diff --git a/.gitignore b/.gitignore
index 16062a91..b7e7e426 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,6 +1,4 @@
-output/
-weight/
-*.pyc
-wandb/
-*.pth
-*.onnx
+output/
+weight/
+*.pyc
+wandb/
diff --git a/requirements.txt b/requirements.txt
index aadfb81c..aa28cd33 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -7,3 +7,4 @@ scipy
 calflops
 transformers
 loguru
+opencv-python
diff --git a/single-forever-1024x646.jpg b/single-forever-1024x646.jpg
new file mode 100644
index 00000000..7573da63
Binary files /dev/null and b/single-forever-1024x646.jpg differ
diff --git a/tools/deployment/export_openvino.py b/tools/deployment/export_openvino.py
new file mode 100644
index 00000000..f3c71de9
--- /dev/null
+++ b/tools/deployment/export_openvino.py
@@ -0,0 +1,115 @@
+"""
+D-FINE: Redefine Regression Task of DETRs as Fine-grained Distribution Refinement
+Copyright (c) 2024 The D-FINE Authors. All Rights Reserved.
+---------------------------------------------------------------------------------
+Modified from RT-DETR (https://github.com/lyuwenyu/RT-DETR)
+Copyright (c) 2023 lyuwenyu. All Rights Reserved.
+"""
+
+import os
+import sys
+
+from pathlib import Path
+
+sys.path.insert(0, os.path.join(os.path.dirname(os.path.abspath(__file__)), "../.."))
+
+import openvino as ov
+import nncf
+import torch
+from torchvision import datasets, transforms
+import numpy as np
+
+
+def main(
+    args,
+):
+    """main"""
+    print("Start OpenVINO model convertion...")
+    if not args.dynamic and args.batch_size == 1:
+        inp = [1, 3, args.img_size[0], args.img_size[1]]
+    elif args.batch_size > 1 and args.dynamic:
+        inp = [-1, 3, -1, -1]
+    elif args.batch_size > 1:
+        inp = [-1, 3, args.img_size[0], args.img_size[1]]
+    elif args.dynamic:
+        inp = [1, 3, -1, -1]
+
+    model = ov.convert_model(
+        input_model=str(args.model_path),
+        input=inp,
+    )
+    ov.serialize(model, str(Path(args.model_path).with_suffix(".xml")), str(Path(args.model_path).with_suffix(".bin")))
+    print("OpenVINO model exported")
+
+    if args.quantize_nncf :
+        print("Start NNCF quantization...")
+
+        # Instantiate your uncompressed model
+        model = ov.Core().read_model(str(Path(args.model_path).with_suffix(".xml")))
+
+        # # Provide validation part of the dataset to collect statistics needed for the compression algorithm
+        val_dataset = datasets.ImageFolder(args.calibration_dataset_path, transform=transforms.Compose([transforms.ToTensor()]))
+        dataset_loader = torch.utils.data.DataLoader(val_dataset, batch_size=1)
+
+        # Step 1: Initialize transformation function
+        def transform_fn(data_item):
+            images, _ = data_item
+            orig_size = np.array([args.img_size[0], args.img_size[0]], dtype=np.int64).reshape(
+            1, 2
+            )
+            inputs = {
+                "images": np.array(images),
+                "orig_target_sizes": orig_size,
+            }
+            return inputs
+
+        # Step 2: Initialize NNCF Dataset
+        calibration_dataset = nncf.Dataset(dataset_loader, transform_fn)
+        # Step 3: Run the quantization pipeline
+        quantized_model = nncf.quantize(model, calibration_dataset, preset=nncf.QuantizationPreset.MIXED)
+        # Step 4: Save model
+        ov.save_model(quantized_model,str(Path(args.model_path.replace(".onnx","_int8.xml"))))
+        print("OpenVINO model quantized")
+
+
+if __name__ == "__main__":
+    import argparse
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--model_path",
+        "-m",
+        type=str,
+        required=True,
+    )
+    parser.add_argument(
+        "--dynamic",
+        "-d",
+        default=False,
+        type=bool,
+    )
+    parser.add_argument(
+        "--batch_size",
+        "-b",
+        default=1,
+        type=int,
+    )
+    parser.add_argument(
+        "--img_size",
+        "-i",
+        default=(640,640),
+        type=tuple,
+    )
+    parser.add_argument(
+        "--quantize_nncf",
+        "-q",
+        default=False,
+        type=bool,
+    )
+    parser.add_argument(
+        "--calibration_dataset_path",
+        "-c",
+        type=str,
+    )
+    args = parser.parse_args()
+    main(args)
diff --git a/tools/deployment/requirements.txt b/tools/deployment/requirements.txt
new file mode 100644
index 00000000..0336ca61
--- /dev/null
+++ b/tools/deployment/requirements.txt
@@ -0,0 +1,4 @@
+onnx
+onnxsim
+nncf
+numpy