diff --git a/models/cv/classification/alexnet/ixrt/README.md b/models/cv/classification/alexnet/ixrt/README.md
index 4a25a911ba8e49f530ce4602eeed5845e02debe3..65fa53efbc1115f3c9bb26c820afa1337d78a561 100644
--- a/models/cv/classification/alexnet/ixrt/README.md
+++ b/models/cv/classification/alexnet/ixrt/README.md
@@ -15,11 +15,7 @@ yum install -y mesa-libGL
 ## Ubuntu
 apt install -y libgl1-mesa-dev
 
-pip3 install tqdm
-pip3 install onnx
-pip3 install onnxsim
-pip3 install tabulate
-pip3 install pycuda
+pip3 install -r requirements.txt
 ```
 
 ### Download
diff --git a/models/cv/classification/alexnet/ixrt/requirements.txt b/models/cv/classification/alexnet/ixrt/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..bc645b22bbcf3675e3bfe6f8d2da91ca8c089b3a
--- /dev/null
+++ b/models/cv/classification/alexnet/ixrt/requirements.txt
@@ -0,0 +1,5 @@
+tqdm
+onnx
+onnxsim
+tabulate
+pycuda
\ No newline at end of file
diff --git a/models/cv/classification/densenet121/ixrt/README.md b/models/cv/classification/densenet121/ixrt/README.md
index 9b5c20781e62eabf873f71a0dc63f61a4b015a29..f506c085b2dadc6c4a62164c258bc571d51ac27e 100644
--- a/models/cv/classification/densenet121/ixrt/README.md
+++ b/models/cv/classification/densenet121/ixrt/README.md
@@ -15,12 +15,7 @@ yum install -y mesa-libGL
 ## Ubuntu
 apt install -y libgl1-mesa-dev
 
-pip3 install tqdm
-pip3 install onnx
-pip3 install onnxsim
-pip3 install tabulate
-pip3 install ppq
-pip3 install pycuda
+pip3 install -r requirements.txt
 ```
 
 ### Download
@@ -40,7 +35,7 @@ python3 export_onnx.py --output_model checkpoints/densenet121.onnx
 export DATASETS_DIR=/path/to/imagenet_val/
 export CHECKPOINTS_DIR=./checkpoints
 export RUN_DIR=./
-export CONFIG_DIR=config/DENSENET_CONFIG
+export CONFIG_DIR=config/DENSENET121_CONFIG
 ```
 
 ### FP16
diff --git a/models/cv/classification/densenet121/ixrt/config/DENSENET_CONFIG b/models/cv/classification/densenet121/ixrt/config/DENSENET121_CONFIG
similarity index 100%
rename from models/cv/classification/densenet121/ixrt/config/DENSENET_CONFIG
rename to models/cv/classification/densenet121/ixrt/config/DENSENET121_CONFIG
diff --git a/models/cv/classification/densenet121/ixrt/inference.py b/models/cv/classification/densenet121/ixrt/inference.py
index 2c9dcb3f9cc5b9a26903651a31fafa16d8f0db31..50aafd4fd5ef9664203cdcbdfbdb577edca933c4 100644
--- a/models/cv/classification/densenet121/ixrt/inference.py
+++ b/models/cv/classification/densenet121/ixrt/inference.py
@@ -83,6 +83,7 @@ def main(config):
         total_sample = 0
         acc_top1, acc_top5 = 0, 0
 
+        start_time = time.time()
         with tqdm(total= len(dataloader)) as _tqdm:
             for idx, (batch_data, batch_label) in enumerate(dataloader):
                 batch_data = batch_data.numpy().astype(inputs[0]["dtype"])
@@ -104,7 +105,10 @@ def main(config):
                 _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample),
                                     acc_5='{:.4f}'.format(acc_top5/total_sample))
                 _tqdm.update(1)
+        end_time = time.time()
+        end2end_time = end_time - start_time
 
+        print(F"E2E time : {end2end_time:.3f} seconds")
         print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}")
         print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}")
         acc1 = acc_top1/total_sample
diff --git a/models/cv/classification/densenet121/ixrt/requirements.txt b/models/cv/classification/densenet121/ixrt/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..01ec4f116bdac5ae39f168903eed8268f2391a08
--- /dev/null
+++ b/models/cv/classification/densenet121/ixrt/requirements.txt
@@ -0,0 +1,6 @@
+tqdm
+onnx
+onnxsim
+tabulate
+ppq
+pycuda
\ No newline at end of file
diff --git a/models/cv/classification/densenet121/ixrt/scripts/infer_densenet_fp16_accuracy.sh b/models/cv/classification/densenet121/ixrt/scripts/infer_densenet121_fp16_accuracy.sh
similarity index 100%
rename from models/cv/classification/densenet121/ixrt/scripts/infer_densenet_fp16_accuracy.sh
rename to models/cv/classification/densenet121/ixrt/scripts/infer_densenet121_fp16_accuracy.sh
diff --git a/models/cv/classification/densenet121/ixrt/scripts/infer_densenet_fp16_performance.sh b/models/cv/classification/densenet121/ixrt/scripts/infer_densenet121_fp16_performance.sh
similarity index 100%
rename from models/cv/classification/densenet121/ixrt/scripts/infer_densenet_fp16_performance.sh
rename to models/cv/classification/densenet121/ixrt/scripts/infer_densenet121_fp16_performance.sh
diff --git a/models/cv/classification/efficientnet_b0/ixrt/README.md b/models/cv/classification/efficientnet_b0/ixrt/README.md
index bf57f509112404bf3a2ba2ead6a1dd828d539a3b..e7f3087bc24565d9459a8d90caf5e19585c07f11 100644
--- a/models/cv/classification/efficientnet_b0/ixrt/README.md
+++ b/models/cv/classification/efficientnet_b0/ixrt/README.md
@@ -15,12 +15,7 @@ yum install -y mesa-libGL
 ## Ubuntu
 apt install -y libgl1-mesa-dev
 
-pip3 install tqdm
-pip3 install onnx
-pip3 install onnxsim
-pip3 install tabulate
-pip3 install ppq==0.6.6
-pip install protobuf==3.20.3 pycuda
+pip3 install -r requirements.txt
 ```
 
 ### Download
@@ -32,7 +27,7 @@ Dataset: <https://www.image-net.org/download.php> to download the validation dat
 ### Model Conversion
 
 ```bash
-python3 python/export_onnx.py --origin_model /path/to/efficientnet_b0_rwightman-3dd342df.pth --output_model efficientnet-b0.onnx
+python3 python/export_onnx.py --origin_model /path/to/efficientnet_b0_rwightman-3dd342df.pth --output_model efficientnet_b0.onnx
 ```
 
 ## Inference
diff --git a/models/cv/classification/efficientnet_b0/ixrt/config/EFFICIENTNET_B0_CONFIG b/models/cv/classification/efficientnet_b0/ixrt/config/EFFICIENTNET_B0_CONFIG
index f9a0976e246bfb155e473a410d9e922155be9665..f566df019d19bb2eb5b57af63837e42e8cdd7504 100644
--- a/models/cv/classification/efficientnet_b0/ixrt/config/EFFICIENTNET_B0_CONFIG
+++ b/models/cv/classification/efficientnet_b0/ixrt/config/EFFICIENTNET_B0_CONFIG
@@ -18,7 +18,7 @@
 # ORIGINE_MODEL : 原始onnx文件名称
 IMGSIZE=224
 MODEL_NAME=EfficientNet_b0
-ORIGINE_MODEL=efficientnet-b0.onnx
+ORIGINE_MODEL=efficientnet_b0.onnx
 
 # QUANT CONFIG (仅PRECISION为int8时生效)
     # QUANT_OBSERVER : 量化策略，可选 [hist_percentile, percentile, minmax, entropy, ema]
diff --git a/models/cv/classification/efficientnet_b0/ixrt/python/inference.py b/models/cv/classification/efficientnet_b0/ixrt/python/inference.py
index 414546b2aa0f945b47ac968a86ac72c6899d824f..f1155702bcdccadc65da85b589aeb25ec269151c 100644
--- a/models/cv/classification/efficientnet_b0/ixrt/python/inference.py
+++ b/models/cv/classification/efficientnet_b0/ixrt/python/inference.py
@@ -85,6 +85,7 @@ def main(config):
         total_sample = 0
         acc_top1, acc_top5 = 0, 0
 
+        start_time = time.time()
         with tqdm(total= len(dataloader)) as _tqdm:
             for idx, (batch_data, batch_label) in enumerate(dataloader):
                 batch_data = batch_data.numpy().astype(inputs[0]["dtype"])
@@ -106,7 +107,10 @@ def main(config):
                 _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample),
                                     acc_5='{:.4f}'.format(acc_top5/total_sample))
                 _tqdm.update(1)
+        end_time = time.time()
+        end2end_time = end_time - start_time
 
+        print(F"E2E time : {end2end_time:.3f} seconds")
         print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}")
         print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}")
         acc1 = acc_top1/total_sample
diff --git a/models/cv/classification/efficientnet_b0/ixrt/requirements.txt b/models/cv/classification/efficientnet_b0/ixrt/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..46a30ba219c99614c9dea617a334954704f70c91
--- /dev/null
+++ b/models/cv/classification/efficientnet_b0/ixrt/requirements.txt
@@ -0,0 +1,7 @@
+tqdm
+onnx
+onnxsim
+tabulate
+ppq==0.6.6
+protobuf==3.20.3
+pycuda
\ No newline at end of file
diff --git a/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_fp16_accuracy.sh b/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_fp16_accuracy.sh
index a8ca6d11ff45cf22e116e9833448792e2b2c019d..f184e30d2aafe766cedc44c2daf67c12bb39e44b 100644
--- a/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_fp16_accuracy.sh
+++ b/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_fp16_accuracy.sh
@@ -14,7 +14,7 @@
 #    License for the specific language governing permissions and limitations
 #    under the License.
 batchsize=32
-model_path="efficientnet-b0"
+model_path="efficientnet_b0"
 # model_path="resnet18"
 datasets_path=${DATASETS_DIR}
 
diff --git a/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_fp16_performance.sh b/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_fp16_performance.sh
index ca523b2ff17f262c25d1d41c1fbd284d6d59b2c6..458d91367021f7ed980748f559625c8a1c91baff 100644
--- a/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_fp16_performance.sh
+++ b/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_fp16_performance.sh
@@ -14,14 +14,10 @@
 #    License for the specific language governing permissions and limitations
 #    under the License.
 batchsize=32
-model_path="efficientnet-b0"
+model_path="efficientnet_b0"
 # model_path="resnet18"
 datasets_path=${DATASETS_DIR}
 
-# create onnx
-python3 python/export_onnx.py               \
-        --output_model ${model_path}.onnx
-
 # change batchsize
 python3 python/modify_batchsize.py              \
         --batch_size ${batchsize}               \
diff --git a/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_int8_accuracy.sh b/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_int8_accuracy.sh
index 5f1c4827f690b6f42df059b745f24e05f75149fe..82517f705e7ae42da3147e5d9677eecfe145ad2d 100644
--- a/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_int8_accuracy.sh
+++ b/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_int8_accuracy.sh
@@ -14,14 +14,10 @@
 #    License for the specific language governing permissions and limitations
 #    under the License.
 batchsize=32
-model_path="efficientnet-b0"
+model_path="efficientnet_b0"
 # model_path="resnet18"
 datasets_path=${DATASETS_DIR}
 
-# create onnx
-python3 python/export_onnx.py               \
-        --output_model ${model_path}.onnx
-
 # change batchsize
 python3 python/modify_batchsize.py              \
         --batch_size ${batchsize}               \
diff --git a/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_int8_performance.sh b/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_int8_performance.sh
index 9c1e159f8085490c1578b2eddc45f742957d99c1..4a40c03038f747b6bd81c13e321f15b3af1e0577 100644
--- a/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_int8_performance.sh
+++ b/models/cv/classification/efficientnet_b0/ixrt/scripts/infer_efficientnet_b0_int8_performance.sh
@@ -14,14 +14,10 @@
 #    License for the specific language governing permissions and limitations
 #    under the License.
 batchsize=32
-model_path="efficientnet-b0"
+model_path="efficientnet_b0"
 # model_path="resnet18"
 datasets_path=${DATASETS_DIR}
 
