memory.used'] if 'gpu' in mem_info else 0
+            dump_result["gpu_util"] = mem_info['gpu'][
+                'utilization.gpu'] if 'gpu' in mem_info else 0
+
+        dump_result["runtime"] = runtime_statis["avg_time"] * 1000
+        dump_result["end2end"] = np.mean(end2end_statis_repeat) * 1000
+
+        time_cost_str = f"Runtime(ms): {dump_result['runtime']}\n" \
+                        f"End2End(ms): {dump_result['end2end']}\n"
+        f.writelines(time_cost_str)
+        print(time_cost_str)
+
+        if enable_collect_memory_info:
+            mem_info_str = f"cpu_rss_mb: {dump_result['cpu_rss_mb']}\n" \
+                           f"gpu_rss_mb: {dump_result['gpu_rss_mb']}\n" \
+                           f"gpu_util: {dump_result['gpu_util']}\n"
+            f.writelines(mem_info_str)
+            print(mem_info_str)
+    except:
+        f.writelines("!!!!!Infer Failed\n")
+
+    f.close()
diff --git a/benchmark/run_benchmark_uie.sh b/benchmark/run_benchmark_uie.sh
new file mode 100644
index 000000000..51eb5d973
--- /dev/null
+++ b/benchmark/run_benchmark_uie.sh
@@ -0,0 +1,27 @@
+# wget https://bj.bcebos.com/fastdeploy/benchmark/uie/reimbursement_form_data.txt
+# wget https://bj.bcebos.com/fastdeploy/models/uie/uie-base.tgz
+# tar xvfz uie-base.tgz
+
+DEVICE_ID=0
+
+echo "[FastDeploy]    Running UIE benchmark..."
+
+# GPU
+echo "-------------------------------GPU Benchmark---------------------------------------"
+python benchmark_uie.py --epoch 5 --model_dir uie-base --data_path reimbursement_form_data.txt --backend paddle --device_id $DEVICE_ID --device gpu --enable_collect_memory_info True
+python benchmark_uie.py --epoch 5 --model_dir uie-base --data_path reimbursement_form_data.txt --backend ort --device_id $DEVICE_ID --device gpu --enable_collect_memory_info True
+python benchmark_uie.py --epoch 5 --model_dir uie-base --data_path reimbursement_form_data.txt --backend paddle_trt --device_id $DEVICE_ID --device gpu --enable_trt_fp16 False --enable_collect_memory_info True
+python benchmark_uie.py --epoch 5 --model_dir uie-base --data_path reimbursement_form_data.txt --backend trt --device_id $DEVICE_ID --device gpu --enable_trt_fp16 False --enable_collect_memory_info True
+python benchmark_uie.py --epoch 5 --model_dir uie-base --data_path reimbursement_form_data.txt --backend paddle_trt --device_id $DEVICE_ID --device gpu --enable_trt_fp16 True --enable_collect_memory_info True
+python benchmark_uie.py --epoch 5 --model_dir uie-base --data_path reimbursement_form_data.txt --backend trt --device_id $DEVICE_ID --device gpu --enable_trt_fp16 True --enable_collect_memory_info True
+echo "-----------------------------------------------------------------------------------"
+
+# CPU
+echo "-------------------------------CPU Benchmark---------------------------------------"
+for cpu_num_threads in 1 8;
+do
+  python benchmark_uie.py --epoch 5 --model_dir uie-base --data_path reimbursement_form_data.txt --backend paddle --device cpu --cpu_num_threads ${cpu_num_threads} --enable_collect_memory_info True
+  python benchmark_uie.py --epoch 5 --model_dir uie-base --data_path reimbursement_form_data.txt --backend ort --device cpu --cpu_num_threads ${cpu_num_threads} --enable_collect_memory_info True
+  python benchmark_uie.py --epoch 5 --model_dir uie-base --data_path reimbursement_form_data.txt --backend ov --device cpu --cpu_num_threads ${cpu_num_threads} --enable_collect_memory_info True
+done
+echo "-----------------------------------------------------------------------------------"
diff --git a/cmake/paddle_inference.cmake b/cmake/paddle_inference.cmake
index 3822f9ac3..e33a14eb6 100644
--- a/cmake/paddle_inference.cmake
+++ b/cmake/paddle_inference.cmake
@@ -40,16 +40,24 @@ if(WIN32)
       CACHE FILEPATH "paddle_inference compile library." FORCE)
   set(DNNL_LIB "${PADDLEINFERENCE_INSTALL_DIR}/third_party/install/mkldnn/lib/mkldnn.lib")
