Support YOLOv8 deploy (#456)

projects/easydeploy/backbone/__init__.py

 # Copyright (c) OpenMMLab. All rights reserved.
+from .common import DeployC2f
 from .focus import DeployFocus, GConvFocus, NcnnFocus
 
-__all__ = ['DeployFocus', 'NcnnFocus', 'GConvFocus']
+__all__ = ['DeployFocus', 'NcnnFocus', 'GConvFocus', 'DeployC2f']

projects/easydeploy/backbone/common.py

+import torch
+import torch.nn as nn
+from torch import Tensor
+
+class DeployC2f(nn.Module):
+
+    def __init__(self, *args, **kwargs):
+        super().__init__()
+
+    def forward(self, x: Tensor) -> Tensor:
+        x_main = self.main_conv(x)
+        x_main = [x_main, x_main[:,self.mid_channels:,...]]
+        x_main.extend(blocks(x_main[-1]) for blocks in self.blocks)
+        x_main.pop(1)
+        return self.final_conv(torch.cat(x_main, 1))

projects/easydeploy/model/model.py

@@ -11,7 +11,8 @@ from torch import Tensor
 from mmyolo.models import RepVGGBlock
 from mmyolo.models.dense_heads import (RTMDetHead, YOLOv5Head, YOLOv7Head,
                                        YOLOXHead)
-from ..backbone import DeployFocus, GConvFocus, NcnnFocus
+from mmyolo.models.layers import CSPLayerWithTwoConv
+from ..backbone import DeployC2f, DeployFocus, GConvFocus, NcnnFocus
 from ..bbox_code import (rtmdet_bbox_decoder, yolov5_bbox_decoder,
                          yolox_bbox_decoder)
 from ..nms import batched_nms, efficient_nms, onnx_nms
@@ -49,7 +50,7 @@ class DeployModel(nn.Module):
         for layer in self.baseModel.modules():
             if isinstance(layer, RepVGGBlock):
                 layer.switch_to_deploy()
-            if isinstance(layer, Focus):
+            elif isinstance(layer, Focus):
                 # onnxruntime tensorrt8 tensorrt7
                 if self.backend in (1, 2, 3):
                     self.baseModel.backbone.stem = DeployFocus(layer)
@@ -59,6 +60,8 @@ class DeployModel(nn.Module):
                 # switch focus to group conv
                 else:
                     self.baseModel.backbone.stem = GConvFocus(layer)
+            elif isinstance(layer, CSPLayerWithTwoConv):
+                setattr(layer, '__class__', DeployC2f)
 
     def pred_by_feat(self,
                      cls_scores: List[Tensor],

projects/easydeploy/tools/export.py

@@ -16,6 +16,7 @@ warnings.filterwarnings(action='ignore', category=torch.jit.TracerWarning)
 warnings.filterwarnings(action='ignore', category=torch.jit.ScriptWarning)
 warnings.filterwarnings(action='ignore', category=UserWarning)
 warnings.filterwarnings(action='ignore', category=FutureWarning)
+warnings.filterwarnings(action='ignore', category=ResourceWarning)
 
 
 def parse_args():

projects/easydeploy/tools/image-demo.py

 # Copyright (c) OpenMMLab. All rights reserved.
+from projects.easydeploy.model import ORTWrapper, TRTWrapper  # isort:skip
 import os
 import random
 from argparse import ArgumentParser
@@ -15,8 +16,6 @@ from mmengine.utils import ProgressBar, path
 from mmyolo.utils import register_all_modules
 from mmyolo.utils.misc import get_file_list
 
-from projects.easydeploy.model import ORTWrapper, TRTWrapper  # isort:skip
-
 
 def parse_args():
     parser = ArgumentParser()