-# create onnx
-python3 python/export_onnx.py               \
-        --output_model ${model_path}.onnx
-
 # change batchsize
 python3 python/modify_batchsize.py              \
         --batch_size ${batchsize}               \
diff --git a/models/cv/classification/efficientnet_v2/ixrt/README.md b/models/cv/classification/efficientnet_v2/ixrt/README.md
index 23c83cf58a8d78876a41df134db1af58c9addef4..ee9197497d5d996aaa532cfc0961674b856b37e6 100755
--- a/models/cv/classification/efficientnet_v2/ixrt/README.md
+++ b/models/cv/classification/efficientnet_v2/ixrt/README.md
@@ -15,14 +15,7 @@ yum install -y mesa-libGL
 ## Ubuntu
 apt install -y libgl1-mesa-dev
 
-pip3 install tqdm
-pip3 install onnx
-pip3 install onnxsim
-pip3 install tabulate
-pip3 install timm
-pip3 install ppq
-pip3 install pycuda
-pip3 install protobuf==3.20.0
+pip3 install -r requirements.txt
 ```
 
 ### Download
@@ -35,15 +28,15 @@ Dataset: <https://www.image-net.org/download.php> to download the validation dat
 
 ```bash
 mkdir checkpoints
-git clone https://github.com/huggingface/pytorch-image-models.git && git checkout <timm version tag>
-cp /Path/to/ixrt/export_onnx.py pytorch-image-models/timm/models
-cd pytorch-image-models/timm/models
-rm _builder.py
-mv /Path/ixrt/_builder.py pytorch-image-models/timm/models
+git clone https://github.com/huggingface/pytorch-image-models.git
+cp ./export_onnx.py pytorch-image-models/timm/models
+rm pytorch-image-models/timm/models/_builder.py
+mv ./_builder.py pytorch-image-models/timm/models
 cd pytorch-image-models/timm
 mkdir -p /root/.cache/torch/hub/checkpoints/
 wget -P /root/.cache/torch/hub/checkpoints/ https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/efficientnetv2_t_agc-3620981a.pth
-python3 -m models.export_onnx --output_model ../../checkpoints/efficientnet.onnx
+python3 -m models.export_onnx --output_model ../../checkpoints/efficientnet_v2.onnx
+cd ../../
 ```
 
 ## Inference
@@ -53,7 +46,7 @@ export PROJ_DIR=/Path/to/efficientnet_v2/ixrt
 export DATASETS_DIR=/path/to/imagenet_val/
 export CHECKPOINTS_DIR=./checkpoints
 export RUN_DIR=/Path/to/efficientnet_v2/ixrt
-export CONFIG_DIR=/Path/to/config/EFFICIENTNET_V2T_CONFIG
+export CONFIG_DIR=/Path/to/config/EFFICIENTNET_V2_CONFIG
 export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python
 ```
 
@@ -61,18 +54,18 @@ export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python
 
 ```bash
 # Accuracy
-bash scripts/infer_efficientnet_fp16_accuracy.sh
+bash scripts/infer_efficientnet_v2_fp16_accuracy.sh
 # Performance
-bash scripts/infer_efficientnet_fp16_performance.sh
+bash scripts/infer_efficientnet_v2_fp16_performance.sh
 ```
 
 ### INT8
 
 ```bash
 # Accuracy
-bash scripts/infer_efficientnet_int8_accuracy.sh
+bash scripts/infer_efficientnet_v2_int8_accuracy.sh
 # Performance
-bash scripts/infer_efficientnet_int8_performance.sh
+bash scripts/infer_efficientnet_v2_int8_performance.sh
 ```
 
 ## Results
diff --git a/models/cv/classification/efficientnet_v2/ixrt/config/EFFICIENTNET_V2T_CONFIG b/models/cv/classification/efficientnet_v2/ixrt/config/EFFICIENTNET_V2_CONFIG
similarity index 95%
rename from models/cv/classification/efficientnet_v2/ixrt/config/EFFICIENTNET_V2T_CONFIG
rename to models/cv/classification/efficientnet_v2/ixrt/config/EFFICIENTNET_V2_CONFIG
index b9e40159818f0dec5fbffff0487b049dea9435ae..6979f31db4b15ffd9b3f41d05f20e4394ded8178 100644
--- a/models/cv/classification/efficientnet_v2/ixrt/config/EFFICIENTNET_V2T_CONFIG
+++ b/models/cv/classification/efficientnet_v2/ixrt/config/EFFICIENTNET_V2_CONFIG
@@ -17,8 +17,8 @@
 # MODEL_NAME : 生成onnx/engine的basename
 # ORIGINE_MODEL : 原始onnx文件名称
 IMGSIZE=288
-MODEL_NAME=EfficientNetv2_t
-ORIGINE_MODEL=efficientnet.onnx
+MODEL_NAME=efficientnet_v2
+ORIGINE_MODEL=efficientnet_v2.onnx
 
 # QUANT CONFIG (仅PRECISION为int8时生效)
     # QUANT_OBSERVER : 量化策略，可选 [hist_percentile, percentile, minmax, entropy, ema]
diff --git a/models/cv/classification/efficientnet_v2/ixrt/inference.py b/models/cv/classification/efficientnet_v2/ixrt/inference.py
index 62ec18b30cd51167fb8d7f2babc01430511ead3f..fcca27a3a2426d8601100a6b6786e94265799d9f 100644
--- a/models/cv/classification/efficientnet_v2/ixrt/inference.py
+++ b/models/cv/classification/efficientnet_v2/ixrt/inference.py
@@ -85,6 +85,7 @@ def main(config):
         total_sample = 0
         acc_top1, acc_top5 = 0, 0
 
+        start_time = time.time()
         with tqdm(total= len(dataloader)) as _tqdm:
             for idx, (batch_data, batch_label) in enumerate(dataloader):
                 batch_data = batch_data.numpy().astype(inputs[0]["dtype"])
@@ -106,7 +107,10 @@ def main(config):
                 _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample),
                                     acc_5='{:.4f}'.format(acc_top5/total_sample))
                 _tqdm.update(1)
+        end_time = time.time()
+        end2end_time = end_time - start_time
 
+        print(F"E2E time : {end2end_time:.3f} seconds")
         print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}")
         print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}")
         acc1 = acc_top1/total_sample
diff --git a/models/cv/classification/efficientnet_v2/ixrt/requirements.txt b/models/cv/classification/efficientnet_v2/ixrt/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..09e8dab9fbba81751d8862b1de0cffdbd1c1059b
--- /dev/null
+++ b/models/cv/classification/efficientnet_v2/ixrt/requirements.txt
@@ -0,0 +1,8 @@
+tqdm
+onnx
+onnxsim
+tabulate
+timm==1.0.10
+ppq
+pycuda
+protobuf==3.20.0
\ No newline at end of file
diff --git a/models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_fp16_accuracy.sh b/models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_v2_fp16_accuracy.sh
old mode 100755
new mode 100644
similarity index 100%
rename from models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_fp16_accuracy.sh
rename to models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_v2_fp16_accuracy.sh
diff --git a/models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_fp16_performance.sh b/models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_v2_fp16_performance.sh
old mode 100755
new mode 100644
similarity index 100%
rename from models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_fp16_performance.sh
rename to models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_v2_fp16_performance.sh
diff --git a/models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_int8_accuracy.sh b/models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_v2_int8_accuracy.sh
old mode 100755
new mode 100644
similarity index 100%
rename from models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_int8_accuracy.sh
rename to models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_v2_int8_accuracy.sh
diff --git a/models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_int8_performance.sh b/models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_v2_int8_performance.sh
old mode 100755
new mode 100644
similarity index 100%
rename from models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_int8_performance.sh
rename to models/cv/classification/efficientnet_v2/ixrt/scripts/infer_efficientnet_v2_int8_performance.sh
diff --git a/models/cv/classification/googlenet/ixrt/README.md b/models/cv/classification/googlenet/ixrt/README.md
index 001319b607136a885c3fd6b6394d0a4d2bbffd81..fa96b4759f7c863ba0c6d3a59e96c1629f59c690 100644
--- a/models/cv/classification/googlenet/ixrt/README.md
+++ b/models/cv/classification/googlenet/ixrt/README.md
@@ -15,10 +15,7 @@ yum install -y mesa-libGL
 ## Ubuntu
 apt install -y libgl1-mesa-dev
 
-pip3 install tqdm
-pip3 install onnx
-pip3 install onnxsim
-pip3 install tabulate
+pip3 install -r requirements.txt
 ```
 
 ### Download
diff --git a/models/cv/classification/googlenet/ixrt/inference.py b/models/cv/classification/googlenet/ixrt/inference.py
index 2c9dcb3f9cc5b9a26903651a31fafa16d8f0db31..50aafd4fd5ef9664203cdcbdfbdb577edca933c4 100644
--- a/models/cv/classification/googlenet/ixrt/inference.py
+++ b/models/cv/classification/googlenet/ixrt/inference.py
@@ -83,6 +83,7 @@ def main(config):
         total_sample = 0
         acc_top1, acc_top5 = 0, 0
 
+        start_time = time.time()
         with tqdm(total= len(dataloader)) as _tqdm:
             for idx, (batch_data, batch_label) in enumerate(dataloader):
                 batch_data = batch_data.numpy().astype(inputs[0]["dtype"])
@@ -104,7 +105,10 @@ def main(config):
                 _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample),
                                     acc_5='{:.4f}'.format(acc_top5/total_sample))
                 _tqdm.update(1)
+        end_time = time.time()
+        end2end_time = end_time - start_time
 
+        print(F"E2E time : {end2end_time:.3f} seconds")
         print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}")
         print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}")
         acc1 = acc_top1/total_sample
diff --git a/models/cv/classification/googlenet/ixrt/requirements.txt b/models/cv/classification/googlenet/ixrt/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e1eda59c3910ca96c73128bab86d534dbd55bbae
--- /dev/null
+++ b/models/cv/classification/googlenet/ixrt/requirements.txt
@@ -0,0 +1,4 @@
+tqdm
+onnx
+onnxsim
+tabulate
\ No newline at end of file
diff --git a/models/cv/classification/inception_v3/ixrt/README.md b/models/cv/classification/inception_v3/ixrt/README.md
index 523fa268d3fd4d4272f27a6c8697c2bb78c3a09b..4fbbe94f695cb00a1a467ad39036a620ec4b93ed 100755
--- a/models/cv/classification/inception_v3/ixrt/README.md
+++ b/models/cv/classification/inception_v3/ixrt/README.md
@@ -15,13 +15,7 @@ yum install -y mesa-libGL
 ## Ubuntu
 apt install -y libgl1-mesa-dev
 
-pip3 install pycuda
-pip3 install tqdm
-pip3 install onnx
-pip3 install onnxsim
-pip3 install tabulate
-pip3 install ppq
-pip3 install protobuf==3.20.0
+pip3 install -r requirements.txt
 ```
 
 ### Download
@@ -35,7 +29,7 @@ Dataset: <https://www.image-net.org/download.php> to download the validation dat
 ```bash
 
 mkdir checkpoints
-python3 export.py --weight inception_v3_google-0cc3c7bd.pth --output checkpoints/inception-v3.onnx
+python3 export.py --weight inception_v3_google-0cc3c7bd.pth --output checkpoints/inception_v3.onnx
 ```
 