   set(OMP_LIB "${PADDLEINFERENCE_INSTALL_DIR}/third_party/install/mklml/lib/libiomp5md.lib")
+  set(P2O_LIB "${PADDLEINFERENCE_INSTALL_DIR}/third_party/install/paddle2onnx/lib/paddle2onnx.lib")
+  set(ORT_LIB "${PADDLEINFERENCE_INSTALL_DIR}/third_party/install/onnxruntime/lib/onnxruntime.lib")
 elseif(APPLE)
   set(PADDLEINFERENCE_COMPILE_LIB
       "${PADDLEINFERENCE_INSTALL_DIR}/paddle/lib/libpaddle_inference.dylib"
       CACHE FILEPATH "paddle_inference compile library." FORCE)
+  set(DNNL_LIB "${PADDLEINFERENCE_INSTALL_DIR}/third_party/install/mkldnn/lib/libdnnl.so.2")
+  set(OMP_LIB "${PADDLEINFERENCE_INSTALL_DIR}/third_party/install/mklml/lib/libiomp5.so")
+  set(P2O_LIB "${PADDLEINFERENCE_INSTALL_DIR}/third_party/install/paddle2onnx/lib/libpaddle2onnx.dylib")
+  set(ORT_LIB "${PADDLEINFERENCE_INSTALL_DIR}/third_party/install/onnxruntime/lib/libonnxruntime.dylib")
 else()
   set(PADDLEINFERENCE_COMPILE_LIB
       "${PADDLEINFERENCE_INSTALL_DIR}/paddle/lib/libpaddle_inference.so"
       CACHE FILEPATH "paddle_inference compile library." FORCE)
   set(DNNL_LIB "${PADDLEINFERENCE_INSTALL_DIR}/third_party/install/mkldnn/lib/libdnnl.so.2")
   set(OMP_LIB "${PADDLEINFERENCE_INSTALL_DIR}/third_party/install/mklml/lib/libiomp5.so")
+  set(P2O_LIB "${PADDLEINFERENCE_INSTALL_DIR}/third_party/install/paddle2onnx/lib/libpaddle2onnx.so")
+  set(ORT_LIB "${PADDLEINFERENCE_INSTALL_DIR}/third_party/install/onnxruntime/lib/libonnxruntime.so")
 endif(WIN32)
 
 
@@ -116,16 +124,23 @@ set_property(TARGET external_paddle_inference PROPERTY IMPORTED_LOCATION
                                          ${PADDLEINFERENCE_COMPILE_LIB})
 add_dependencies(external_paddle_inference ${PADDLEINFERENCE_PROJECT})
 
-if (NOT APPLE)
-  # no third parties libs(mkldnn and omp) need to 
-  # link into paddle_inference on MacOS OSX.
-  add_library(external_dnnl STATIC IMPORTED GLOBAL)
-  set_property(TARGET external_dnnl PROPERTY IMPORTED_LOCATION
-                                          ${DNNL_LIB})
-  add_dependencies(external_dnnl ${PADDLEINFERENCE_PROJECT})
 
-  add_library(external_omp STATIC IMPORTED GLOBAL)
-  set_property(TARGET external_omp PROPERTY IMPORTED_LOCATION
-                                          ${OMP_LIB})
-  add_dependencies(external_omp ${PADDLEINFERENCE_PROJECT})
-endif()
+add_library(external_p2o STATIC IMPORTED GLOBAL)
+set_property(TARGET external_p2o PROPERTY IMPORTED_LOCATION
+        ${P2O_LIB})
+add_dependencies(external_p2o ${PADDLEINFERENCE_PROJECT})
+
+add_library(external_ort STATIC IMPORTED GLOBAL)
+set_property(TARGET external_ort PROPERTY IMPORTED_LOCATION
+        ${ORT_LIB})
+add_dependencies(external_ort ${PADDLEINFERENCE_PROJECT})
+
+add_library(external_dnnl STATIC IMPORTED GLOBAL)
+set_property(TARGET external_dnnl PROPERTY IMPORTED_LOCATION
+                                        ${DNNL_LIB})
+add_dependencies(external_dnnl ${PADDLEINFERENCE_PROJECT})
+
+add_library(external_omp STATIC IMPORTED GLOBAL)
+set_property(TARGET external_omp PROPERTY IMPORTED_LOCATION
+                                        ${OMP_LIB})
+add_dependencies(external_omp ${PADDLEINFERENCE_PROJECT})
diff --git a/cmake/toolchain.cmake b/cmake/toolchain.cmake
index 4b3485748..85bd05798 100755
--- a/cmake/toolchain.cmake
+++ b/cmake/toolchain.cmake
@@ -10,7 +10,7 @@ if (DEFINED TARGET_ABI)
         set(OPENCV_URL "https://bj.bcebos.com/fastdeploy/third_libs/opencv-linux-armv7hf-4.6.0.tgz")
         set(OPENCV_FILENAME "opencv-linux-armv7hf-4.6.0")
         if(WITH_TIMVX)
-            set(PADDLELITE_URL "https://bj.bcebos.com/fastdeploy/third_libs/lite-linux-armhf-timvx-1130.tgz")
+            set(PADDLELITE_URL "https://bj.bcebos.com/fastdeploy/third_libs/lite-linux-armhf-timvx-20221229.tgz")
         else()
             message(STATUS "PADDLELITE_URL will be configured if WITH_TIMVX=ON.")
