diff --git a/anylabeling/configs/auto_labeling/models.yaml b/anylabeling/configs/auto_labeling/models.yaml
index f810013e..78a21060 100644
--- a/anylabeling/configs/auto_labeling/models.yaml
+++ b/anylabeling/configs/auto_labeling/models.yaml
@@ -62,6 +62,16 @@
   config_file: ":/ram_plus_swin_large_14m.yaml"
 - model_name: "ram_swin_large_14m-r20231024"
   config_file: ":/ram_swin_large_14m.yaml"
+- model_name: "rtdetrv2l-r20240730"
+  config_file: ":/rtdetrv2l.yaml"
+- model_name: "rtdetrv2m-r20240730"
+  config_file: ":/rtdetrv2m.yaml"
+- model_name: "rtdetrv2m7x-r20240730"
+  config_file: ":/rtdetrv2m7x.yaml"
+- model_name: "rtdetrv2s-r20240730"
+  config_file: ":/rtdetrv2s.yaml"
+- model_name: "rtdetrv2x-r20240730"
+  config_file: ":/rtdetrv2x.yaml"
 - model_name: "rtdetr_r50-r20230520"
   config_file: ":/rtdetr_r50.yaml"
 - model_name: "rtmdet_m_coco_person_rtmo_m-r20240112"
diff --git a/anylabeling/configs/auto_labeling/rtdetrv2l.yaml b/anylabeling/configs/auto_labeling/rtdetrv2l.yaml
new file mode 100644
index 00000000..5768a564
--- /dev/null
+++ b/anylabeling/configs/auto_labeling/rtdetrv2l.yaml
@@ -0,0 +1,86 @@
+type: rtdetrv2
+name: rtdetrv2l-r20240730
+display_name: RT-DETRv2-L PaddleDetection
+model_path: https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.4.0/rtdetrv2_r50vd_6x_coco.onnx
+score_threshold: 0.45
+classes:
+  - person
+  - bicycle
+  - car
+  - motorcycle
+  - airplane
+  - bus
+  - train
+  - truck
+  - boat
+  - traffic light
+  - fire hydrant
+  - stop sign
+  - parking meter
+  - bench
+  - bird
+  - cat
+  - dog
+  - horse
+  - sheep
+  - cow
+  - elephant
+  - bear
+  - zebra
+  - giraffe
+  - backpack
+  - umbrella
+  - handbag
+  - tie
+  - suitcase
+  - frisbee
+  - skis
+  - snowboard
+  - sports ball
+  - kite
+  - baseball bat
+  - baseball glove
+  - skateboard
+  - surfboard
+  - tennis racket
+  - bottle
+  - wine glass
+  - cup
+  - fork
+  - knife
+  - spoon
+  - bowl
+  - banana
+  - apple
+  - sandwich
+  - orange
+  - broccoli
+  - carrot
+  - hot dog
+  - pizza
+  - donut
+  - cake
+  - chair
+  - couch
+  - potted plant
+  - bed
+  - dining table
+  - toilet
+  - tv
+  - laptop
+  - mouse
+  - remote
+  - keyboard
+  - cell phone
+  - microwave
+  - oven
+  - toaster
+  - sink
+  - refrigerator
+  - book
+  - clock
+  - vase
+  - scissors
+  - teddy bear
+  - hair drier
+  - toothbrush
diff --git a/anylabeling/configs/auto_labeling/rtdetrv2m.yaml b/anylabeling/configs/auto_labeling/rtdetrv2m.yaml
new file mode 100644
index 00000000..e0176180
--- /dev/null
+++ b/anylabeling/configs/auto_labeling/rtdetrv2m.yaml
@@ -0,0 +1,86 @@
+type: rtdetrv2
+name: rtdetrv2m-r20240730
+display_name: RT-DETRv2-M PaddleDetection
+model_path: https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.4.0/rtdetrv2_r34vd_120e_coco.onnx
+score_threshold: 0.45
+classes:
+  - person
+  - bicycle
+  - car
+  - motorcycle
+  - airplane
+  - bus
+  - train
+  - truck
+  - boat
+  - traffic light
+  - fire hydrant
+  - stop sign
+  - parking meter
+  - bench
+  - bird
+  - cat
+  - dog
+  - horse
+  - sheep
+  - cow
+  - elephant
+  - bear
+  - zebra
+  - giraffe
+  - backpack
+  - umbrella
+  - handbag
+  - tie
+  - suitcase
+  - frisbee
+  - skis
+  - snowboard
+  - sports ball
+  - kite
+  - baseball bat
+  - baseball glove
+  - skateboard
+  - surfboard
+  - tennis racket
+  - bottle
+  - wine glass
+  - cup
+  - fork
+  - knife
+  - spoon
+  - bowl
+  - banana
+  - apple
+  - sandwich
+  - orange
+  - broccoli
+  - carrot
+  - hot dog
+  - pizza
+  - donut
+  - cake
+  - chair
+  - couch
+  - potted plant
+  - bed
+  - dining table
+  - toilet
+  - tv
+  - laptop
+  - mouse
+  - remote
+  - keyboard
+  - cell phone
+  - microwave
+  - oven
+  - toaster
+  - sink
+  - refrigerator
+  - book
+  - clock
+  - vase
+  - scissors
+  - teddy bear
+  - hair drier
+  - toothbrush
diff --git a/anylabeling/configs/auto_labeling/rtdetrv2m7x.yaml b/anylabeling/configs/auto_labeling/rtdetrv2m7x.yaml
new file mode 100644
index 00000000..6c0f92cf
--- /dev/null
+++ b/anylabeling/configs/auto_labeling/rtdetrv2m7x.yaml
@@ -0,0 +1,86 @@
+type: rtdetrv2
+name: rtdetrv2m7x-r20240730