 ## Inference
diff --git a/models/cv/classification/inception_v3/ixrt/config/INCEPTION_V3_CONFIG b/models/cv/classification/inception_v3/ixrt/config/INCEPTION_V3_CONFIG
index f5223eaf824040a2ecad2a0759925132aa82bb0d..041b09103ee4fec17959afb18887ee595e7b74b3 100644
--- a/models/cv/classification/inception_v3/ixrt/config/INCEPTION_V3_CONFIG
+++ b/models/cv/classification/inception_v3/ixrt/config/INCEPTION_V3_CONFIG
@@ -18,7 +18,7 @@
 # ORIGINE_MODEL : 原始onnx文件名称
 IMGSIZE=224
 MODEL_NAME=Inception_v3
-ORIGINE_MODEL=inception-v3.onnx
+ORIGINE_MODEL=inception_v3.onnx
 
 # QUANT CONFIG (仅PRECISION为int8时生效)
     # QUANT_OBSERVER : 量化策略，可选 [hist_percentile, percentile, minmax, entropy, ema]
diff --git a/models/cv/classification/inception_v3/ixrt/inference.py b/models/cv/classification/inception_v3/ixrt/inference.py
index 62ec18b30cd51167fb8d7f2babc01430511ead3f..fcca27a3a2426d8601100a6b6786e94265799d9f 100644
--- a/models/cv/classification/inception_v3/ixrt/inference.py
+++ b/models/cv/classification/inception_v3/ixrt/inference.py
@@ -85,6 +85,7 @@ def main(config):
         total_sample = 0
         acc_top1, acc_top5 = 0, 0
 
+        start_time = time.time()
         with tqdm(total= len(dataloader)) as _tqdm:
             for idx, (batch_data, batch_label) in enumerate(dataloader):
                 batch_data = batch_data.numpy().astype(inputs[0]["dtype"])
@@ -106,7 +107,10 @@ def main(config):
                 _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample),
                                     acc_5='{:.4f}'.format(acc_top5/total_sample))
                 _tqdm.update(1)
+        end_time = time.time()
+        end2end_time = end_time - start_time
 
+        print(F"E2E time : {end2end_time:.3f} seconds")
         print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}")
         print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}")
         acc1 = acc_top1/total_sample
diff --git a/models/cv/classification/inception_v3/ixrt/requirements.txt b/models/cv/classification/inception_v3/ixrt/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..bb2683ddc5fb6d26debebe20d8dbd0b5a3c6c3f1
--- /dev/null
+++ b/models/cv/classification/inception_v3/ixrt/requirements.txt
@@ -0,0 +1,7 @@
+pycuda
+tqdm
+onnx
+onnxsim
+tabulate
+ppq
+protobuf==3.20.0
\ No newline at end of file
diff --git a/models/cv/classification/mobilenet_v2/ixrt/README.md b/models/cv/classification/mobilenet_v2/ixrt/README.md
index d3a375f8b5a38da49481c3adf23195027b32ae68..65e27ec41ebd829ac074c315227a68a3d5b463a1 100644
--- a/models/cv/classification/mobilenet_v2/ixrt/README.md
+++ b/models/cv/classification/mobilenet_v2/ixrt/README.md
@@ -9,23 +9,34 @@ The MobileNetV2 architecture is based on an inverted residual structure where th
 ### Install
 
 ```bash
-pip3 install tqdm
-pip3 install onnxsim
-pip3 install opencv-python
-pip3 install ppq
-pip3 install protobuf==3.20.0
+pip3 install -r requirements.txt
 ```
 
 ### Download
 
-Download the [imagenet](https://www.image-net.org/download.php) validation dataset, and place in `${PROJ_ROOT}/data/datasets`;
+Pretrained model: <https://download.pytorch.org/models/mobilenet_v2-b0353104.pth>
+
+Download the [imagenet](https://www.image-net.org/download.php) to download the validation dataset.
+
+### Model Conversion
+
+```bash
+mkdir checkpoints
+python3 python/export_onnx.py --origin_model /path/to/mobilenet_v2-b0353104 --output_model checkpoints/mobilenet_v2.onnx
+```
 