         endif()
diff --git a/examples/text/uie/serving/models/uie/1/model.py b/examples/text/uie/serving/models/uie/1/model.py
index 5bb1c8164..b839ae065 100644
--- a/examples/text/uie/serving/models/uie/1/model.py
+++ b/examples/text/uie/serving/models/uie/1/model.py
@@ -141,7 +141,7 @@ class TritonPythonModel:
                 self.uie_model_.set_schema(schema)
             results = self.uie_model_.predict(texts, return_dict=True)
 
-            results = np.array(results, dtype=np.object)
+            results = np.array(results, dtype=np.object_)
             out_tensor = pb_utils.Tensor(self.output_names[0], results)
             inference_response = pb_utils.InferenceResponse(
                 output_tensors=[out_tensor, ])
diff --git a/examples/vision/classification/paddleclas/rknpu2/cpp/README.md b/examples/vision/classification/paddleclas/rknpu2/cpp/README.md
index 1e1883486..c21d1d77b 100644
--- a/examples/vision/classification/paddleclas/rknpu2/cpp/README.md
+++ b/examples/vision/classification/paddleclas/rknpu2/cpp/README.md
@@ -64,8 +64,8 @@ cd ./build/install
 
 ## 运行结果展示
 ClassifyResult(
-label_ids: 153, 
-scores: 0.684570, 
+label_ids: 153,
+scores: 0.684570,
 )
 
 ## 注意事项
@@ -75,4 +75,4 @@ DisablePermute(C++)或`disable_permute(Python)，在预处理阶段禁用数据
 ## 其它文档
 - [ResNet50_vd Python 部署](../python)
 - [模型预测结果说明](../../../../../../docs/api/vision_results/)
-- [转换ResNet50_vd RKNN模型文档](../README.md)
\ No newline at end of file
+- [转换ResNet50_vd RKNN模型文档](../README.md)
diff --git a/examples/vision/classification/paddleclas/rknpu2/python/README.md b/examples/vision/classification/paddleclas/rknpu2/python/README.md
index b85bb81f7..f1f0994d8 100644
--- a/examples/vision/classification/paddleclas/rknpu2/python/README.md
+++ b/examples/vision/classification/paddleclas/rknpu2/python/README.md
@@ -19,8 +19,8 @@ python3 infer.py --model_file ./ResNet50_vd_infer/ResNet50_vd_infer_rk3588.rknn
 
 # 运行完成后返回结果如下所示
 ClassifyResult(
-label_ids: 153, 
-scores: 0.684570, 
+label_ids: 153,
+scores: 0.684570,
 )
 ```
 
@@ -32,4 +32,4 @@ DisablePermute(C++)或`disable_permute(Python)，在预处理阶段禁用数据
 ## 其它文档
 - [ResNet50_vd C++部署](../cpp)
 - [模型预测结果说明](../../../../../../docs/api/vision_results/)
-- [转换ResNet50_vd RKNN模型文档](../README.md)
\ No newline at end of file
+- [转换ResNet50_vd RKNN模型文档](../README.md)
diff --git a/examples/vision/classification/paddleclas/serving/models/postprocess/1/model.py b/examples/vision/classification/paddleclas/serving/models/postprocess/1/model.py
index 0ab7dcdc4..de000f6ee 100755
--- a/examples/vision/classification/paddleclas/serving/models/postprocess/1/model.py
+++ b/examples/vision/classification/paddleclas/serving/models/postprocess/1/model.py
@@ -92,7 +92,7 @@ class TritonPythonModel:
             results = self.postprocess_.run([infer_outputs, ])
             r_str = fd.vision.utils.fd_result_to_json(results)
 
-            r_np = np.array(r_str, dtype=np.object)
+            r_np = np.array(r_str, dtype=np.object_)
             out_tensor = pb_utils.Tensor(self.output_names[0], r_np)
             inference_response = pb_utils.InferenceResponse(
                 output_tensors=[out_tensor, ])
diff --git a/examples/vision/detection/nanodet_plus/python/README.md b/examples/vision/detection/nanodet_plus/python/README.md
index b5085662c..a89e15d1b 100644
--- a/examples/vision/detection/nanodet_plus/python/README.md
+++ b/examples/vision/detection/nanodet_plus/python/README.md
@@ -69,7 +69,7 @@ NanoDetPlus模型加载和初始化，其中model_file为导出的ONNX模型格
 > > * **padding_value**(list[float]): 通过此参数可以修改图片在resize时候做填充(padding)的值, 包含三个浮点型元素, 分别表示三个通道的值, 默认值为[0, 0, 0]
 > > * **keep_ratio**(bool): 通过此参数指定resize时是否保持宽高比例不变，默认是fasle.