+display_name: RT-DETRv2-M* PaddleDetection
+model_path: https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.4.0/rtdetrv2_r50vd_m_7x_coco.onnx
+score_threshold: 0.45
+classes:
+  - person
+  - bicycle
+  - car
+  - motorcycle
+  - airplane
+  - bus
+  - train
+  - truck
+  - boat
+  - traffic light
+  - fire hydrant
+  - stop sign
+  - parking meter
+  - bench
+  - bird
+  - cat
+  - dog
+  - horse
+  - sheep
+  - cow
+  - elephant
+  - bear
+  - zebra
+  - giraffe
+  - backpack
+  - umbrella
+  - handbag
+  - tie
+  - suitcase
+  - frisbee
+  - skis
+  - snowboard
+  - sports ball
+  - kite
+  - baseball bat
+  - baseball glove
+  - skateboard
+  - surfboard
+  - tennis racket
+  - bottle
+  - wine glass
+  - cup
+  - fork
+  - knife
+  - spoon
+  - bowl
+  - banana
+  - apple
+  - sandwich
+  - orange
+  - broccoli
+  - carrot
+  - hot dog
+  - pizza
+  - donut
+  - cake
+  - chair
+  - couch
+  - potted plant
+  - bed
+  - dining table
+  - toilet
+  - tv
+  - laptop
+  - mouse
+  - remote
+  - keyboard
+  - cell phone
+  - microwave
+  - oven
+  - toaster
+  - sink
+  - refrigerator
+  - book
+  - clock
+  - vase
+  - scissors
+  - teddy bear
+  - hair drier
+  - toothbrush
diff --git a/anylabeling/configs/auto_labeling/rtdetrv2s.yaml b/anylabeling/configs/auto_labeling/rtdetrv2s.yaml
new file mode 100644
index 00000000..a76e88e6
--- /dev/null
+++ b/anylabeling/configs/auto_labeling/rtdetrv2s.yaml
@@ -0,0 +1,86 @@
+type: rtdetrv2
+name: rtdetrv2s-r20240730
+display_name: RT-DETRv2-S PaddleDetection
+model_path: https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.4.0/rtdetrv2_r18vd_120e_coco.onnx
+score_threshold: 0.45
+classes:
+  - person
+  - bicycle
+  - car
+  - motorcycle
+  - airplane
+  - bus
+  - train
+  - truck
+  - boat
+  - traffic light
+  - fire hydrant
+  - stop sign
+  - parking meter
+  - bench
+  - bird
+  - cat
+  - dog
+  - horse
+  - sheep
+  - cow
+  - elephant
+  - bear
+  - zebra
+  - giraffe
+  - backpack
+  - umbrella
+  - handbag
+  - tie
+  - suitcase
+  - frisbee
+  - skis
+  - snowboard
+  - sports ball
+  - kite
+  - baseball bat
+  - baseball glove
+  - skateboard
+  - surfboard
+  - tennis racket
+  - bottle
+  - wine glass
+  - cup
+  - fork
+  - knife
+  - spoon
+  - bowl
+  - banana
+  - apple
+  - sandwich
+  - orange
+  - broccoli
+  - carrot
+  - hot dog
+  - pizza
+  - donut
+  - cake
+  - chair
+  - couch
+  - potted plant
+  - bed
+  - dining table
+  - toilet
+  - tv
+  - laptop
+  - mouse
+  - remote
+  - keyboard
+  - cell phone
+  - microwave
+  - oven
+  - toaster
+  - sink
+  - refrigerator
+  - book
+  - clock
+  - vase
+  - scissors
+  - teddy bear
+  - hair drier
+  - toothbrush
diff --git a/anylabeling/configs/auto_labeling/rtdetrv2x.yaml b/anylabeling/configs/auto_labeling/rtdetrv2x.yaml
new file mode 100644
index 00000000..e08a77d7
--- /dev/null
+++ b/anylabeling/configs/auto_labeling/rtdetrv2x.yaml
@@ -0,0 +1,86 @@
+type: rtdetrv2
+name: rtdetrv2x-r20240730
+display_name: RT-DETRv2-X PaddleDetection
+model_path: https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.4.0/rtdetrv2_r101vd_6x_coco.onnx
+score_threshold: 0.45
+classes:
+  - person
+  - bicycle
+  - car
+  - motorcycle
+  - airplane
+  - bus
+  - train
+  - truck
+  - boat
+  - traffic light
+  - fire hydrant
+  - stop sign
+  - parking meter
+  - bench
+  - bird
+  - cat
+  - dog
+  - horse
+  - sheep
+  - cow
+  - elephant
+  - bear
+  - zebra
+  - giraffe
+  - backpack
+  - umbrella
+  - handbag
+  - tie
+  - suitcase
+  - frisbee
+  - skis
+  - snowboard
+  - sports ball
+  - kite
+  - baseball bat
+  - baseball glove
+  - skateboard
+  - surfboard
+  - tennis racket
+  - bottle
+  - wine glass
+  - cup
+  - fork
+  - knife
+  - spoon
+  - bowl
+  - banana
+  - apple
+  - sandwich
+  - orange
+  - broccoli
+  - carrot
+  - hot dog
+  - pizza
+  - donut
+  - cake
+  - chair
+  - couch
+  - potted plant
+  - bed
+  - dining table
+  - toilet
+  - tv
+  - laptop
+  - mouse
+  - remote
+  - keyboard
+  - cell phone
+  - microwave
+  - oven
+  - toaster
+  - sink
+  - refrigerator
+  - book
+  - clock
+  - vase
+  - scissors
+  - teddy bear
+  - hair drier
+  - toothbrush