 ## Inference
 
+```bash
+export PROJ_DIR=./
+export DATASETS_DIR=/path/to/imagenet_val/
+export CHECKPOINTS_DIR=./checkpoints
+export RUN_DIR=./
+```
+
 ### FP16
 
 ```bash
-cd python/
 # Test ACC
 bash script/infer_mobilenetv2_fp16_accuracy.sh
 # Test FPS
diff --git a/models/cv/classification/mobilenet_v2/ixrt/python/export_onnx.py b/models/cv/classification/mobilenet_v2/ixrt/python/export_onnx.py
index 8351ffc8c89820b109aa0e09a0bc43104017fb29..4881a4c1793bf2da5ffbe86240f145b3387bd984 100644
--- a/models/cv/classification/mobilenet_v2/ixrt/python/export_onnx.py
+++ b/models/cv/classification/mobilenet_v2/ixrt/python/export_onnx.py
@@ -20,13 +20,15 @@ import argparse
 
 def parse_args():
     parser = argparse.ArgumentParser()
+    parser.add_argument("--origin_model", type=str)
     parser.add_argument("--output_model", type=str)
     args = parser.parse_args()
     return args
 
 
 args = parse_args()
-model = models.mobilenet_v2(pretrained=True)
+model = models.mobilenet_v2()
+model.load_state_dict(torch.load(args.origin_model))
 model.cuda()
 model.eval()
 inputx = torch.randn(1, 3, 224, 224, device='cuda')
@@ -42,3 +44,4 @@ torch.onnx.export(model,
                   input_names = ['input'],
                   output_names = ['output'],)
 print(f"Convert onnx model in {export_onnx_file}")
+exit()
diff --git a/models/cv/classification/mobilenet_v2/ixrt/requirements.txt b/models/cv/classification/mobilenet_v2/ixrt/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..a6b325a766ce064d35b417190ddff6e23f1efe50
--- /dev/null
+++ b/models/cv/classification/mobilenet_v2/ixrt/requirements.txt
@@ -0,0 +1,5 @@
+tqdm
+onnxsim
+opencv-python
+ppq
+protobuf==3.20.0
\ No newline at end of file
diff --git a/models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_fp16_accuracy.sh b/models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_fp16_accuracy.sh
similarity index 80%
rename from models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_fp16_accuracy.sh
rename to models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_fp16_accuracy.sh
index 93c3cda41bb1467bd020b127e39fdb4cc5a9d905..f3e4828de462dc6da18c16408d58ba56b679fc72 100644
--- a/models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_fp16_accuracy.sh
+++ b/models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_fp16_accuracy.sh
@@ -44,18 +44,18 @@ do
     esac
 done
 
-RUN_DIR=$(cd $(dirname $0); cd ../; pwd)
-PROJ_DIR=$(cd $(dirname $0); cd ../../../../../../../; pwd)
-DATASETS_DIR="${PROJ_DIR}/data/datasets/imagenet_val"
-CHECKPOINTS_DIR="${PROJ_DIR}/data/checkpoints/mobilenetv2"
+RUN_DIR=${RUN_DIR}
+PROJ_DIR=${PROJ_DIR}
+DATASETS_DIR=${DATASETS_DIR}
+CHECKPOINTS_DIR=${CHECKPOINTS_DIR}
 
 if [ ! -d $CHECKPOINTS_DIR ]; then
     mkdir -p $CHECKPOINTS_DIR
 fi
 
 
-MODEL_NAME="mobilenetv2"
-ORIGINE_MODEL="${CHECKPOINTS_DIR}/raw_mobilenetv2.onnx"
+MODEL_NAME="mobilenet_v2"
+ORIGINE_MODEL="${CHECKPOINTS_DIR}/mobilenet_v2.onnx"
 
 echo CHECKPOINTS_DIR : ${CHECKPOINTS_DIR}
 echo DATASETS_DIR : ${DATASETS_DIR}
@@ -69,14 +69,6 @@ step=0
 # Export Onnx Model
 let step++
 echo;
-echo [STEP ${step}] : Export Onnx Model
-if [ -f ${ORIGINE_MODEL} ];then
-    echo "  "Onnx Model, ${ORIGINE_MODEL} has been existed
-else
-    python3 ${RUN_DIR}/export_onnx.py \
-        --output_model $ORIGINE_MODEL
-    echo "  "Generate ${ORIGINE_MODEL}
-fi
 
 SIM_MODEL=${CHECKPOINTS_DIR}/${MODEL_NAME}_sim.onnx
 # Simplify Model
@@ -86,7 +78,7 @@ echo [STEP ${step}] : Simplify Model
 if [ -f ${SIM_MODEL} ];then
     echo "  "Simplify Model, ${SIM_MODEL} has been existed
 else
-    python3 ${RUN_DIR}/simplify_model.py     \
+    python3 ${RUN_DIR}python/simplify_model.py     \
         --origin_model $ORIGINE_MODEL        \
         --output_model ${SIM_MODEL}
     echo "  "Generate ${SIM_MODEL}
@@ -100,7 +92,7 @@ FINAL_MODEL=${CHECKPOINTS_DIR}/${MODEL_NAME}_${BSZ}.onnx
 if [ -f $FINAL_MODEL ];then
     echo "  "Change Batchsize Skip, $FINAL_MODEL has been existed
 else
-    python3 ${RUN_DIR}/modify_batchsize.py  \
+    python3 ${RUN_DIR}python/modify_batchsize.py  \
         --batch_size ${BSZ}                 \
         --origin_model ${SIM_MODEL}         \
         --output_model ${FINAL_MODEL}
@@ -115,7 +107,7 @@ ENGINE_FILE=${CHECKPOINTS_DIR}/${MODEL_NAME}_${PRECISION}_bs${BSZ}.engine
 if [ -f $ENGINE_FILE ];then
     echo "  "Build Engine Skip, $ENGINE_FILE has been existed
 else
-    python3 ${RUN_DIR}/build_engine.py          \
+    python3 ${RUN_DIR}python/build_engine.py          \
         --precision ${PRECISION}                \
         --model ${FINAL_MODEL}                  \
         --engine ${ENGINE_FILE}
@@ -126,7 +118,7 @@ fi
 let step++
 echo;
 echo [STEP ${step}] : Inference
-python3 ${RUN_DIR}/inference.py     \
+python3 ${RUN_DIR}python/inference.py     \
     --engine_file=${ENGINE_FILE}    \
     --datasets_dir=${DATASETS_DIR}  \
     --imgsz=${IMGSIZE}              \
diff --git a/models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_fp16_performance.sh b/models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_fp16_performance.sh
similarity index 80%
rename from models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_fp16_performance.sh
rename to models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_fp16_performance.sh
index 1042fb91f244ce59509baa56381f91ae609369b8..1057dadb582ac362146e6dc6fd72654a556f371d 100644
--- a/models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_fp16_performance.sh
+++ b/models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_fp16_performance.sh
@@ -44,18 +44,18 @@ do
     esac
 done
 
-RUN_DIR=$(cd $(dirname $0); cd ../; pwd)
-PROJ_DIR=$(cd $(dirname $0); cd ../../../../../../../; pwd)
-DATASETS_DIR="${PROJ_DIR}/data/datasets/imagenet_val"
-CHECKPOINTS_DIR="${PROJ_DIR}/data/checkpoints/mobilenetv2"
+RUN_DIR=${RUN_DIR}
+PROJ_DIR=${PROJ_DIR}
+DATASETS_DIR=${DATASETS_DIR}
+CHECKPOINTS_DIR=${CHECKPOINTS_DIR}
 
 if [ ! -d $CHECKPOINTS_DIR ]; then
     mkdir -p $CHECKPOINTS_DIR
 fi
 
 
-MODEL_NAME="mobilenetv2"
-ORIGINE_MODEL="${CHECKPOINTS_DIR}/raw_mobilenetv2.onnx"
+MODEL_NAME="mobilenet_v2"
+ORIGINE_MODEL="${CHECKPOINTS_DIR}/mobilenet_v2.onnx"
 
 echo CHECKPOINTS_DIR : ${CHECKPOINTS_DIR}
 echo DATASETS_DIR : ${DATASETS_DIR}
@@ -69,14 +69,6 @@ step=0
 # Export Onnx Model
 let step++
 echo;
-echo [STEP ${step}] : Export Onnx Model
-if [ -f ${ORIGINE_MODEL} ];then
-    echo "  "Onnx Model, ${ORIGINE_MODEL} has been existed
-else
-    python3 ${RUN_DIR}/export_onnx.py \
-        --output_model $ORIGINE_MODEL
-    echo "  "Generate ${ORIGINE_MODEL}
-fi
 
 SIM_MODEL=${CHECKPOINTS_DIR}/${MODEL_NAME}_sim.onnx
 # Simplify Model
@@ -86,7 +78,7 @@ echo [STEP ${step}] : Simplify Model
 if [ -f ${SIM_MODEL} ];then
     echo "  "Simplify Model, ${SIM_MODEL} has been existed
 else
-    python3 ${RUN_DIR}/simplify_model.py  \
+    python3 ${RUN_DIR}python/simplify_model.py  \
         --origin_model $ORIGINE_MODEL     \
         --output_model ${SIM_MODEL}
     echo "  "Generate ${SIM_MODEL}
@@ -100,7 +92,7 @@ FINAL_MODEL=${CHECKPOINTS_DIR}/${MODEL_NAME}_${BSZ}.onnx
 if [ -f $FINAL_MODEL ];then
     echo "  "Change Batchsize Skip, $FINAL_MODEL has been existed
 else
-    python3 ${RUN_DIR}/modify_batchsize.py  \
+    python3 ${RUN_DIR}python/modify_batchsize.py  \
         --batch_size ${BSZ}                 \
         --origin_model ${SIM_MODEL}         \
         --output_model ${FINAL_MODEL}
@@ -115,7 +107,7 @@ ENGINE_FILE=${CHECKPOINTS_DIR}/${MODEL_NAME}_${PRECISION}_bs${BSZ}.engine
 if [ -f $ENGINE_FILE ];then
     echo "  "Build Engine Skip, $ENGINE_FILE has been existed
 else
-    python3 ${RUN_DIR}/build_engine.py          \
+    python3 ${RUN_DIR}python/build_engine.py          \
         --precision ${PRECISION}                \
         --model ${FINAL_MODEL}                  \
         --engine ${ENGINE_FILE}
@@ -126,7 +118,7 @@ fi
 let step++
 echo;
 echo [STEP ${step}] : Inference
-python3 ${RUN_DIR}/inference.py     \
+python3 ${RUN_DIR}python/inference.py     \
     --engine_file=${ENGINE_FILE}    \
     --datasets_dir=${DATASETS_DIR}  \
     --imgsz=${IMGSIZE}              \
diff --git a/models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_int8_accuracy.sh b/models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_int8_accuracy.sh
similarity index 82%
rename from models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_int8_accuracy.sh
rename to models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_int8_accuracy.sh
index 7c32c7892a7867574380ee53311637cc15f4ce61..95653d9ff43497fcb5d994f51218588963733b0f 100644
--- a/models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_int8_accuracy.sh
+++ b/models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_int8_accuracy.sh
@@ -44,18 +44,18 @@ do
     esac
 done
 
-RUN_DIR=$(cd $(dirname $0); cd ../; pwd)
-PROJ_DIR=$(cd $(dirname $0); cd ../../../../../../../; pwd)
-DATASETS_DIR="${PROJ_DIR}/data/datasets/imagenet_val"
-CHECKPOINTS_DIR="${PROJ_DIR}/data/checkpoints/mobilenetv2"
+RUN_DIR=${RUN_DIR}
+PROJ_DIR=${PROJ_DIR}
+DATASETS_DIR=${DATASETS_DIR}
+CHECKPOINTS_DIR=${CHECKPOINTS_DIR}
 
 if [ ! -d $CHECKPOINTS_DIR ]; then
     mkdir -p $CHECKPOINTS_DIR
 fi
 
 
-MODEL_NAME="mobilenetv2"
-ORIGINE_MODEL="${CHECKPOINTS_DIR}/raw_mobilenetv2.onnx"
+MODEL_NAME="mobilenet_v2"
+ORIGINE_MODEL="${CHECKPOINTS_DIR}/mobilenet_v2.onnx"
 
 echo CHECKPOINTS_DIR : ${CHECKPOINTS_DIR}
 echo DATASETS_DIR : ${DATASETS_DIR}
@@ -69,14 +69,6 @@ step=0
 # Export Onnx Model
 let step++
 echo;
-echo [STEP ${step}] : Export Onnx Model
-if [ -f ${ORIGINE_MODEL} ];then
-    echo "  "Onnx Model, ${ORIGINE_MODEL} has been existed
-else
-    python3 ${RUN_DIR}/export_onnx.py \
-        --output_model $ORIGINE_MODEL
-    echo "  "Generate ${ORIGINE_MODEL}
-fi
 
 SIM_MODEL=${CHECKPOINTS_DIR}/${MODEL_NAME}_sim.onnx
 # Simplify Model
@@ -86,7 +78,7 @@ echo [STEP ${step}] : Simplify Model
 if [ -f ${SIM_MODEL} ];then
     echo "  "Simplify Model, ${SIM_MODEL} has been existed
 else
-    python3 ${RUN_DIR}/simplify_model.py  \
+    python3 ${RUN_DIR}python/simplify_model.py  \
         --origin_model $ORIGINE_MODEL     \
         --output_model ${SIM_MODEL}
     echo "  "Generate ${SIM_MODEL}
@@ -100,7 +92,7 @@ FINAL_MODEL=${CHECKPOINTS_DIR}/${MODEL_NAME}_${BSZ}.onnx
 if [ -f $FINAL_MODEL ];then
     echo "  "Change Batchsize Skip, $FINAL_MODEL has been existed
 else
-    python3 ${RUN_DIR}/modify_batchsize.py  \
+    python3 ${RUN_DIR}python/modify_batchsize.py  \
         --batch_size ${BSZ}                 \
         --origin_model ${SIM_MODEL}         \
         --output_model ${FINAL_MODEL}
@@ -116,7 +108,7 @@ QUANTIZED_Q_PARAMS_JSON=${CHECKPOINTS_DIR}/quant_cfg.json
 if [ -f $QUANTIZED_MODEL ];then
     echo "  "Quantized Model Skip By PPQ, $QUANTIZED_MODEL has been existed
 else
-    python3 ${RUN_DIR}/quant.py           \
+    python3 ${RUN_DIR}python/quant.py           \
         --model_name ${MODEL_NAME}        \
         --model ${FINAL_MODEL}            \
         --dataset_dir ${DATASETS_DIR}     \
@@ -132,7 +124,7 @@ ENGINE_FILE=${CHECKPOINTS_DIR}/${MODEL_NAME}_${PRECISION}_bs${BSZ}.engine
 if [ -f $ENGINE_FILE ];then
     echo "  "Build Engine Skip, $ENGINE_FILE has been existed
 else
-    python3 ${RUN_DIR}/build_engine_by_write_qparams.py          \
+    python3 ${RUN_DIR}python/build_engine_by_write_qparams.py          \
         --onnx ${QUANTIZED_MODEL}                                \
         --qparam_json ${QUANTIZED_Q_PARAMS_JSON}                 \
         --engine ${ENGINE_FILE}
@@ -143,7 +135,7 @@ fi
 let step++
 echo;
 echo [STEP ${step}] : Inference
-python3 ${RUN_DIR}/inference.py     \
+python3 ${RUN_DIR}python/inference.py     \
     --engine_file=${ENGINE_FILE}    \
     --datasets_dir=${DATASETS_DIR}  \
     --imgsz=${IMGSIZE}              \
diff --git a/models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_int8_performance.sh b/models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_int8_performance.sh
similarity index 82%
rename from models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_int8_performance.sh
rename to models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_int8_performance.sh
index 196a5090411f3427cdccad1b39eabd8af6206379..739f62cbed80281cca4f1ab811468d59bb200c0f 100644
--- a/models/cv/classification/mobilenet_v2/ixrt/python/script/infer_mobilenetv2_int8_performance.sh
+++ b/models/cv/classification/mobilenet_v2/ixrt/script/infer_mobilenetv2_int8_performance.sh
@@ -44,18 +44,18 @@ do
     esac
 done
 
-RUN_DIR=$(cd $(dirname $0); cd ../; pwd)
-PROJ_DIR=$(cd $(dirname $0); cd ../../../../../../../; pwd)
-DATASETS_DIR="${PROJ_DIR}/data/datasets/imagenet_val"
-CHECKPOINTS_DIR="${PROJ_DIR}/data/checkpoints/mobilenetv2"
+RUN_DIR=${RUN_DIR}
+PROJ_DIR=${PROJ_DIR}
+DATASETS_DIR=${DATASETS_DIR}
+CHECKPOINTS_DIR=${CHECKPOINTS_DIR}
 
 if [ ! -d $CHECKPOINTS_DIR ]; then
     mkdir -p $CHECKPOINTS_DIR
 fi
 
 
-MODEL_NAME="mobilenetv2"
-ORIGINE_MODEL="${CHECKPOINTS_DIR}/raw_mobilenetv2.onnx"
+MODEL_NAME="mobilenet_v2"
+ORIGINE_MODEL="${CHECKPOINTS_DIR}/mobilenet_v2.onnx"
 
 echo CHECKPOINTS_DIR : ${CHECKPOINTS_DIR}
 echo DATASETS_DIR : ${DATASETS_DIR}
@@ -69,14 +69,6 @@ step=0
 # Export Onnx Model
 let step++
 echo;
-echo [STEP ${step}] : Export Onnx Model
-if [ -f ${ORIGINE_MODEL} ];then
-    echo "  "Onnx Model, ${ORIGINE_MODEL} has been existed
-else
-    python3 ${RUN_DIR}/export_onnx.py \
-        --output_model $ORIGINE_MODEL
-    echo "  "Generate ${ORIGINE_MODEL}
-fi
 
 SIM_MODEL=${CHECKPOINTS_DIR}/${MODEL_NAME}_sim.onnx
 # Simplify Model
@@ -86,7 +78,7 @@ echo [STEP ${step}] : Simplify Model
 if [ -f ${SIM_MODEL} ];then
     echo "  "Simplify Model, ${SIM_MODEL} has been existed
 else
-    python3 ${RUN_DIR}/simplify_model.py  \
+    python3 ${RUN_DIR}python/simplify_model.py  \
         --origin_model $ORIGINE_MODEL     \
         --output_model ${SIM_MODEL}
     echo "  "Generate ${SIM_MODEL}
@@ -100,7 +92,7 @@ FINAL_MODEL=${CHECKPOINTS_DIR}/${MODEL_NAME}_${BSZ}.onnx
 if [ -f $FINAL_MODEL ];then
     echo "  "Change Batchsize Skip, $FINAL_MODEL has been existed
 else
-    python3 ${RUN_DIR}/modify_batchsize.py  \
+    python3 ${RUN_DIR}python/modify_batchsize.py  \
         --batch_size ${BSZ}                 \
         --origin_model ${SIM_MODEL}         \
         --output_model ${FINAL_MODEL}
@@ -116,7 +108,7 @@ QUANTIZED_Q_PARAMS_JSON=${CHECKPOINTS_DIR}/quant_cfg.json
 if [ -f $QUANTIZED_MODEL ];then
     echo "  "Quantized Model Skip By PPQ, $QUANTIZED_MODEL has been existed
 else
-    python3 ${RUN_DIR}/quant.py           \
+    python3 ${RUN_DIR}python/quant.py           \
         --model_name ${MODEL_NAME}        \
         --model ${FINAL_MODEL}            \
         --dataset_dir ${DATASETS_DIR}     \
@@ -132,7 +124,7 @@ ENGINE_FILE=${CHECKPOINTS_DIR}/${MODEL_NAME}_${PRECISION}_bs${BSZ}.engine
 if [ -f $ENGINE_FILE ];then
     echo "  "Build Engine Skip, $ENGINE_FILE has been existed
 else
-    python3 ${RUN_DIR}/build_engine_by_write_qparams.py          \
+    python3 ${RUN_DIR}python/build_engine_by_write_qparams.py          \
         --onnx ${QUANTIZED_MODEL}                                \
         --qparam_json ${QUANTIZED_Q_PARAMS_JSON}                 \
         --engine ${ENGINE_FILE}
@@ -143,7 +135,7 @@ fi
 let step++
 echo;
 echo [STEP ${step}] : Inference
-python3 ${RUN_DIR}/inference.py     \
+python3 ${RUN_DIR}python/inference.py     \
     --engine_file=${ENGINE_FILE}    \
     --datasets_dir=${DATASETS_DIR}  \
     --imgsz=${IMGSIZE}              \
diff --git a/models/cv/classification/mobilenet_v3/ixrt/README.md b/models/cv/classification/mobilenet_v3/ixrt/README.md
index b1ef8f3dd97b24c8ea0ed9b426434446a2fdf68d..1ff5e158f9764e81c2977df60ef76b1bf6432c42 100644
--- a/models/cv/classification/mobilenet_v3/ixrt/README.md
+++ b/models/cv/classification/mobilenet_v3/ixrt/README.md
@@ -15,10 +15,7 @@ yum install -y mesa-libGL
 ## Ubuntu
 apt install -y libgl1-mesa-dev
 
-pip3 install tqdm
-pip3 install onnx
-pip3 install onnxsim
-pip3 install tabulate
+pip3 install -r requirements.txt
 ```
 