 > > * **reg_max**(int): GFL回归中的reg_max参数，默认是7.
-> > * **downsample_strides**(list[int]): 通过此参数可以修改生成anchor的特征图的下采样倍数, 包含三个整型元素, 分别表示默认的生成anchor的下采样倍数, 默认值为[8, 16, 32, 64]
+> > * **downsample_strides**(list[int]): 通过此参数可以修改生成anchor的特征图的下采样倍数, 包含四个整型元素, 分别表示默认的生成anchor的下采样倍数, 默认值为[8, 16, 32, 64]
 
 
 
diff --git a/examples/vision/detection/paddledetection/serving/models/postprocess/1/model.py b/examples/vision/detection/paddledetection/serving/models/postprocess/1/model.py
index 4872b0dee..35054e516 100644
--- a/examples/vision/detection/paddledetection/serving/models/postprocess/1/model.py
+++ b/examples/vision/detection/paddledetection/serving/models/postprocess/1/model.py
@@ -95,7 +95,7 @@ class TritonPythonModel:
             results = self.postprocess_.run(infer_outputs)
             r_str = fd.vision.utils.fd_result_to_json(results)
 
-            r_np = np.array(r_str, dtype=np.object)
+            r_np = np.array(r_str, dtype=np.object_)
             out_tensor = pb_utils.Tensor(self.output_names[0], r_np)
             inference_response = pb_utils.InferenceResponse(
                 output_tensors=[out_tensor, ])
diff --git a/examples/vision/detection/yolov5/serving/models/postprocess/1/model.py b/examples/vision/detection/yolov5/serving/models/postprocess/1/model.py
index 7c608db43..1204446c4 100644
--- a/examples/vision/detection/yolov5/serving/models/postprocess/1/model.py
+++ b/examples/vision/detection/yolov5/serving/models/postprocess/1/model.py
@@ -96,7 +96,7 @@ class TritonPythonModel:
 
             results = self.postprocessor_.run([infer_outputs], im_infos)
             r_str = fd.vision.utils.fd_result_to_json(results)
-            r_np = np.array(r_str, dtype=np.object)
+            r_np = np.array(r_str, dtype=np.object_)
 
             out_tensor = pb_utils.Tensor(self.output_names[0], r_np)
             inference_response = pb_utils.InferenceResponse(
diff --git a/examples/vision/detection/yolov5/serving/models/preprocess/1/model.py b/examples/vision/detection/yolov5/serving/models/preprocess/1/model.py
index cf4f7e8e8..d60de6541 100644
--- a/examples/vision/detection/yolov5/serving/models/preprocess/1/model.py
+++ b/examples/vision/detection/yolov5/serving/models/preprocess/1/model.py
@@ -95,7 +95,7 @@ class TritonPythonModel:
                                                           dlpack_tensor)
             output_tensor_1 = pb_utils.Tensor(
                 self.output_names[1], np.array(
-                    im_infos, dtype=np.object))
+                    im_infos, dtype=np.object_))
             inference_response = pb_utils.InferenceResponse(
                 output_tensors=[output_tensor_0, output_tensor_1])
             responses.append(inference_response)
diff --git a/examples/vision/ocr/PP-OCRv3/serving/models/det_postprocess/1/model.py b/examples/vision/ocr/PP-OCRv3/serving/models/det_postprocess/1/model.py
index faaca9067..9cfe2583e 100644
--- a/examples/vision/ocr/PP-OCRv3/serving/models/det_postprocess/1/model.py
+++ b/examples/vision/ocr/PP-OCRv3/serving/models/det_postprocess/1/model.py
@@ -217,7 +217,7 @@ class TritonPythonModel:
             out_tensor_0 = pb_utils.Tensor(
                 self.output_names[0],
                 np.array(
-                    batch_rec_texts, dtype=np.object))
+                    batch_rec_texts, dtype=np.object_))
             out_tensor_1 = pb_utils.Tensor(self.output_names[1],
                                            np.array(batch_rec_scores))
             inference_response = pb_utils.InferenceResponse(
diff --git a/examples/vision/ocr/PP-OCRv3/serving/models/rec_postprocess/1/model.py b/examples/vision/ocr/PP-OCRv3/serving/models/rec_postprocess/1/model.py
index fe66e8c3f..c046cd929 100755
--- a/examples/vision/ocr/PP-OCRv3/serving/models/rec_postprocess/1/model.py
+++ b/examples/vision/ocr/PP-OCRv3/serving/models/rec_postprocess/1/model.py