diff --git a/anylabeling/services/auto_labeling/model_manager.py b/anylabeling/services/auto_labeling/model_manager.py
index f269e729..f618070f 100644
--- a/anylabeling/services/auto_labeling/model_manager.py
+++ b/anylabeling/services/auto_labeling/model_manager.py
@@ -64,6 +64,7 @@ class ModelManager(QObject):
         "yolov10",
         "depth_anything_v2",
         "yolow_ram",
+        "rtdetrv2",
     ]
 
     model_configs_changed = pyqtSignal(list)
@@ -1054,6 +1055,28 @@ def _load_model(self, model_id):
                     )
                 )
                 return
+        elif model_config["type"] == "rtdetrv2":
+            from .rtdetrv2 import RTDETRv2
+
+            try:
+                model_config["model"] = RTDETRv2(
+                    model_config, on_message=self.new_model_status.emit
+                )
+                self.auto_segmentation_model_unselected.emit()
+            except Exception as e:  # noqa
+                self.new_model_status.emit(
+                    self.tr(
+                        "Error in loading model: {error_message}".format(
+                            error_message=str(e)
+                        )
+                    )
+                )
+                print(
+                    "Error in loading model: {error_message}".format(
+                        error_message=str(e)
+                    )
+                )
+                return
         elif model_config["type"] == "yolov6_face":
             from .yolov6_face import YOLOv6Face
 
diff --git a/anylabeling/services/auto_labeling/rtdetrv2.py b/anylabeling/services/auto_labeling/rtdetrv2.py
new file mode 100644
index 00000000..e370038e
--- /dev/null
+++ b/anylabeling/services/auto_labeling/rtdetrv2.py
@@ -0,0 +1,150 @@
+import logging
+import os
+
+import cv2
+import numpy as np
+from PyQt5 import QtCore
+from PyQt5.QtCore import QCoreApplication
+
+from anylabeling.app_info import __preferred_device__
+from anylabeling.views.labeling.shape import Shape
+from anylabeling.views.labeling.utils.opencv import qt_img_to_rgb_cv_img
+from .model import Model
+from .types import AutoLabelingResult
+from .engines.build_onnx_engine import OnnxBaseModel
+from .utils.points_conversion import cxywh2xyxy
+
+
+class RTDETRv2(Model):
+    """Object detection model using RTDETRv2"""
+
+    class Meta:
+        required_config_names = [
+            "type",
+            "name",
+            "display_name",
+            "model_path",
+            "score_threshold",
+            "classes",
+        ]
+        widgets = [
+            "button_run",
+            "input_conf", 
+            "edit_conf",
+            "toggle_preserve_existing_annotations",
+        ]
+        output_modes = {
+            "rectangle": QCoreApplication.translate("Model", "Rectangle"),
+        }
+        default_output_mode = "rectangle"
+
+    def __init__(self, model_config, on_message) -> None:
+        # Run the parent class's init method
+        super().__init__(model_config, on_message)
+        model_name = self.config["type"]
+        model_abs_path = self.get_model_abs_path(self.config, "model_path")
+        if not model_abs_path or not os.path.isfile(model_abs_path):
+            raise FileNotFoundError(
+                QCoreApplication.translate(
+                    "Model",
+                    f"Could not download or initialize {model_name} model.",
+                )
+            )
+        self.net = OnnxBaseModel(model_abs_path, __preferred_device__)
+        self.classes = self.config["classes"]
+        self.input_shape = self.net.get_input_shape()[-2:]
+        self.conf_thres = self.config["score_threshold"]
+        self.replace = True
+
+    def set_auto_labeling_conf(self, value):
+        """ set auto labeling confidence threshold """
+        self.conf_thres = value
+
+    def set_auto_labeling_preserve_existing_annotations_state(self, state):
+        """ Toggle the preservation of existing annotations based on the checkbox state. """
+        self.replace = not state
+
+    def preprocess(self, input_image):
+        """
+        Pre-processes the input image before feeding it to the network.