 ### Download
@@ -31,7 +28,7 @@ Dataset: <https://www.image-net.org/download.php> to download the validation dat
 
 ```bash
 mkdir checkpoints
-python3 export_onnx.py --origin_model /path/to/mobilenet_v3_small-047dcff4.pth --output_model checkpoints/mobilenetv3.onnx
+python3 export_onnx.py --origin_model /path/to/mobilenet_v3_small-047dcff4.pth --output_model checkpoints/mobilenet_v3.onnx
 ```
 
 ## Inference
@@ -41,16 +38,16 @@ export PROJ_DIR=./
 export DATASETS_DIR=/path/to/imagenet_val/
 export CHECKPOINTS_DIR=./checkpoints
 export RUN_DIR=./
-export CONFIG_DIR=config/MOBILENETV3_CONFIG
+export CONFIG_DIR=config/MOBILENET_V3_CONFIG
 ```
 
 ### FP16
 
 ```bash
 # Accuracy
-bash scripts/infer_mobilenetv3_fp16_accuracy.sh
+bash scripts/infer_mobilenet_v3_fp16_accuracy.sh
 # Performance
-bash scripts/infer_mobilenetv3_fp16_performance.sh
+bash scripts/infer_mobilenet_v3_fp16_performance.sh
 ```
 
 ## Results
diff --git a/models/cv/classification/mobilenet_v3/ixrt/config/MOBILENETV3_CONFIG b/models/cv/classification/mobilenet_v3/ixrt/config/MOBILENET_V3_CONFIG
similarity index 97%
rename from models/cv/classification/mobilenet_v3/ixrt/config/MOBILENETV3_CONFIG
rename to models/cv/classification/mobilenet_v3/ixrt/config/MOBILENET_V3_CONFIG
index cd97156638c6e3030e5420cc8355972729b03bf7..aef74a6c84b70973cd498fbd4c4e97f9b99ab7a4 100644
--- a/models/cv/classification/mobilenet_v3/ixrt/config/MOBILENETV3_CONFIG
+++ b/models/cv/classification/mobilenet_v3/ixrt/config/MOBILENET_V3_CONFIG
@@ -17,7 +17,7 @@
 # ORIGINE_MODEL : 原始onnx文件名称
 IMGSIZE=224
 MODEL_NAME=MobileNet_v3
-ORIGINE_MODEL=mobilenetv3.onnx
+ORIGINE_MODEL=mobilenet_v3.onnx
 
 # QUANT CONFIG (仅PRECISION为int8时生效)
     # QUANT_OBSERVER : 量化策略，可选 [hist_percentile, percentile, minmax, entropy, ema]
diff --git a/models/cv/classification/mobilenet_v3/ixrt/inference.py b/models/cv/classification/mobilenet_v3/ixrt/inference.py
index 2c9dcb3f9cc5b9a26903651a31fafa16d8f0db31..50aafd4fd5ef9664203cdcbdfbdb577edca933c4 100644
--- a/models/cv/classification/mobilenet_v3/ixrt/inference.py
+++ b/models/cv/classification/mobilenet_v3/ixrt/inference.py
@@ -83,6 +83,7 @@ def main(config):
         total_sample = 0
         acc_top1, acc_top5 = 0, 0
 
+        start_time = time.time()
         with tqdm(total= len(dataloader)) as _tqdm:
             for idx, (batch_data, batch_label) in enumerate(dataloader):
                 batch_data = batch_data.numpy().astype(inputs[0]["dtype"])
@@ -104,7 +105,10 @@ def main(config):
                 _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample),
                                     acc_5='{:.4f}'.format(acc_top5/total_sample))
                 _tqdm.update(1)
+        end_time = time.time()
+        end2end_time = end_time - start_time
 
+        print(F"E2E time : {end2end_time:.3f} seconds")
         print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}")
         print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}")
         acc1 = acc_top1/total_sample
diff --git a/models/cv/classification/mobilenet_v3/ixrt/requirements.txt b/models/cv/classification/mobilenet_v3/ixrt/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e1eda59c3910ca96c73128bab86d534dbd55bbae
--- /dev/null
+++ b/models/cv/classification/mobilenet_v3/ixrt/requirements.txt
@@ -0,0 +1,4 @@
+tqdm
+onnx
+onnxsim
+tabulate
\ No newline at end of file
diff --git a/models/cv/classification/mobilenet_v3/ixrt/scripts/infer_mobilenetv3_fp16_accuracy.sh b/models/cv/classification/mobilenet_v3/ixrt/scripts/infer_mobilenet_v3_fp16_accuracy.sh
similarity index 100%
rename from models/cv/classification/mobilenet_v3/ixrt/scripts/infer_mobilenetv3_fp16_accuracy.sh
rename to models/cv/classification/mobilenet_v3/ixrt/scripts/infer_mobilenet_v3_fp16_accuracy.sh
diff --git a/models/cv/classification/mobilenet_v3/ixrt/scripts/infer_mobilenetv3_fp16_performance.sh b/models/cv/classification/mobilenet_v3/ixrt/scripts/infer_mobilenet_v3_fp16_performance.sh
similarity index 100%
rename from models/cv/classification/mobilenet_v3/ixrt/scripts/infer_mobilenetv3_fp16_performance.sh
rename to models/cv/classification/mobilenet_v3/ixrt/scripts/infer_mobilenet_v3_fp16_performance.sh
diff --git a/models/cv/classification/res2net50/ixrt/README.md b/models/cv/classification/res2net50/ixrt/README.md
index 9c381613818d34de041ad5725b69e6291623c734..1ec7a25194062661cc526a773ca7755aac493b66 100644
--- a/models/cv/classification/res2net50/ixrt/README.md
+++ b/models/cv/classification/res2net50/ixrt/README.md
@@ -15,21 +15,20 @@ yum install -y mesa-libGL
 ## Ubuntu
 apt install -y libgl1-mesa-dev
 
-pip3 install tqdm
-pip3 install onnx
-pip3 install onnxsim
-pip3 install tabulate
+pip3 install -r requirements.txt
 ```
 
 ### Download
 
+Pretrained model: <https://shanghuagao.oss-cn-beijing.aliyuncs.com/res2net/res2net50_14w_8s-6527dddc.pth>
+
 Dataset: <https://www.image-net.org/download.php> to download the validation dataset.
 
 ### Model Conversion
 
 ```bash
 mkdir checkpoints
-python3 export_onnx.py --output_model checkpoints/res2net50.onnx
+python3 export_onnx.py --origin_model /path/to/res2net50_14w_8s-6527dddc.pth --output_model checkpoints/res2net50.onnx
 ```
 
 ## Inference
diff --git a/models/cv/classification/res2net50/ixrt/export_onnx.py b/models/cv/classification/res2net50/ixrt/export_onnx.py
index c85685e5bf3f9eb0540cae29d49d742e529e6ed9..ebc4a2f2efc260f94a50ee1ff83eca33268a3709 100644
--- a/models/cv/classification/res2net50/ixrt/export_onnx.py
+++ b/models/cv/classification/res2net50/ixrt/export_onnx.py
@@ -164,25 +164,17 @@ class Res2Net(nn.Module):
 
         return x
 
-def res2net50_14w_8s(pretrained=False, **kwargs):
-    """Constructs a Res2Net-50_14w_8s model.
-    Args:
-        pretrained (bool): If True, returns a model pre-trained on ImageNet
-    """
-    model = Res2Net(Bottle2neck, [3, 4, 6, 3], baseWidth = 14, scale = 8, **kwargs)
-    if pretrained:
-        model.load_state_dict(model_zoo.load_url(model_urls['res2net50_14w_8s']))
-    return model
-
 def parse_args():
     parser = argparse.ArgumentParser()
+    parser.add_argument("--origin_model", type=str)
     parser.add_argument("--output_model", type=str)
     args = parser.parse_args()
     return args
 
 if __name__ == '__main__':
     args = parse_args()
-    model = res2net50_14w_8s(pretrained=True)
+    model = Res2Net(Bottle2neck, [3, 4, 6, 3], baseWidth = 14, scale = 8)
+    model.load_state_dict(torch.load(args.origin_model))
     model.cuda()
     model.eval()
     input = torch.randn(32, 3, 224, 224, device='cuda')
diff --git a/models/cv/classification/res2net50/ixrt/inference.py b/models/cv/classification/res2net50/ixrt/inference.py
index 2c9dcb3f9cc5b9a26903651a31fafa16d8f0db31..50aafd4fd5ef9664203cdcbdfbdb577edca933c4 100644
--- a/models/cv/classification/res2net50/ixrt/inference.py
+++ b/models/cv/classification/res2net50/ixrt/inference.py
@@ -83,6 +83,7 @@ def main(config):
         total_sample = 0
         acc_top1, acc_top5 = 0, 0
 
+        start_time = time.time()
         with tqdm(total= len(dataloader)) as _tqdm:
             for idx, (batch_data, batch_label) in enumerate(dataloader):
                 batch_data = batch_data.numpy().astype(inputs[0]["dtype"])
@@ -104,7 +105,10 @@ def main(config):
                 _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample),
                                     acc_5='{:.4f}'.format(acc_top5/total_sample))
                 _tqdm.update(1)
+        end_time = time.time()
+        end2end_time = end_time - start_time
 
+        print(F"E2E time : {end2end_time:.3f} seconds")
         print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}")
         print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}")
         acc1 = acc_top1/total_sample
diff --git a/models/cv/classification/res2net50/ixrt/requirements.txt b/models/cv/classification/res2net50/ixrt/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e1eda59c3910ca96c73128bab86d534dbd55bbae
--- /dev/null
+++ b/models/cv/classification/res2net50/ixrt/requirements.txt
@@ -0,0 +1,4 @@
+tqdm
+onnx
+onnxsim
+tabulate
\ No newline at end of file
diff --git a/models/cv/classification/resnet18/ixrt/README.md b/models/cv/classification/resnet18/ixrt/README.md
index f78e7696ef5e69055a2f58fab41192958f72e419..71857e6566130c3daf7787a1314ecc1e947205e3 100644
--- a/models/cv/classification/resnet18/ixrt/README.md
+++ b/models/cv/classification/resnet18/ixrt/README.md
@@ -15,21 +15,20 @@ yum install -y mesa-libGL
 ## Ubuntu
 apt install -y libgl1-mesa-dev
 