@@ -96,7 +96,7 @@ class TritonPythonModel:
             results = self.postprocessor.run([infer_outputs])
             out_tensor_0 = pb_utils.Tensor(
                 self.output_names[0], np.array(
-                    results[0], dtype=np.object))
+                    results[0], dtype=np.object_))
             out_tensor_1 = pb_utils.Tensor(self.output_names[1],
                                            np.array(results[1]))
             inference_response = pb_utils.InferenceResponse(
diff --git a/examples/vision/segmentation/paddleseg/rknpu2/cpp/infer.cc b/examples/vision/segmentation/paddleseg/rknpu2/cpp/infer.cc
index 834b2ccb3..f80d3fc8f 100644
--- a/examples/vision/segmentation/paddleseg/rknpu2/cpp/infer.cc
+++ b/examples/vision/segmentation/paddleseg/rknpu2/cpp/infer.cc
@@ -62,7 +62,8 @@ void RKNPU2Infer(const std::string& model_dir, const std::string& image_file) {
     std::cerr << "Failed to initialize." << std::endl;
     return;
   }
-  model.GetPreprocessor().DisableNormalizeAndPermute();
+  model.GetPreprocessor().DisablePermute();
+  model.GetPreprocessor().DisableNormalize();
 
   fastdeploy::TimeCounter tc;
   tc.Start();
diff --git a/examples/vision/segmentation/paddleseg/rknpu2/python/infer.py b/examples/vision/segmentation/paddleseg/rknpu2/python/infer.py
index 4168d591d..193a6dfb9 100644
--- a/examples/vision/segmentation/paddleseg/rknpu2/python/infer.py
+++ b/examples/vision/segmentation/paddleseg/rknpu2/python/infer.py
@@ -49,7 +49,8 @@ model = fd.vision.segmentation.PaddleSegModel(
     runtime_option=runtime_option,
     model_format=fd.ModelFormat.RKNN)
 
-model.preprocessor.disable_normalize_and_permute()
+model.preprocessor.disable_normalize()
+model.preprocessor.disable_permute()
 
 # 预测图片分割结果
 im = cv2.imread(args.image)
diff --git a/fastdeploy/vision/detection/ppdet/model.h b/fastdeploy/vision/detection/ppdet/model.h
index be13b0b4d..17502cf21 100755
--- a/fastdeploy/vision/detection/ppdet/model.h
+++ b/fastdeploy/vision/detection/ppdet/model.h
@@ -68,6 +68,7 @@ class FASTDEPLOY_DECL PPYOLOE : public PPDetBase {
     valid_gpu_backends = {Backend::ORT, Backend::PDINFER, Backend::TRT};
     valid_timvx_backends = {Backend::LITE};
     valid_kunlunxin_backends = {Backend::LITE};
+    valid_rknpu_backends = {Backend::RKNPU2};
     valid_ascend_backends = {Backend::LITE};
     initialized = Initialize();
   }
diff --git a/fastdeploy/vision/detection/ppdet/ppdet_pybind.cc b/fastdeploy/vision/detection/ppdet/ppdet_pybind.cc
index 09c89dfce..573164910 100644
--- a/fastdeploy/vision/detection/ppdet/ppdet_pybind.cc
+++ b/fastdeploy/vision/detection/ppdet/ppdet_pybind.cc
@@ -31,7 +31,13 @@ void BindPPDet(pybind11::module& m) {
           outputs[i].StopSharing();
         }
         return outputs;
-      });
+      })
+      .def("disable_normalize", [](vision::detection::PaddleDetPreprocessor& self) {
+        self.DisableNormalize();
+      })
+      .def("disable_permute", [](vision::detection::PaddleDetPreprocessor& self) {
+        self.DisablePermute();
+      });;
 
   pybind11::class_<vision::detection::PaddleDetPostprocessor>(
       m, "PaddleDetPostprocessor")
diff --git a/fastdeploy/vision/detection/ppdet/preprocessor.cc b/fastdeploy/vision/detection/ppdet/preprocessor.cc
index bb38c67ec..a18d43b70 100644
--- a/fastdeploy/vision/detection/ppdet/preprocessor.cc
+++ b/fastdeploy/vision/detection/ppdet/preprocessor.cc
@@ -22,19 +22,19 @@ namespace vision {
 namespace detection {
 
 PaddleDetPreprocessor::PaddleDetPreprocessor(const std::string& config_file) {
-  FDASSERT(BuildPreprocessPipelineFromConfig(config_file),
+  this->config_file_ = config_file;
+  FDASSERT(BuildPreprocessPipelineFromConfig(),
            "Failed to create PaddleDetPreprocessor.");
   initialized_ = true;
 }
 
-bool PaddleDetPreprocessor::BuildPreprocessPipelineFromConfig(
-    const std::string& config_file) {
+bool PaddleDetPreprocessor::BuildPreprocessPipelineFromConfig() {