+
+        Args:
+            input_image (numpy.ndarray): The input image to be processed.
+
+        Returns:
+            numpy.ndarray: The pre-processed output.
+        """
+        # Get the image width and height
+        image_h, image_w = input_image.shape[:2]
+        input_h, input_w = self.input_shape
+        # Perform the pre-processing steps
+        image = cv2.resize(input_image, (input_w, input_h))
+        image = image.transpose((2, 0, 1))  # HWC to CHW
+        image = np.ascontiguousarray(image).astype("float32")
+        image /= 255  # 0 - 255 to 0.0 - 1.0
+        if len(image.shape) == 3:
+            image = image[None]
+        orig_size = np.array([image_w, image_h], np.int64)[None, :]
+        blob = {"images": image, "orig_target_sizes": orig_size}
+        return blob
+
+    def postprocess(self, outputs):
+        """
+        Post-processes the network's output.
+
+        Args:
+            outputs (numpy.ndarray): The output from the network.
+
+        Returns:
+            scores (List[float]): prediction score
+            indexs (List[int]): category index
+            bboxes (List[list[int]]): xyxy format
+        """
+        indexs, boxes, scores = outputs
+        scores = scores[0]
+        indexs = indexs[0][scores > self.conf_thres]
+        bboxes = boxes[0][scores > self.conf_thres]
+
+        return scores, indexs, bboxes
+
+    def predict_shapes(self, image, image_path=None):
+        """
+        Predict shapes from image
+        """
+
+        if image is None:
+            return []
+
+        try:
+            image = qt_img_to_rgb_cv_img(image, image_path)
+        except Exception as e:  # noqa
+            logging.warning("Could not inference model")
+            logging.warning(e)
+            return []
+
+        blob = self.preprocess(image)
+        detections = self.net.get_ort_inference(
+            None, inputs=blob, extract=False
+        )
+        scores, indexs, bboxes = self.postprocess(detections)
+        shapes = []
+
+        for score, index, box in zip(scores, indexs, bboxes):
+            xmin, ymin, xmax, ymax = box
+            label = self.classes[int(index)]
+            shape = Shape(
+                label=str(label),
+                score=float(score),
+                shape_type="rectangle"
+            )
+            shape.add_point(QtCore.QPointF(xmin, ymin))
+            shape.add_point(QtCore.QPointF(xmax, ymin))
+            shape.add_point(QtCore.QPointF(xmax, ymax))
+            shape.add_point(QtCore.QPointF(xmin, ymax))
+            shapes.append(shape)
+
+        result = AutoLabelingResult(shapes, replace=self.replace)
+        return result
+
+    def unload(self):
+        del self.net
diff --git a/docs/en/model_zoo.md b/docs/en/model_zoo.md
index d50bc275..88f1a022 100644
--- a/docs/en/model_zoo.md
+++ b/docs/en/model_zoo.md
@@ -65,6 +65,11 @@
 | Gold_m_pre_dist.onnx | [Gold-YOLO](https://github.com/huawei-noah/Efficient-Computing/tree/master/Detection/Gold-YOLO)-COCO  | [gold_yolo_m.yaml](../../anylabeling/configs/auto_labeling/gold_yolo_m.yaml) | 169.88MB | [baidu](https://pan.baidu.com/s/1lY5VljoL9pZxadpe9DEUdQ?pwd=ephp) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.3.0/Gold_m_pre_dist.onnx) |