-pip3 install tqdm
-pip3 install onnx
-pip3 install onnxsim
-pip3 install tabulate
+pip3 install -r requirements.txt
 ```
 
 ### Download
 
+Pretrained model: <https://download.pytorch.org/models/resnet18-f37072fd.pth>
+
 Dataset: <https://www.image-net.org/download.php> to download the validation dataset.
 
 ### Model Conversion
 
 ```bash
 mkdir checkpoints
-python3 export_onnx.py --output_model checkpoints/resnet18.onnx
+python3 export_onnx.py --origin_model /path/to/resnet18-f37072fd.pth --output_model checkpoints/resnet18.onnx
 ```
 
 ## Inference
diff --git a/models/cv/classification/resnet18/ixrt/export_onnx.py b/models/cv/classification/resnet18/ixrt/export_onnx.py
index 3f963af607436a492d204478ab86d2183600e85e..708a205ad78f86c0bad535875eb4c1e65f560f09 100644
--- a/models/cv/classification/resnet18/ixrt/export_onnx.py
+++ b/models/cv/classification/resnet18/ixrt/export_onnx.py
@@ -18,12 +18,14 @@ import argparse
 
 def parse_args():
     parser = argparse.ArgumentParser()
+    parser.add_argument("--origin_model", type=str)
     parser.add_argument("--output_model", type=str)
     args = parser.parse_args()
     return args
 
 args = parse_args()
-model = models.resnet18(pretrained=True)
+model = models.resnet18()
+model.load_state_dict(torch.load(args.origin_model))
 model.cuda()
 model.eval()
 input = torch.randn(1, 3, 224, 224, device='cuda')
diff --git a/models/cv/classification/resnet18/ixrt/inference.py b/models/cv/classification/resnet18/ixrt/inference.py
index 1ec56b4a1f09ee4bd7516461f758ac121a5346a0..4e178df4059e16e61daf0644862f27dd5fe99fbe 100644
--- a/models/cv/classification/resnet18/ixrt/inference.py
+++ b/models/cv/classification/resnet18/ixrt/inference.py
@@ -84,6 +84,7 @@ def main(config):
         total_sample = 0
         acc_top1, acc_top5 = 0, 0
 
+        start_time = time.time()
         with tqdm(total= len(dataloader)) as _tqdm:
             for idx, (batch_data, batch_label) in enumerate(dataloader):
                 batch_data = batch_data.numpy().astype(inputs[0]["dtype"])
@@ -105,7 +106,10 @@ def main(config):
                 _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample),
                                     acc_5='{:.4f}'.format(acc_top5/total_sample))
                 _tqdm.update(1)
+        end_time = time.time()
+        end2end_time = end_time - start_time
 
+        print(F"E2E time : {end2end_time:.3f} seconds")
         print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}")
         print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}")
         acc1 = acc_top1/total_sample
diff --git a/models/cv/classification/resnet18/ixrt/requirements.txt b/models/cv/classification/resnet18/ixrt/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e1eda59c3910ca96c73128bab86d534dbd55bbae
--- /dev/null
+++ b/models/cv/classification/resnet18/ixrt/requirements.txt
@@ -0,0 +1,4 @@
+tqdm
+onnx
+onnxsim
+tabulate
\ No newline at end of file
diff --git a/models/cv/classification/shufflenet_v1/ixrt/README.md b/models/cv/classification/shufflenet_v1/ixrt/README.md
index e29de33a7591d2009687d454676a54b5735d3012..4dee5cae70e0259f6abf2d47d90b6689d3e0b758 100644
--- a/models/cv/classification/shufflenet_v1/ixrt/README.md
+++ b/models/cv/classification/shufflenet_v1/ixrt/README.md
@@ -16,17 +16,13 @@ yum install -y mesa-libGL
 ## Ubuntu
 apt install -y libgl1-mesa-dev
 
-pip3 install tqdm
-pip3 install tabulate
-pip3 install onnx
-pip3 install onnxsim
-pip3 install opencv-python==4.6.0.66
-pip3 install mmcls==0.24.0
-pip3 install mmcv==1.5.3
+pip3 install -r requirements.txt
 ```
 
 ### Download
 
+Pretrained model: <https://download.openmmlab.com/mmclassification/v0/shufflenet_v1/shufflenet_v1_batch1024_imagenet_20200804-5d6cec73.pth>
+
 Dataset: <https://www.image-net.org/download.php> to download the validation dataset.
 
 ### Model Conversion
@@ -39,7 +35,7 @@ cd ..
 
 python3 export_onnx.py   \
     --config_file ./checkpoints/mmpretrain/configs/shufflenet_v1/shufflenet-v1-1x_16xb64_in1k.py  \
-    --checkpoint_file  https://download.openmmlab.com/mmclassification/v0/shufflenet_v1/shufflenet_v1_batch1024_imagenet_20200804-5d6cec73.pth \
+    --checkpoint_file  ./shufflenet_v1_batch1024_imagenet_20200804-5d6cec73.pth \
     --output_model ./checkpoints/shufflenet_v1.onnx
 ```
 
diff --git a/models/cv/classification/shufflenet_v1/ixrt/inference.py b/models/cv/classification/shufflenet_v1/ixrt/inference.py
index 1ec56b4a1f09ee4bd7516461f758ac121a5346a0..4e178df4059e16e61daf0644862f27dd5fe99fbe 100644
--- a/models/cv/classification/shufflenet_v1/ixrt/inference.py
+++ b/models/cv/classification/shufflenet_v1/ixrt/inference.py
@@ -84,6 +84,7 @@ def main(config):
         total_sample = 0
         acc_top1, acc_top5 = 0, 0
 
+        start_time = time.time()
         with tqdm(total= len(dataloader)) as _tqdm:
             for idx, (batch_data, batch_label) in enumerate(dataloader):
                 batch_data = batch_data.numpy().astype(inputs[0]["dtype"])
@@ -105,7 +106,10 @@ def main(config):
                 _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample),
                                     acc_5='{:.4f}'.format(acc_top5/total_sample))
                 _tqdm.update(1)
+        end_time = time.time()
+        end2end_time = end_time - start_time
 
+        print(F"E2E time : {end2end_time:.3f} seconds")
         print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}")
         print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}")
         acc1 = acc_top1/total_sample
diff --git a/models/cv/classification/shufflenet_v1/ixrt/requirements.txt b/models/cv/classification/shufflenet_v1/ixrt/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..fdd84a5d3a5ddc461faddea827aa328528ef8f88
--- /dev/null
+++ b/models/cv/classification/shufflenet_v1/ixrt/requirements.txt
@@ -0,0 +1,7 @@
+tqdm
+tabulate
+onnx
+onnxsim
+opencv-python==4.6.0.66
+mmcls==0.24.0
+mmcv==1.5.3
\ No newline at end of file
diff --git a/models/cv/classification/squeezenet_1.1/ixrt/README.md b/models/cv/classification/squeezenet_v11/ixrt/README.md
similarity index 87%
rename from models/cv/classification/squeezenet_1.1/ixrt/README.md
rename to models/cv/classification/squeezenet_v11/ixrt/README.md
index 08fe037a0c7c3f1037b531c440dc553d43ebdb60..df5b02d4e3e120381f69995591364b1edcb01524 100644
--- a/models/cv/classification/squeezenet_1.1/ixrt/README.md
+++ b/models/cv/classification/squeezenet_v11/ixrt/README.md
@@ -17,13 +17,7 @@ yum install -y mesa-libGL
 ## Ubuntu
 apt install -y libgl1-mesa-dev
 
-pip3 install tqdm
-pip3 install onnx
-pip3 install onnxsim
-pip3 install tabulate
-pip3 install ppq
-pip3 install pycuda
-pip3 install opencv-python==4.6.0.66
+pip3 install -r requirements.txt
 ```
 
 ### Download
@@ -36,7 +30,7 @@ Dataset: <https://www.image-net.org/download.php> to download the validation dat
 
 ```bash
 mkdir checkpoints 
-python3 export_onnx.py --origin_model  /path/to/squeezenet1_1-b8a52dc0.pth --output_model checkpoints/squeezenetv11.onnx
+python3 export_onnx.py --origin_model  /path/to/squeezenet1_1-b8a52dc0.pth --output_model checkpoints/squeezenet_v11.onnx
 ```
 
 ## Inference
diff --git a/models/cv/classification/squeezenet_1.1/ixrt/build_engine.py b/models/cv/classification/squeezenet_v11/ixrt/build_engine.py
similarity index 100%
rename from models/cv/classification/squeezenet_1.1/ixrt/build_engine.py
rename to models/cv/classification/squeezenet_v11/ixrt/build_engine.py
diff --git a/models/cv/classification/squeezenet_1.1/ixrt/build_i8_engine.py b/models/cv/classification/squeezenet_v11/ixrt/build_i8_engine.py
similarity index 100%
rename from models/cv/classification/squeezenet_1.1/ixrt/build_i8_engine.py
rename to models/cv/classification/squeezenet_v11/ixrt/build_i8_engine.py
diff --git a/models/cv/classification/squeezenet_1.1/ixrt/calibration_dataset.py b/models/cv/classification/squeezenet_v11/ixrt/calibration_dataset.py
similarity index 100%
rename from models/cv/classification/squeezenet_1.1/ixrt/calibration_dataset.py
rename to models/cv/classification/squeezenet_v11/ixrt/calibration_dataset.py
diff --git a/models/cv/classification/squeezenet_1.1/ixrt/common.py b/models/cv/classification/squeezenet_v11/ixrt/common.py
similarity index 100%
rename from models/cv/classification/squeezenet_1.1/ixrt/common.py
rename to models/cv/classification/squeezenet_v11/ixrt/common.py
diff --git a/models/cv/classification/squeezenet_1.1/ixrt/config/SQUEEZENET_V11_CONFIG b/models/cv/classification/squeezenet_v11/ixrt/config/SQUEEZENET_V11_CONFIG
similarity index 95%
rename from models/cv/classification/squeezenet_1.1/ixrt/config/SQUEEZENET_V11_CONFIG
rename to models/cv/classification/squeezenet_v11/ixrt/config/SQUEEZENET_V11_CONFIG
index efc2a0870434a41575d490a17821a8ad816c81b9..19d35c97654c126bf70a5c0eeaabab48b7fe291f 100644
--- a/models/cv/classification/squeezenet_1.1/ixrt/config/SQUEEZENET_V11_CONFIG
+++ b/models/cv/classification/squeezenet_v11/ixrt/config/SQUEEZENET_V11_CONFIG
@@ -3,7 +3,7 @@
 # ORIGINE_MODEL : 原始onnx文件名称
 IMGSIZE=224
 MODEL_NAME=SqueezeNet_v11
-ORIGINE_MODEL=squeezenetv11.onnx
+ORIGINE_MODEL=squeezenet_v11.onnx
 
 # QUANT CONFIG (仅PRECISION为int8时生效)
     # QUANT_OBSERVER : 量化策略，可选 [hist_percentile, percentile, minmax, entropy, ema]
diff --git a/models/cv/classification/squeezenet_1.1/ixrt/export_onnx.py b/models/cv/classification/squeezenet_v11/ixrt/export_onnx.py
similarity index 100%
rename from models/cv/classification/squeezenet_1.1/ixrt/export_onnx.py
rename to models/cv/classification/squeezenet_v11/ixrt/export_onnx.py
diff --git a/models/cv/classification/squeezenet_1.1/ixrt/inference.py b/models/cv/classification/squeezenet_v11/ixrt/inference.py
similarity index 96%
rename from models/cv/classification/squeezenet_1.1/ixrt/inference.py
rename to models/cv/classification/squeezenet_v11/ixrt/inference.py
index 1ec56b4a1f09ee4bd7516461f758ac121a5346a0..4e178df4059e16e61daf0644862f27dd5fe99fbe 100644
--- a/models/cv/classification/squeezenet_1.1/ixrt/inference.py
+++ b/models/cv/classification/squeezenet_v11/ixrt/inference.py
@@ -84,6 +84,7 @@ def main(config):
         total_sample = 0
         acc_top1, acc_top5 = 0, 0
 