   processors_.clear();
   YAML::Node cfg;
   try {
-    cfg = YAML::LoadFile(config_file);
+    cfg = YAML::LoadFile(config_file_);
   } catch (YAML::BadFile& e) {
-    FDERROR << "Failed to load yaml file " << config_file
+    FDERROR << "Failed to load yaml file " << config_file_
             << ", maybe you should check this file." << std::endl;
     return false;
   }
@@ -45,21 +45,23 @@ bool PaddleDetPreprocessor::BuildPreprocessPipelineFromConfig(
   for (const auto& op : cfg["Preprocess"]) {
     std::string op_name = op["type"].as<std::string>();
     if (op_name == "NormalizeImage") {
-      auto mean = op["mean"].as<std::vector<float>>();
-      auto std = op["std"].as<std::vector<float>>();
-      bool is_scale = true;
-      if (op["is_scale"]) {
-        is_scale = op["is_scale"].as<bool>();
+      if (!disable_normalize_) {
+        auto mean = op["mean"].as<std::vector<float>>();
+        auto std = op["std"].as<std::vector<float>>();
+        bool is_scale = true;
+        if (op["is_scale"]) {
+          is_scale = op["is_scale"].as<bool>();
+        }
+        std::string norm_type = "mean_std";
+        if (op["norm_type"]) {
+          norm_type = op["norm_type"].as<std::string>();
+        }
+        if (norm_type != "mean_std") {
+          std::fill(mean.begin(), mean.end(), 0.0);
+          std::fill(std.begin(), std.end(), 1.0);
+        }
+        processors_.push_back(std::make_shared<Normalize>(mean, std, is_scale));
       }
-      std::string norm_type = "mean_std";
-      if (op["norm_type"]) {
-        norm_type = op["norm_type"].as<std::string>();
-      }
-      if (norm_type != "mean_std") {
-        std::fill(mean.begin(), mean.end(), 0.0);
-        std::fill(std.begin(), std.end(), 1.0);
-      }
-      processors_.push_back(std::make_shared<Normalize>(mean, std, is_scale));
     } else if (op_name == "Resize") {
       bool keep_ratio = op["keep_ratio"].as<bool>();
       auto target_size = op["target_size"].as<std::vector<int>>();
@@ -104,10 +106,12 @@ bool PaddleDetPreprocessor::BuildPreprocessPipelineFromConfig(
       return false;
     }
   }
-  if (has_permute) {
-    // permute = cast<float> + HWC2CHW
-    processors_.push_back(std::make_shared<Cast>("float"));
-    processors_.push_back(std::make_shared<HWC2CHW>());
+  if (!disable_permute_) {
+    if (has_permute) {
+      // permute = cast<float> + HWC2CHW
+      processors_.push_back(std::make_shared<Cast>("float"));
+      processors_.push_back(std::make_shared<HWC2CHW>());
+    }
   }
 
   // Fusion will improve performance
@@ -202,7 +206,20 @@ bool PaddleDetPreprocessor::Run(std::vector<FDMat>* images,
 
   return true;
 }
-
+void PaddleDetPreprocessor::DisableNormalize() {
+  this->disable_normalize_ = true;
+  // the DisableNormalize function will be invalid if the configuration file is loaded during preprocessing
+  if (!BuildPreprocessPipelineFromConfig()) {
+    FDERROR << "Failed to build preprocess pipeline from configuration file." << std::endl;
+  }
+}
+void PaddleDetPreprocessor::DisablePermute() {
+  this->disable_permute_ = true;
+  // the DisablePermute function will be invalid if the configuration file is loaded during preprocessing
+  if (!BuildPreprocessPipelineFromConfig()) {
+    FDERROR << "Failed to build preprocess pipeline from configuration file." << std::endl;
+  }
+}
 } // namespace detection
 } // namespace vision
 } // namespace fastdeploy
diff --git a/fastdeploy/vision/detection/ppdet/preprocessor.h b/fastdeploy/vision/detection/ppdet/preprocessor.h
index 2733c450e..8371afb69 100644
--- a/fastdeploy/vision/detection/ppdet/preprocessor.h
+++ b/fastdeploy/vision/detection/ppdet/preprocessor.h
@@ -39,10 +39,21 @@ class FASTDEPLOY_DECL PaddleDetPreprocessor {
    */
   bool Run(std::vector<FDMat>* images, std::vector<FDTensor>* outputs);
 
+  /// This function will disable normalize in preprocessing step.
