Add missing mean std propagation to mmdeploy exporter

Signed-off-by: Kim, Vinnam <[email protected]>
openvinotoolkit · Apr 9, 2024 · 4fda8cb · 4fda8cb
1 parent fd0c9a1
commit 4fda8cb
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Showing 6 changed files with 38 additions and 0 deletions.
diff --git a/src/otx/algo/detection/atss.py b/src/otx/algo/detection/atss.py
@@ -16,6 +16,7 @@
 from otx.core.model.base import DefaultOptimizerCallable, DefaultSchedulerCallable
 from otx.core.model.detection import MMDetCompatibleModel
 from otx.core.schedulers import LRSchedulerListCallable
+from otx.core.utils.utils import get_mean_std_from_data_processing
 
 if TYPE_CHECKING:
     from lightning.pytorch.cli import LRSchedulerCallable, OptimizerCallable
@@ -54,13 +55,17 @@ def _exporter(self) -> OTXModelExporter:
         if self.image_size is None:
             raise ValueError(self.image_size)
 
+        mean, std = get_mean_std_from_data_processing(self.config)
+
         return MMdeployExporter(
             model_builder=self._create_model,
             model_cfg=deepcopy(self.config),
             deploy_cfg="otx.algo.detection.mmdeploy.atss",
             test_pipeline=self._make_fake_test_pipeline(),
             task_level_export_parameters=self._export_parameters,
             input_size=self.image_size,
+            mean=mean,
+            std=std,
             resize_mode="standard",
             pad_value=0,
             swap_rgb=False,

diff --git a/src/otx/algo/detection/rtmdet.py b/src/otx/algo/detection/rtmdet.py
@@ -16,6 +16,7 @@
 from otx.core.model.base import DefaultOptimizerCallable, DefaultSchedulerCallable
 from otx.core.model.detection import MMDetCompatibleModel
 from otx.core.schedulers import LRSchedulerListCallable
+from otx.core.utils.utils import get_mean_std_from_data_processing
 
 if TYPE_CHECKING:
     from lightning.pytorch.cli import LRSchedulerCallable, OptimizerCallable
@@ -54,13 +55,17 @@ def _exporter(self) -> OTXModelExporter:
         if self.image_size is None:
             raise ValueError(self.image_size)
 
+        mean, std = get_mean_std_from_data_processing(self.config)
+
         return MMdeployExporter(
             model_builder=self._create_model,
             model_cfg=deepcopy(self.config),
             deploy_cfg="otx.algo.detection.mmdeploy.rtmdet",
             test_pipeline=self._make_fake_test_pipeline(),
             task_level_export_parameters=self._export_parameters,
             input_size=self.image_size,
+            mean=mean,
+            std=std,
             resize_mode="fit_to_window_letterbox",
             pad_value=114,
             swap_rgb=False,

diff --git a/src/otx/algo/detection/ssd.py b/src/otx/algo/detection/ssd.py
@@ -21,6 +21,7 @@
 from otx.core.model.detection import MMDetCompatibleModel
 from otx.core.schedulers import LRSchedulerListCallable
 from otx.core.utils.build import build_mm_model, modify_num_classes
+from otx.core.utils.utils import get_mean_std_from_data_processing
 
 if TYPE_CHECKING:
     import torch
@@ -269,13 +270,17 @@ def _exporter(self) -> OTXModelExporter:
         if self.image_size is None:
             raise ValueError(self.image_size)
 
+        mean, std = get_mean_std_from_data_processing(self.config)
+
         return MMdeployExporter(
             model_builder=self._create_model,
             model_cfg=deepcopy(self.config),
             deploy_cfg="otx.algo.detection.mmdeploy.ssd_mobilenetv2",
             test_pipeline=self._make_fake_test_pipeline(),
             task_level_export_parameters=self._export_parameters,
             input_size=self.image_size,
+            mean=mean,
+            std=std,
             resize_mode="standard",
             pad_value=0,
             swap_rgb=False,

diff --git a/src/otx/algo/detection/yolox.py b/src/otx/algo/detection/yolox.py
@@ -16,6 +16,7 @@
 from otx.core.model.base import DefaultOptimizerCallable, DefaultSchedulerCallable
 from otx.core.model.detection import MMDetCompatibleModel
 from otx.core.schedulers import LRSchedulerListCallable
+from otx.core.utils.utils import get_mean_std_from_data_processing
 
 if TYPE_CHECKING:
     from lightning.pytorch.cli import LRSchedulerCallable, OptimizerCallable
@@ -54,13 +55,17 @@ def _exporter(self) -> OTXModelExporter:
         if self.image_size is None:
             raise ValueError(self.image_size)
 