 | Gold_l_pre_dist.onnx | [Gold-YOLO](https://github.com/huawei-noah/Efficient-Computing/tree/master/Detection/Gold-YOLO)-COCO  | [gold_yolo_l.yaml](../../anylabeling/configs/auto_labeling/gold_yolo_l.yaml) | 286.79MB | [baidu](https://pan.baidu.com/s/1ySxB3R18oWuIdYzKRLrflg?pwd=1wlk) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.3.0/Gold_l_pre_dist.onnx) |
 | rtdetr_r50vd_6x_coco.onnx | [RT-DETR](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/rtdetr/README.md)-COCO  | [rtdetr_r50.yaml](../../anylabeling/configs/auto_labeling/rtdetr_r50.yaml)  | 160.96MB  | [baidu](https://pan.baidu.com/s/11vkwveTeZWwOFUpk8qrqVg?pwd=3sc4) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.1.0/rtdetr_r50vd_6x_coco.onnx) |
+| rtdetrv2_r101vd_6x_coco.onnx | [RT-DETRv2-X](https://github.com/lyuwenyu/RT-DETR/tree/main/rtdetrv2_pytorch)-COCO | [rtdetrv2x.yaml](../../anylabeling/configs/auto_labeling/rtdetrv2x.yaml) | 286.48MB | [baidu](https://pan.baidu.com/s/11lpaWt4IyFb39jJxKtlxnQ?pwd=t2kv) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.4.0/rtdetrv2_r101vd_6x_coco.onnx) |
+| rtdetrv2_r50vd_6x_coco.onnx | [RT-DETRv2-L](https://github.com/lyuwenyu/RT-DETR/tree/main/rtdetrv2_pytorch)-COCO | [rtdetrv2l.yaml](../../anylabeling/configs/auto_labeling/rtdetrv2l.yaml) | 161.38MB | [baidu](https://pan.baidu.com/s/1ex1fzc18wnIa7YREBGD3_g?pwd=qrab) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.4.0/rtdetrv2_r50vd_6x_coco.onnx) |
+| rtdetrv2_r50vd_m_7x_coco.onnx | [RT-DETRv2-M*](https://github.com/lyuwenyu/RT-DETR/tree/main/rtdetrv2_pytorch)-COCO | [rtdetrv2m7x.yaml](../../anylabeling/configs/auto_labeling/rtdetrv2m7x.yaml) | 126.52MB | [baidu](https://pan.baidu.com/s/1wzf6wJoysHfvAbgtv337oA?pwd=v8lw) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.4.0/rtdetrv2_r50vd_m_7x_coco.onnx) |
+| rtdetrv2_r34vd_120e_coco.onnx | [RT-DETRv2-M](https://github.com/lyuwenyu/RT-DETR/tree/main/rtdetrv2_pytorch)-COCO | [rtdetrv2m.yaml](../../anylabeling/configs/auto_labeling/rtdetrv2m.yaml) | 119.73MB | [baidu](https://pan.baidu.com/s/1ByaV67J7yBKtznvwHvtRiQ?pwd=oeny) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.4.0/rtdetrv2_r34vd_120e_coco.onnx) |
+| rtdetrv2_r18vd_120e_coco.onnx | [RT-DETRv2-S](https://github.com/lyuwenyu/RT-DETR/tree/main/rtdetrv2_pytorch)-COCO | [rtdetrv2s.yaml](../../anylabeling/configs/auto_labeling/rtdetrv2s.yaml) | 76.80MB | [baidu](https://pan.baidu.com/s/1jEuzrrn3P1GQcQ28qY-Q2Q?pwd=axm2) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.4.0/rtdetrv2_r18vd_120e_coco.onnx) |
 | yolo_nas_l.onnx | [YOLO-NAS](https://github.com/Deci-AI/super-gradients/tree/master)-COCO  | [yolo_nas_l.yaml](../../anylabeling/configs/auto_labeling/yolo_nas_l.yaml)  | 160.38MB  | [baidu](https://pan.baidu.com/s/1ckVfkul8ZckiQd3PfM-Htw?pwd=wmk8) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.1.0/yolo_nas_l.onnx) |
 | yolo_nas_m.onnx | [YOLO-NAS](https://github.com/Deci-AI/super-gradients/tree/master)-COCO  | [yolo_nas_m.yaml](../../anylabeling/configs/auto_labeling/yolo_nas_m.yaml)  | 121.87MB  | [baidu](https://pan.baidu.com/s/1bPH1m6dSxxG2KG3zrDywAA?pwd=1mlh) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.1.0/yolo_nas_m.onnx) |
 | yolo_nas_s.onnx | [YOLO-NAS](https://github.com/Deci-AI/super-gradients/tree/master)-COCO  | [yolo_nas_s.yaml](../../anylabeling/configs/auto_labeling/yolo_nas_s.yaml)  | 46.62MB  | [baidu](https://pan.baidu.com/s/1yA_n6QxJGXoR38xlY25q_w?pwd=4wdw) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.1.0/yolo_nas_s.onnx) |
@@ -90,10 +95,8 @@