+  void DisableNormalize();
+  /// This function will disable hwc2chw in preprocessing step.
+  void DisablePermute();
+
  private:
-  bool BuildPreprocessPipelineFromConfig(const std::string& config_file);
+  bool BuildPreprocessPipelineFromConfig();
   std::vector<std::shared_ptr<Processor>> processors_;
   bool initialized_ = false;
+  // for recording the switch of hwc2chw
+  bool disable_permute_ = false;
+  // for recording the switch of normalize
+  bool disable_normalize_ = false;
+  // read config file
+  std::string config_file_;
 };
 
 }  // namespace detection
diff --git a/fastdeploy/vision/segmentation/ppseg/ppseg_pybind.cc b/fastdeploy/vision/segmentation/ppseg/ppseg_pybind.cc
index e687d3cc4..78c7c9ccc 100644
--- a/fastdeploy/vision/segmentation/ppseg/ppseg_pybind.cc
+++ b/fastdeploy/vision/segmentation/ppseg/ppseg_pybind.cc
@@ -36,9 +36,12 @@ void BindPPSeg(pybind11::module& m) {
              }
              return make_pair(outputs, imgs_info);;
            })
-      .def("disable_normalize_and_permute",
-                     &vision::segmentation::PaddleSegPreprocessor::DisableNormalizeAndPermute)
-                     
+      .def("disable_normalize", [](vision::segmentation::PaddleSegPreprocessor& self) {
+        self.DisableNormalize();
+      })
+      .def("disable_permute", [](vision::segmentation::PaddleSegPreprocessor& self) {
+        self.DisablePermute();
+      })
       .def_property("is_vertical_screen",
                      &vision::segmentation::PaddleSegPreprocessor::GetIsVerticalScreen,
 		     &vision::segmentation::PaddleSegPreprocessor::SetIsVerticalScreen);
diff --git a/fastdeploy/vision/segmentation/ppseg/preprocessor.cc b/fastdeploy/vision/segmentation/ppseg/preprocessor.cc
index 027309aad..92b037895 100644
--- a/fastdeploy/vision/segmentation/ppseg/preprocessor.cc
+++ b/fastdeploy/vision/segmentation/ppseg/preprocessor.cc
@@ -43,7 +43,7 @@ bool PaddleSegPreprocessor::BuildPreprocessPipelineFromConfig() {
       FDASSERT(op.IsMap(),
                "Require the transform information in yaml be Map type.");
       if (op["type"].as<std::string>() == "Normalize") {
-        if (!disable_normalize_and_permute_) {
+        if (!disable_normalize_) {
           std::vector<float> mean = {0.5, 0.5, 0.5};
           std::vector<float> std = {0.5, 0.5, 0.5};
           if (op["mean"]) {
@@ -55,7 +55,7 @@ bool PaddleSegPreprocessor::BuildPreprocessPipelineFromConfig() {
           processors_.push_back(std::make_shared<Normalize>(mean, std));
         }
       } else if (op["type"].as<std::string>() == "Resize") {
-        is_contain_resize_op = true;
+        is_contain_resize_op_ = true;
         const auto& target_size = op["target_size"];
         int resize_width = target_size[0].as<int>();
         int resize_height = target_size[1].as<int>();
@@ -73,13 +73,13 @@ bool PaddleSegPreprocessor::BuildPreprocessPipelineFromConfig() {
     auto input_shape = cfg["Deploy"]["input_shape"];
     int input_height = input_shape[2].as<int>();
     int input_width = input_shape[3].as<int>();
-    if (input_height != -1 && input_width != -1 && !is_contain_resize_op) {
-      is_contain_resize_op = true;
+    if (input_height != -1 && input_width != -1 && !is_contain_resize_op_) {
+      is_contain_resize_op_ = true;
       processors_.insert(processors_.begin(),
           std::make_shared<Resize>(input_width, input_height));
     }
   }
-  if (!disable_normalize_and_permute_) {
+  if (!disable_permute_) {
     processors_.push_back(std::make_shared<HWC2CHW>());
   }
 
@@ -121,7 +121,7 @@ bool PaddleSegPreprocessor::Run(std::vector<FDMat>* images, std::vector<FDTensor
   }
   size_t img_num = images->size();
   // Batch preprocess : resize all images to the largest image shape in batch
-  if (!is_contain_resize_op && img_num > 1) {
+  if (!is_contain_resize_op_ && img_num > 1) {
     int max_width = 0;
     int max_height = 0; 
     for (size_t i = 0; i < img_num; ++i) {
@@ -156,14 +156,20 @@ bool PaddleSegPreprocessor::Run(std::vector<FDMat>* images, std::vector<FDTensor
   return true;
 }
 
-void PaddleSegPreprocessor::DisableNormalizeAndPermute(){
-  disable_normalize_and_permute_ = true;