+        start_time = time.time()
         with tqdm(total= len(dataloader)) as _tqdm:
             for idx, (batch_data, batch_label) in enumerate(dataloader):
                 batch_data = batch_data.numpy().astype(inputs[0]["dtype"])
@@ -105,7 +106,10 @@ def main(config):
                 _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample),
                                     acc_5='{:.4f}'.format(acc_top5/total_sample))
                 _tqdm.update(1)
+        end_time = time.time()
+        end2end_time = end_time - start_time
 
+        print(F"E2E time : {end2end_time:.3f} seconds")
         print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}")
         print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}")
         acc1 = acc_top1/total_sample
diff --git a/models/cv/classification/squeezenet_1.1/ixrt/modify_batchsize.py b/models/cv/classification/squeezenet_v11/ixrt/modify_batchsize.py
similarity index 100%
rename from models/cv/classification/squeezenet_1.1/ixrt/modify_batchsize.py
rename to models/cv/classification/squeezenet_v11/ixrt/modify_batchsize.py
diff --git a/models/cv/classification/squeezenet_1.1/ixrt/quant.py b/models/cv/classification/squeezenet_v11/ixrt/quant.py
similarity index 100%
rename from models/cv/classification/squeezenet_1.1/ixrt/quant.py
rename to models/cv/classification/squeezenet_v11/ixrt/quant.py
diff --git a/models/cv/classification/squeezenet_1.1/ixrt/refine_model.py b/models/cv/classification/squeezenet_v11/ixrt/refine_model.py
similarity index 100%
rename from models/cv/classification/squeezenet_1.1/ixrt/refine_model.py
rename to models/cv/classification/squeezenet_v11/ixrt/refine_model.py
diff --git a/models/cv/classification/squeezenet_v11/ixrt/requirements.txt b/models/cv/classification/squeezenet_v11/ixrt/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..e4d443b8e992b2c8b0184ab649efff0ba2f0a458
--- /dev/null
+++ b/models/cv/classification/squeezenet_v11/ixrt/requirements.txt
@@ -0,0 +1,7 @@
+tqdm
+onnx
+onnxsim
+tabulate
+ppq
+pycuda
+opencv-python==4.6.0.66
\ No newline at end of file
diff --git a/models/cv/classification/squeezenet_1.1/ixrt/scripts/infer_squeezenet_v11_fp16_accuracy.sh b/models/cv/classification/squeezenet_v11/ixrt/scripts/infer_squeezenet_v11_fp16_accuracy.sh
similarity index 100%
rename from models/cv/classification/squeezenet_1.1/ixrt/scripts/infer_squeezenet_v11_fp16_accuracy.sh
rename to models/cv/classification/squeezenet_v11/ixrt/scripts/infer_squeezenet_v11_fp16_accuracy.sh
diff --git a/models/cv/classification/squeezenet_1.1/ixrt/scripts/infer_squeezenet_v11_fp16_performance.sh b/models/cv/classification/squeezenet_v11/ixrt/scripts/infer_squeezenet_v11_fp16_performance.sh
similarity index 100%
rename from models/cv/classification/squeezenet_1.1/ixrt/scripts/infer_squeezenet_v11_fp16_performance.sh
rename to models/cv/classification/squeezenet_v11/ixrt/scripts/infer_squeezenet_v11_fp16_performance.sh
diff --git a/models/cv/classification/squeezenet_1.1/ixrt/scripts/infer_squeezenet_v11_int8_accuracy.sh b/models/cv/classification/squeezenet_v11/ixrt/scripts/infer_squeezenet_v11_int8_accuracy.sh
similarity index 100%
rename from models/cv/classification/squeezenet_1.1/ixrt/scripts/infer_squeezenet_v11_int8_accuracy.sh
rename to models/cv/classification/squeezenet_v11/ixrt/scripts/infer_squeezenet_v11_int8_accuracy.sh
diff --git a/models/cv/classification/squeezenet_1.1/ixrt/scripts/infer_squeezenet_v11_int8_performance.sh b/models/cv/classification/squeezenet_v11/ixrt/scripts/infer_squeezenet_v11_int8_performance.sh
similarity index 100%
rename from models/cv/classification/squeezenet_1.1/ixrt/scripts/infer_squeezenet_v11_int8_performance.sh
rename to models/cv/classification/squeezenet_v11/ixrt/scripts/infer_squeezenet_v11_int8_performance.sh
diff --git a/models/cv/classification/squeezenet_1.1/ixrt/simplify_model.py b/models/cv/classification/squeezenet_v11/ixrt/simplify_model.py
similarity index 100%
rename from models/cv/classification/squeezenet_1.1/ixrt/simplify_model.py
rename to models/cv/classification/squeezenet_v11/ixrt/simplify_model.py
diff --git a/models/cv/classification/vgg16/ixrt/README.md b/models/cv/classification/vgg16/ixrt/README.md
index 370adda08eab7178f22bd98afd3e57eb8dbbb720..789fcc8b3684285c58795ecd92fb93f707817dd2 100644
--- a/models/cv/classification/vgg16/ixrt/README.md
+++ b/models/cv/classification/vgg16/ixrt/README.md
@@ -16,20 +16,20 @@ yum install -y mesa-libGL
 ## Ubuntu
 apt install -y libgl1-mesa-dev
 
-pip3 install tqdm
-pip3 install onnxsim
-pip3 install opencv-python==4.6.0.66
+pip3 install -r requirements.txt
 ```
 
 ### Download
 
+Pretrained model: <https://download.pytorch.org/models/vgg16-397923af.pth>
+
 Dataset: <https://www.image-net.org/download.php> to download the validation dataset.
 
 ### Model Conversion
 
 ```bash
 mkdir checkpoints 
-python3 export_onnx.py --output_model checkpoints/vgg16.onnx
+python3 export_onnx.py --origin_model /path/to/vgg16-397923af.pth --output_model checkpoints/vgg16.onnx
 ```
 
 ## Inference
diff --git a/models/cv/classification/vgg16/ixrt/export_onnx.py b/models/cv/classification/vgg16/ixrt/export_onnx.py
index aa0b19ae125c80b7b1c9253a602d8cd8dd628184..17d8bb550f8ba8af7bcf8073682808d44d34701d 100644
--- a/models/cv/classification/vgg16/ixrt/export_onnx.py
+++ b/models/cv/classification/vgg16/ixrt/export_onnx.py
@@ -18,12 +18,14 @@ import argparse
 
 def parse_args():
     parser = argparse.ArgumentParser()
+    parser.add_argument("--origin_model", type=str)
     parser.add_argument("--output_model", type=str)
     args = parser.parse_args()
     return args
 
 args = parse_args()
-model = models.vgg16(pretrained=True)
+model = models.vgg16()
+model.load_state_dict(torch.load(args.origin_model))
 model.cuda()
 model.eval()
 input = torch.randn(1, 3, 224, 224, device='cuda')
diff --git a/models/cv/classification/vgg16/ixrt/inference.py b/models/cv/classification/vgg16/ixrt/inference.py
index 1ec56b4a1f09ee4bd7516461f758ac121a5346a0..4e178df4059e16e61daf0644862f27dd5fe99fbe 100644
--- a/models/cv/classification/vgg16/ixrt/inference.py
+++ b/models/cv/classification/vgg16/ixrt/inference.py
@@ -84,6 +84,7 @@ def main(config):
         total_sample = 0
         acc_top1, acc_top5 = 0, 0
 
+        start_time = time.time()
         with tqdm(total= len(dataloader)) as _tqdm:
             for idx, (batch_data, batch_label) in enumerate(dataloader):
                 batch_data = batch_data.numpy().astype(inputs[0]["dtype"])
@@ -105,7 +106,10 @@ def main(config):
                 _tqdm.set_postfix(acc_1='{:.4f}'.format(acc_top1/total_sample),
                                     acc_5='{:.4f}'.format(acc_top5/total_sample))
                 _tqdm.update(1)
+        end_time = time.time()
+        end2end_time = end_time - start_time
 
+        print(F"E2E time : {end2end_time:.3f} seconds")
         print(F"Acc@1 : {acc_top1/total_sample} = {acc_top1}/{total_sample}")
         print(F"Acc@5 : {acc_top5/total_sample} = {acc_top5}/{total_sample}")
         acc1 = acc_top1/total_sample
diff --git a/models/cv/classification/vgg16/ixrt/requirements.txt b/models/cv/classification/vgg16/ixrt/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..24dc14b78899672d6308c24c16a8168b90577adb
--- /dev/null
+++ b/models/cv/classification/vgg16/ixrt/requirements.txt
@@ -0,0 +1,3 @@
+tqdm
+onnxsim
+opencv-python==4.6.0.66
\ No newline at end of file
diff --git a/models/cv/detection/yolov8/igie/README.md b/models/cv/detection/yolov8/igie/README.md
index ce5ce80d45f958e2df15e464e5685363f7234a22..cb2a3594c7c7a629bca502caaa9a793ee652f76a 100644
--- a/models/cv/detection/yolov8/igie/README.md
+++ b/models/cv/detection/yolov8/igie/README.md
@@ -18,7 +18,7 @@ apt install -y libgl1-mesa-dev
 pip3 install tqdm
 pip3 install onnx
 pip3 install pycocotools
-pip3 install ultralytics
+pip3 install ultralytics==8.2.51
 ```
 
 ### Download
diff --git a/models/cv/detection/yolov8/ixrt/README.md b/models/cv/detection/yolov8/ixrt/README.md
index 96d637e0d9bfd485d169ddaf7c55d26eddeacbf3..6ed7ea5364fe0d7eeecf65d31d75ca47ecb52676 100644
--- a/models/cv/detection/yolov8/ixrt/README.md
+++ b/models/cv/detection/yolov8/ixrt/README.md
@@ -15,12 +15,7 @@ yum install -y mesa-libGL
 ## Ubuntu
 apt install -y libgl1-mesa-glx
 
-pip3 install tqdm
-pip3 install onnx
-pip3 install onnxsim
-pip3 install pycocotools
-pip3 install ultralytics
-pip3 install cuda-python
+pip3 install -r requirements.txt
 ```
 
 ### Download
@@ -29,39 +24,40 @@ Pretrained model: <https://github.com/ultralytics/assets/releases/download/v8.2.
 
 Dataset: <http://images.cocodataset.org/zips/val2017.zip> to download the validation dataset.
 
-```bash
-# get yolov8n.pt
-wget https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt
-# set coco path
-mkdir -p data/
-ln -s /Path/to/coco/ data/coco
-```
-
 ### Model Conversion
 
 ```bash
-python3 export.py --weight yolov8n.pt --batch 32
-onnxsim yolov8n.onnx ./data/yolov8n.onnx
+mkdir -p checkpoints/
+mv yolov8n.pt yolov8.pt
+python3 export.py --weight yolov8.pt --batch 32
+onnxsim yolov8.onnx ./checkpoints/yolov8.onnx
 ```
 
 ## Inference
 
+```bash
+export PROJ_DIR=./
+export DATASETS_DIR=/path/to/coco/
+export CHECKPOINTS_DIR=./checkpoints
+export RUN_DIR=./
+```
+
 ### FP16
 
 ```bash
 # Accuracy
-bash scripts/infer_yolov8n_fp16_accuracy.sh
+bash scripts/infer_yolov8_fp16_accuracy.sh
 # Performance
-bash scripts/infer_yolov8n_fp16_performance.sh
+bash scripts/infer_yolov8_fp16_performance.sh
 ```
 
 ### INT8
 