 | yolov8x-oiv7.onnx | [YOLOv8](https://github.com/ultralytics/ultralytics)-Open Image V7 | [yolov8x_oiv7.yaml](../../anylabeling/configs/auto_labeling/yolov8x_oiv7.yaml) | 262.24MB | [baidu](https://pan.baidu.com/s/1in76UG8GhsXw6ACNqOVYKA?pwd=o07s) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.7/yolov8x-oiv7.onnx) |
 | yolov8l-oiv7.onnx | [YOLOv8](https://github.com/ultralytics/ultralytics)-Open Image V7 | [yolov8l_oiv7.yaml](../../anylabeling/configs/auto_labeling/yolov8l_oiv7.yaml) | 168.28MB | [baidu](https://pan.baidu.com/s/1p9-oYvkV-IXvy6RlTxLWfQ?pwd=fs07) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.7/yolov8l-oiv7.onnx) |
 | yolov8m-oiv7.onnx | [YOLOv8](https://github.com/ultralytics/ultralytics)-Open Image V7 | [yolov8m_oiv7.yaml](../../anylabeling/configs/auto_labeling/yolov8m_oiv7.yaml) | 100.05MB | [baidu](https://pan.baidu.com/s/1E7c-XIriTLH-gmBm5UmdWA?pwd=36n6) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.7/yolov8m-oiv7.onnx) |
-| yolov8s-oiv7.onnx | [YOLOv8](https://github.com/ultralytics/ultralytics)-Open Image V7 | 
-[yolov8s_oiv7.yaml](../../anylabeling/configs/auto_labeling/yolov8s_oiv7.yaml) | 43.47MB | [baidu](https://pan.baidu.com/s/1a6bP_x76Gk7LIf8uisWqfA?pwd=53lu) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.7/yolov8s-oiv7.onnx) |
-| yolov8n-oiv7.onnx | [YOLOv8](https://github.com/ultralytics/ultralytics)-Open Image V7 | 
-[yolov8n_oiv7.yaml](../../anylabeling/configs/auto_labeling/yolov8n_oiv7.yaml) | 13.47MB | [baidu](https://pan.baidu.com/s/1u8sUFr2LmBGwqZCbGb6Xww?pwd=l6ip) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.7/yolov8n-oiv7.onnx) |
+| yolov8s-oiv7.onnx | [YOLOv8](https://github.com/ultralytics/ultralytics)-Open Image V7 | [yolov8s_oiv7.yaml](../../anylabeling/configs/auto_labeling/yolov8s_oiv7.yaml) | 43.47MB | [baidu](https://pan.baidu.com/s/1a6bP_x76Gk7LIf8uisWqfA?pwd=53lu) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.7/yolov8s-oiv7.onnx) |
+| yolov8n-oiv7.onnx | [YOLOv8](https://github.com/ultralytics/ultralytics)-Open Image V7 | [yolov8n_oiv7.yaml](../../anylabeling/configs/auto_labeling/yolov8n_oiv7.yaml) | 13.47MB | [baidu](https://pan.baidu.com/s/1u8sUFr2LmBGwqZCbGb6Xww?pwd=l6ip) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.7/yolov8n-oiv7.onnx) |
 | yolov9c.onnx | [YOLOv9](https://github.com/WongKinYiu/yolov9)-COCO | [yolov9c.yaml](../../anylabeling/configs/auto_labeling/yolov9c.yaml) | 195.34MB | [baidu](https://pan.baidu.com/s/1iHZH29HE8s4fG8X7aHcn5g?pwd=zb5w) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.2/yolov9c.onnx) |
 | yolov9e.onnx | [YOLOv9](https://github.com/WongKinYiu/yolov9)-COCO | [yolov9e.yaml](../../anylabeling/configs/auto_labeling/yolov9e.yaml) | 265.43MB | [baidu](https://pan.baidu.com/s/1oJJQ1L5UfKi43kT96tauSA?pwd=vpa1) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.2/yolov9e.onnx) |
 | gelan-c.onnx | [YOLOv9](https://github.com/WongKinYiu/yolov9)-COCO | [gelan-c.yaml](../../anylabeling/configs/auto_labeling/yolov9_gelan_c.yaml) | 97.43MB | [baidu](https://pan.baidu.com/s/1cM0Tc056ICuA5jvesacCng?pwd=whb3) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.2/gelan-c.onnx) |
diff --git a/docs/zh_cn/model_zoo.md b/docs/zh_cn/model_zoo.md
index 98a1d43c..e0d0dcba 100644
--- a/docs/zh_cn/model_zoo.md
+++ b/docs/zh_cn/model_zoo.md
@@ -63,6 +63,11 @@
 | Gold_m_pre_dist.onnx | [Gold-YOLO](https://github.com/huawei-noah/Efficient-Computing/tree/master/Detection/Gold-YOLO)-COCO  | [gold_yolo_m.yaml](../../anylabeling/configs/auto_labeling/gold_yolo_m.yaml) | 169.88MB | [百度网盘](https://pan.baidu.com/s/1lY5VljoL9pZxadpe9DEUdQ?pwd=ephp) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.3.0/Gold_m_pre_dist.onnx) |