-  // the DisableNormalizeAndPermute function will be invalid if the configuration file is loaded during preprocessing
+void PaddleSegPreprocessor::DisableNormalize() {
+  this->disable_normalize_ = true;
+  // the DisableNormalize function will be invalid if the configuration file is loaded during preprocessing
+  if (!BuildPreprocessPipelineFromConfig()) {
+    FDERROR << "Failed to build preprocess pipeline from configuration file." << std::endl;
+  }
+}
+void PaddleSegPreprocessor::DisablePermute() {
+  this->disable_permute_ = true;
+  // the DisablePermute function will be invalid if the configuration file is loaded during preprocessing
   if (!BuildPreprocessPipelineFromConfig()) {
     FDERROR << "Failed to build preprocess pipeline from configuration file." << std::endl;
   }
 }
-
 }  // namespace segmentation
 }  // namespace vision
 }  // namespace fastdeploy
diff --git a/fastdeploy/vision/segmentation/ppseg/preprocessor.h b/fastdeploy/vision/segmentation/ppseg/preprocessor.h
index faa7fb8de..6452e8e0e 100644
--- a/fastdeploy/vision/segmentation/ppseg/preprocessor.h
+++ b/fastdeploy/vision/segmentation/ppseg/preprocessor.h
@@ -49,8 +49,10 @@ class FASTDEPLOY_DECL PaddleSegPreprocessor {
     is_vertical_screen_ = value;
   }
 
-  // This function will disable normalize and hwc2chw in preprocessing step.
-  void DisableNormalizeAndPermute();
+  /// This function will disable normalize in preprocessing step.
+  void DisableNormalize();
+  /// This function will disable hwc2chw in preprocessing step.
+  void DisablePermute();
 
  private:
   virtual bool BuildPreprocessPipelineFromConfig();
@@ -61,10 +63,12 @@ class FASTDEPLOY_DECL PaddleSegPreprocessor {
    */
   bool is_vertical_screen_ = false;
 
-  // for recording the switch of normalize and hwc2chw
-  bool disable_normalize_and_permute_ = false;
+  // for recording the switch of hwc2chw
+  bool disable_permute_ = false;
+  // for recording the switch of normalize
+  bool disable_normalize_ = false;
 
-  bool is_contain_resize_op = false;
+  bool is_contain_resize_op_ = false;
 
   bool initialized_ = false;
 };
diff --git a/python/fastdeploy/vision/detection/ppdet/__init__.py b/python/fastdeploy/vision/detection/ppdet/__init__.py
index 45734eef0..f9b162aca 100644
--- a/python/fastdeploy/vision/detection/ppdet/__init__.py
+++ b/python/fastdeploy/vision/detection/ppdet/__init__.py
@@ -36,6 +36,18 @@ class PaddleDetPreprocessor:
         """
         return self._preprocessor.run(input_ims)
 
+    def disable_normalize(self):
+        """
+        This function will disable normalize in preprocessing step.
+        """
+        self._preprocessor.disable_normalize()
+
+    def disable_permute(self):
+        """
+        This function will disable hwc2chw in preprocessing step.
+        """
+        self._preprocessor.disable_permute()
+
 
 class PaddleDetPostprocessor:
     def __init__(self):
@@ -500,4 +512,4 @@ class RTMDet(PPYOLOE):
         self._model = C.vision.detection.RTMDet(
             model_file, params_file, config_file, self._runtime_option,
             model_format)
-        assert self.initialized, "RTMDet model initialize failed."
\ No newline at end of file
+        assert self.initialized, "RTMDet model initialize failed."
diff --git a/python/fastdeploy/vision/segmentation/ppseg/__init__.py b/python/fastdeploy/vision/segmentation/ppseg/__init__.py
index 455785686..f0106a39a 100644
--- a/python/fastdeploy/vision/segmentation/ppseg/__init__.py
+++ b/python/fastdeploy/vision/segmentation/ppseg/__init__.py
@@ -104,10 +104,17 @@ class PaddleSegPreprocessor:
         """
         return self._preprocessor.run(input_ims)
 
-    def disable_normalize_and_permute(self):
-        """To disable normalize and hwc2chw in preprocessing step.
+    def disable_normalize(self):
         """
-        return self._preprocessor.disable_normalize_and_permute()
+        This function will disable normalize in preprocessing step.
+        """
+        self._preprocessor.disable_normalize()
+
+    def disable_permute(self):
+        """
+        This function will disable hwc2chw in preprocessing step.
+        """
+        self._preprocessor.disable_permute()
 
     @property
     def is_vertical_screen(self):