 ```bash
 # Accuracy
-bash scripts/infer_yolov8n_int8_accuracy.sh
+bash scripts/infer_yolov8_int8_accuracy.sh
 # Performance
-bash scripts/infer_yolov8n_int8_performance.sh
+bash scripts/infer_yolov8_int8_performance.sh
 ```
 
 ## Results
diff --git a/models/cv/detection/yolov8/ixrt/requirements.txt b/models/cv/detection/yolov8/ixrt/requirements.txt
new file mode 100644
index 0000000000000000000000000000000000000000..cc201ca4f6b252e9330de7997a4e707544f07470
--- /dev/null
+++ b/models/cv/detection/yolov8/ixrt/requirements.txt
@@ -0,0 +1,6 @@
+tqdm
+onnx
+onnxsim
+pycocotools
+ultralytics==8.2.51
+cuda-python
\ No newline at end of file
diff --git a/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_fp16_accuracy.sh b/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_fp16_accuracy.sh
similarity index 88%
rename from models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_fp16_accuracy.sh
rename to models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_fp16_accuracy.sh
index 44e7537657a65fc84d89531b8df9ad647513dfbe..65434fece2c57f803a2e27eadf2289bdf61cc7b3 100644
--- a/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_fp16_accuracy.sh
+++ b/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_fp16_accuracy.sh
@@ -22,27 +22,27 @@ check_status()
     fi
 }
 
-PROJ_DIR=$(cd $(dirname $0);cd ../; pwd)
-DATASETS_DIR="${PROJ_DIR}/data/coco"
+PROJ_DIR=${PROJ_DIR}
+DATASETS_DIR=${DATASETS_DIR}
 COCO_GT=${DATASETS_DIR}/annotations/instances_val2017.json
 EVAL_DIR=${DATASETS_DIR}/images/val2017
-CHECKPOINTS_DIR="${PROJ_DIR}/data"
-RUN_DIR="${PROJ_DIR}"
+CHECKPOINTS_DIR=${CHECKPOINTS_DIR}
+RUN_DIR=${PROJ_DIR}
 ORIGINE_MODEL=${CHECKPOINTS_DIR}
 
 echo CHECKPOINTS_DIR : ${CHECKPOINTS_DIR}
 echo DATASETS_DIR : ${DATASETS_DIR}
 echo RUN_DIR : ${RUN_DIR}
 echo ====================== Model Info ======================
-echo Model Name : yolov8n
+echo Model Name : yolov8
 echo Onnx Path : ${ORIGINE_MODEL}
 
 BATCH_SIZE=32
-CURRENT_MODEL=${CHECKPOINTS_DIR}/yolov8n.onnx
+CURRENT_MODEL=${CHECKPOINTS_DIR}/yolov8.onnx
 
 # Build Engine
 echo Build Engine
-ENGINE_FILE=${CHECKPOINTS_DIR}/yolov8n_fp16.engine
+ENGINE_FILE=${CHECKPOINTS_DIR}/yolov8_fp16.engine
 if [ -f $ENGINE_FILE ];then
     echo "  "Build Engine Skip, $ENGINE_FILE has been existed
 else
diff --git a/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_fp16_performance.sh b/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_fp16_performance.sh
similarity index 88%
rename from models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_fp16_performance.sh
rename to models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_fp16_performance.sh
index 1ab3808f1f45cf2072fa41a2107fa88c17fa3610..355b27bc6f306786f31c1dee3beabc5360e2bf0d 100644
--- a/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_fp16_performance.sh
+++ b/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_fp16_performance.sh
@@ -22,27 +22,27 @@ check_status()
     fi
 }
 
-PROJ_DIR=$(cd $(dirname $0);cd ../; pwd)
-DATASETS_DIR="${PROJ_DIR}/data/coco"
+PROJ_DIR=${PROJ_DIR}
+DATASETS_DIR=${DATASETS_DIR}
 COCO_GT=${DATASETS_DIR}/annotations/instances_val2017.json
 EVAL_DIR=${DATASETS_DIR}/images/val2017
-CHECKPOINTS_DIR="${PROJ_DIR}/data"
-RUN_DIR="${PROJ_DIR}"
+CHECKPOINTS_DIR=${CHECKPOINTS_DIR}
+RUN_DIR=${PROJ_DIR}
 ORIGINE_MODEL=${CHECKPOINTS_DIR}
 
 echo CHECKPOINTS_DIR : ${CHECKPOINTS_DIR}
 echo DATASETS_DIR : ${DATASETS_DIR}
 echo RUN_DIR : ${RUN_DIR}
 echo ====================== Model Info ======================
-echo Model Name : yolov8n
+echo Model Name : yolov8
 echo Onnx Path : ${ORIGINE_MODEL}
 
 BATCH_SIZE=32
-CURRENT_MODEL=${CHECKPOINTS_DIR}/yolov8n.onnx
+CURRENT_MODEL=${CHECKPOINTS_DIR}/yolov8.onnx
 
 # Build Engine
 echo Build Engine
-ENGINE_FILE=${CHECKPOINTS_DIR}/yolov8n_fp16.engine
+ENGINE_FILE=${CHECKPOINTS_DIR}/yolov8_fp16.engine
 if [ -f $ENGINE_FILE ];then
     echo "  "Build Engine Skip, $ENGINE_FILE has been existed
 else
diff --git a/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_int8_accuracy.sh b/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_int8_accuracy.sh
similarity index 90%
rename from models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_int8_accuracy.sh
rename to models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_int8_accuracy.sh
index a2257463d70ee8fe6e9853db0fafd44f98ad8c83..bf1ecf255f6a16ee859573b1dd5d93b7d138b245 100644
--- a/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_int8_accuracy.sh
+++ b/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_int8_accuracy.sh
@@ -22,12 +22,12 @@ check_status()
     fi
 }
 
-PROJ_DIR=$(cd $(dirname $0);cd ../; pwd)
-DATASETS_DIR="${PROJ_DIR}/data/coco"
+PROJ_DIR=${PROJ_DIR}
+DATASETS_DIR=${DATASETS_DIR}
 COCO_GT=${DATASETS_DIR}/annotations/instances_val2017.json
 EVAL_DIR=${DATASETS_DIR}/images/val2017
-CHECKPOINTS_DIR="${PROJ_DIR}/data"
-RUN_DIR="${PROJ_DIR}"
+CHECKPOINTS_DIR=${CHECKPOINTS_DIR}
+RUN_DIR=${PROJ_DIR}
 ORIGINE_MODEL=${CHECKPOINTS_DIR}
 DISABLE_NAMES=('/model.22/Concat' '/model.22/Concat_1' '/model.22/Concat_2' '/model.22/Reshape' '/model.22/Reshape_1' '/model.22/Reshape_2' '/model.22/Concat_3' '/model.22/Split' '/model.22/dfl/Reshape' '/model.22/dfl/Transpose' '/model.22/dfl/Softmax' '/model.22/dfl/Transpose_1' '/model.22/dfl/conv/Conv' '/model.22/dfl/Reshape_1' '/model.22/Slice' '/model.22/Slice_1' '/model.22/Sub' '/model.22/Add_1' '/model.22/Add_2' '/model.22/Div_1' '/model.22/Sub_1' '/model.22/Concat_4' '/model.22/Mul_2' '/model.22/Sigmoid' '/model.22/Concat_5')
 
@@ -35,19 +35,19 @@ echo CHECKPOINTS_DIR : ${CHECKPOINTS_DIR}
 echo DATASETS_DIR : ${DATASETS_DIR}
 echo RUN_DIR : ${RUN_DIR}
 echo ====================== Model Info ======================
-echo Model Name : yolov8n
+echo Model Name : yolov8
 echo Onnx Path : ${ORIGINE_MODEL}
 
 BATCH_SIZE=32
-CURRENT_MODEL=${CHECKPOINTS_DIR}/yolov8n.onnx
+CURRENT_MODEL=${CHECKPOINTS_DIR}/yolov8.onnx
 
 # quant
-FINAL_MODEL=${CHECKPOINTS_DIR}/quantized_yolov8n_bs${BATCH_SIZE}.onnx
+FINAL_MODEL=${CHECKPOINTS_DIR}/quantized_yolov8_bs${BATCH_SIZE}.onnx
 if [ -f $FINAL_MODEL ];then
     echo "  "Quantize Skip, $FINAL_MODEL has been existed
 else
     python3 ${RUN_DIR}/quant.py             \
-        --model_name "YOLOV8N"       \
+        --model_name "YOLOV8"       \
         --model ${CURRENT_MODEL}            \
         --bsz ${BATCH_SIZE}                 \
         --dataset_dir ${EVAL_DIR}           \
@@ -62,7 +62,7 @@ CURRENT_MODEL=${FINAL_MODEL}
 
 # Build Engine
 echo Build Engine
-ENGINE_FILE=${CHECKPOINTS_DIR}/yolov8n_int8.engine
+ENGINE_FILE=${CHECKPOINTS_DIR}/yolov8_int8.engine
 if [ -f $ENGINE_FILE ];then
     echo "  "Build Engine Skip, $ENGINE_FILE has been existed
 else
diff --git a/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_int8_performance.sh b/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_int8_performance.sh
similarity index 89%
rename from models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_int8_performance.sh
rename to models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_int8_performance.sh
index f1774d5b2b28ce734dadb3e022a3359b3790f2da..f4c31b681cb2b436543cdbe568d5349e3693080d 100644
--- a/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8n_int8_performance.sh
+++ b/models/cv/detection/yolov8/ixrt/scripts/infer_yolov8_int8_performance.sh
@@ -22,31 +22,31 @@ check_status()
     fi
 }
 
-PROJ_DIR=$(cd $(dirname $0);cd ../; pwd)
-DATASETS_DIR="${PROJ_DIR}/data/coco"
+PROJ_DIR=${PROJ_DIR}
+DATASETS_DIR=${DATASETS_DIR}
 COCO_GT=${DATASETS_DIR}/annotations/instances_val2017.json
 EVAL_DIR=${DATASETS_DIR}/images/val2017
-CHECKPOINTS_DIR="${PROJ_DIR}/data"
-RUN_DIR="${PROJ_DIR}"
+CHECKPOINTS_DIR=${CHECKPOINTS_DIR}
+RUN_DIR=${PROJ_DIR}
 ORIGINE_MODEL=${CHECKPOINTS_DIR}
 
 echo CHECKPOINTS_DIR : ${CHECKPOINTS_DIR}
 echo DATASETS_DIR : ${DATASETS_DIR}
 echo RUN_DIR : ${RUN_DIR}
 echo ====================== Model Info ======================
-echo Model Name : yolov8n
+echo Model Name : yolov8
 echo Onnx Path : ${ORIGINE_MODEL}
 
 BATCH_SIZE=32
-CURRENT_MODEL=${CHECKPOINTS_DIR}/yolov8n.onnx
+CURRENT_MODEL=${CHECKPOINTS_DIR}/yolov8.onnx
 
 # quant
-FINAL_MODEL=${CHECKPOINTS_DIR}/quantized_yolov8n_bs${BATCH_SIZE}.onnx
+FINAL_MODEL=${CHECKPOINTS_DIR}/quantized_yolov8_bs${BATCH_SIZE}.onnx
 if [ -f $FINAL_MODEL ];then
     echo "  "Quantize Skip, $FINAL_MODEL has been existed
 else
     python3 ${RUN_DIR}/quant.py             \
-        --model_name "YOLOV8N"       \
+        --model_name "YOLOV8"       \
         --model ${CURRENT_MODEL}            \
         --bsz ${BATCH_SIZE}                 \
         --dataset_dir ${EVAL_DIR}           \
@@ -61,7 +61,7 @@ CURRENT_MODEL=${FINAL_MODEL}
 
 # Build Engine
 echo Build Engine
-ENGINE_FILE=${CHECKPOINTS_DIR}/yolov8n_int8.engine
+ENGINE_FILE=${CHECKPOINTS_DIR}/yolov8_int8.engine
 if [ -f $ENGINE_FILE ];then
     echo "  "Build Engine Skip, $ENGINE_FILE has been existed
 else