 | Gold_l_pre_dist.onnx | [Gold-YOLO](https://github.com/huawei-noah/Efficient-Computing/tree/master/Detection/Gold-YOLO)-COCO  | [gold_yolo_l.yaml](../../anylabeling/configs/auto_labeling/gold_yolo_l.yaml) | 286.79MB | [百度网盘](https://pan.baidu.com/s/1ySxB3R18oWuIdYzKRLrflg?pwd=1wlk) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.3.0/Gold_l_pre_dist.onnx) |
 | rtdetr_r50vd_6x_coco.onnx | [RT-DETR](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/rtdetr/README.md)-COCO  | [rtdetr_r50.yaml](../../anylabeling/configs/auto_labeling/rtdetr_r50.yaml)  | 160.96MB  | [百度网盘](https://pan.baidu.com/s/11vkwveTeZWwOFUpk8qrqVg?pwd=3sc4) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.1.0/rtdetr_r50vd_6x_coco.onnx) |
+| rtdetrv2_r101vd_6x_coco.onnx | [RT-DETRv2-X](https://github.com/lyuwenyu/RT-DETR/tree/main/rtdetrv2_pytorch)-COCO | [rtdetrv2x.yaml](../../anylabeling/configs/auto_labeling/rtdetrv2x.yaml) | 286.48MB | [百度网盘](https://pan.baidu.com/s/11lpaWt4IyFb39jJxKtlxnQ?pwd=t2kv) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.4.0/rtdetrv2_r101vd_6x_coco.onnx) |
+| rtdetrv2_r50vd_6x_coco.onnx | [RT-DETRv2-L](https://github.com/lyuwenyu/RT-DETR/tree/main/rtdetrv2_pytorch)-COCO | [rtdetrv2l.yaml](../../anylabeling/configs/auto_labeling/rtdetrv2l.yaml) | 161.38MB | [百度网盘](https://pan.baidu.com/s/1ex1fzc18wnIa7YREBGD3_g?pwd=qrab) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.4.0/rtdetrv2_r50vd_6x_coco.onnx) |
+| rtdetrv2_r50vd_m_7x_coco.onnx | [RT-DETRv2-M*](https://github.com/lyuwenyu/RT-DETR/tree/main/rtdetrv2_pytorch)-COCO | [rtdetrv2m7x.yaml](../../anylabeling/configs/auto_labeling/rtdetrv2m7x.yaml) | 126.52MB | [百度网盘](https://pan.baidu.com/s/1wzf6wJoysHfvAbgtv337oA?pwd=v8lw) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.4.0/rtdetrv2_r50vd_m_7x_coco.onnx) |
+| rtdetrv2_r34vd_120e_coco.onnx | [RT-DETRv2-M](https://github.com/lyuwenyu/RT-DETR/tree/main/rtdetrv2_pytorch)-COCO | [rtdetrv2m.yaml](../../anylabeling/configs/auto_labeling/rtdetrv2m.yaml) | 119.73MB | [百度网盘](https://pan.baidu.com/s/1ByaV67J7yBKtznvwHvtRiQ?pwd=oeny) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.4.0/rtdetrv2_r34vd_120e_coco.onnx) |
+| rtdetrv2_r18vd_120e_coco.onnx | [RT-DETRv2-S](https://github.com/lyuwenyu/RT-DETR/tree/main/rtdetrv2_pytorch)-COCO | [rtdetrv2s.yaml](../../anylabeling/configs/auto_labeling/rtdetrv2s.yaml) | 76.80MB | [百度网盘](https://pan.baidu.com/s/1jEuzrrn3P1GQcQ28qY-Q2Q?pwd=axm2) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.4.0/rtdetrv2_r18vd_120e_coco.onnx) |
 | yolo_nas_l.onnx | [YOLO-NAS](https://github.com/Deci-AI/super-gradients/tree/master)-COCO  | [yolo_nas_l.yaml](../../anylabeling/configs/auto_labeling/yolo_nas_l.yaml)  | 160.38MB  | [百度网盘](https://pan.baidu.com/s/1ckVfkul8ZckiQd3PfM-Htw?pwd=wmk8) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.1.0/yolo_nas_l.onnx) |
 | yolo_nas_m.onnx | [YOLO-NAS](https://github.com/Deci-AI/super-gradients/tree/master)-COCO  | [yolo_nas_m.yaml](../../anylabeling/configs/auto_labeling/yolo_nas_m.yaml)  | 121.87MB  | [百度网盘](https://pan.baidu.com/s/1bPH1m6dSxxG2KG3zrDywAA?pwd=1mlh) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.1.0/yolo_nas_m.onnx) |
 | yolo_nas_s.onnx | [YOLO-NAS](https://github.com/Deci-AI/super-gradients/tree/master)-COCO  | [yolo_nas_s.yaml](../../anylabeling/configs/auto_labeling/yolo_nas_s.yaml)  | 46.62MB  | [百度网盘](https://pan.baidu.com/s/1yA_n6QxJGXoR38xlY25q_w?pwd=4wdw) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v0.1.0/yolo_nas_s.onnx) |
@@ -88,10 +93,8 @@
 | yolov8x-oiv7.onnx | [YOLOv8](https://github.com/ultralytics/ultralytics)-Open Image V7 | [yolov8x_oiv7.yaml](../../anylabeling/configs/auto_labeling/yolov8x_oiv7.yaml) | 262.24MB | [百度网盘](https://pan.baidu.com/s/1in76UG8GhsXw6ACNqOVYKA?pwd=o07s) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.7/yolov8x-oiv7.onnx) |
 | yolov8l-oiv7.onnx | [YOLOv8](https://github.com/ultralytics/ultralytics)-Open Image V7 | [yolov8l_oiv7.yaml](../../anylabeling/configs/auto_labeling/yolov8l_oiv7.yaml) | 168.28MB | [百度网盘](https://pan.baidu.com/s/1p9-oYvkV-IXvy6RlTxLWfQ?pwd=fs07) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.7/yolov8l-oiv7.onnx) |
 | yolov8m-oiv7.onnx | [YOLOv8](https://github.com/ultralytics/ultralytics)-Open Image V7 | [yolov8m_oiv7.yaml](../../anylabeling/configs/auto_labeling/yolov8m_oiv7.yaml) | 100.05MB | [百度网盘](https://pan.baidu.com/s/1E7c-XIriTLH-gmBm5UmdWA?pwd=36n6) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.7/yolov8m-oiv7.onnx) |
-| yolov8s-oiv7.onnx | [YOLOv8](https://github.com/ultralytics/ultralytics)-Open Image V7 | 
-[yolov8s_oiv7.yaml](../../anylabeling/configs/auto_labeling/yolov8s_oiv7.yaml) | 43.47MB | [百度网盘](https://pan.baidu.com/s/1a6bP_x76Gk7LIf8uisWqfA?pwd=53lu) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.7/yolov8s-oiv7.onnx) |
-| yolov8n-oiv7.onnx | [YOLOv8](https://github.com/ultralytics/ultralytics)-Open Image V7 | 
-[yolov8n_oiv7.yaml](../../anylabeling/configs/auto_labeling/yolov8n_oiv7.yaml) | 13.47MB | [百度网盘](https://pan.baidu.com/s/1u8sUFr2LmBGwqZCbGb6Xww?pwd=l6ip) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.7/yolov8n-oiv7.onnx) |
+| yolov8s-oiv7.onnx | [YOLOv8](https://github.com/ultralytics/ultralytics)-Open Image V7 | [yolov8s_oiv7.yaml](../../anylabeling/configs/auto_labeling/yolov8s_oiv7.yaml) | 43.47MB | [百度网盘](https://pan.baidu.com/s/1a6bP_x76Gk7LIf8uisWqfA?pwd=53lu) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.7/yolov8s-oiv7.onnx) |
+| yolov8n-oiv7.onnx | [YOLOv8](https://github.com/ultralytics/ultralytics)-Open Image V7 | [yolov8n_oiv7.yaml](../../anylabeling/configs/auto_labeling/yolov8n_oiv7.yaml) | 13.47MB | [百度网盘](https://pan.baidu.com/s/1u8sUFr2LmBGwqZCbGb6Xww?pwd=l6ip) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.7/yolov8n-oiv7.onnx) |
 | yolov9c.onnx | [YOLOv9](https://github.com/WongKinYiu/yolov9)-COCO | [yolov9c.yaml](../../anylabeling/configs/auto_labeling/yolov9c.yaml) | 195.34MB | [百度网盘](https://pan.baidu.com/s/1iHZH29HE8s4fG8X7aHcn5g?pwd=zb5w) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.2/yolov9c.onnx) |
 | yolov9e.onnx | [YOLOv9](https://github.com/WongKinYiu/yolov9)-COCO | [yolov9e.yaml](../../anylabeling/configs/auto_labeling/yolov9e.yaml) | 265.43MB | [百度网盘](https://pan.baidu.com/s/1oJJQ1L5UfKi43kT96tauSA?pwd=vpa1) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.2/yolov9e.onnx) |
 | gelan-c.onnx | [YOLOv9](https://github.com/WongKinYiu/yolov9)-COCO | [gelan-c.yaml](../../anylabeling/configs/auto_labeling/yolov9_gelan_c.yaml) | 97.43MB | [百度网盘](https://pan.baidu.com/s/1cM0Tc056ICuA5jvesacCng?pwd=whb3) \| [github](https://github.com/CVHub520/X-AnyLabeling/releases/download/v2.3.2/gelan-c.onnx) |