+        mean, std = get_mean_std_from_data_processing(self.config)
+
         return MMdeployExporter(
             model_builder=self._create_model,
             model_cfg=deepcopy(self.config),
             deploy_cfg="otx.algo.detection.mmdeploy.yolox",
             test_pipeline=self._make_fake_test_pipeline(),
             task_level_export_parameters=self._export_parameters,
             input_size=self.image_size,
+            mean=mean,
+            std=std,
             resize_mode="fit_to_window_letterbox",
             pad_value=114,
             swap_rgb=True,
@@ -102,13 +107,17 @@ def _exporter(self) -> OTXModelExporter:
         if self.image_size is None:
             raise ValueError(self.image_size)
 
+        mean, std = get_mean_std_from_data_processing(self.config)
+
         return MMdeployExporter(
             model_builder=self._create_model,
             model_cfg=deepcopy(self.config),
             deploy_cfg="otx.algo.detection.mmdeploy.yolox_tiny",
             test_pipeline=self._make_fake_test_pipeline(),
             task_level_export_parameters=self._export_parameters,
             input_size=self.image_size,
+            mean=mean,
+            std=std,
             resize_mode="fit_to_window_letterbox",
             pad_value=114,
             swap_rgb=False,

diff --git a/src/otx/algo/instance_segmentation/maskrcnn.py b/src/otx/algo/instance_segmentation/maskrcnn.py
@@ -16,6 +16,7 @@
 from otx.core.model.base import DefaultOptimizerCallable, DefaultSchedulerCallable
 from otx.core.model.instance_segmentation import MMDetInstanceSegCompatibleModel
 from otx.core.schedulers import LRSchedulerListCallable
+from otx.core.utils.utils import get_mean_std_from_data_processing
 
 if TYPE_CHECKING:
     from lightning.pytorch.cli import LRSchedulerCallable, OptimizerCallable
@@ -54,13 +55,17 @@ def _exporter(self) -> OTXModelExporter:
         if self.image_size is None:
             raise ValueError(self.image_size)
 
+        mean, std = get_mean_std_from_data_processing(self.config)
+
         return MMdeployExporter(
             model_builder=self._create_model,
             model_cfg=deepcopy(self.config),
             deploy_cfg="otx.algo.instance_segmentation.mmdeploy.maskrcnn",
             test_pipeline=self._make_fake_test_pipeline(),
             task_level_export_parameters=self._export_parameters,
             input_size=self.image_size,
+            mean=mean,
+            std=std,
             resize_mode="standard",  # [TODO](@Eunwoo): need to revert it to fit_to_window after resolving
             pad_value=0,
             swap_rgb=False,
@@ -102,13 +107,17 @@ def _exporter(self) -> OTXModelExporter:
         if self.image_size is None:
             raise ValueError(self.image_size)
 
+        mean, std = get_mean_std_from_data_processing(self.config)
+
         return MMdeployExporter(
             model_builder=self._create_model,
             model_cfg=deepcopy(self.config),
             deploy_cfg="otx.algo.instance_segmentation.mmdeploy.maskrcnn_swint",
             test_pipeline=self._make_fake_test_pipeline(),
             task_level_export_parameters=self._export_parameters,
             input_size=self.image_size,
+            mean=mean,
+            std=std,
             resize_mode="standard",  # [TODO](@Eunwoo): need to revert it to fit_to_window after resolving
             pad_value=0,
             swap_rgb=False,

diff --git a/src/otx/algo/instance_segmentation/rtmdet_inst.py b/src/otx/algo/instance_segmentation/rtmdet_inst.py
@@ -15,6 +15,7 @@
 from otx.core.model.base import DefaultOptimizerCallable, DefaultSchedulerCallable
 from otx.core.model.instance_segmentation import MMDetInstanceSegCompatibleModel
 from otx.core.schedulers import LRSchedulerListCallable
+from otx.core.utils.utils import get_mean_std_from_data_processing
 
 if TYPE_CHECKING:
     from lightning.pytorch.cli import LRSchedulerCallable, OptimizerCallable
@@ -53,13 +54,17 @@ def _exporter(self) -> OTXModelExporter:
         if self.image_size is None:
             raise ValueError(self.image_size)
 
+        mean, std = get_mean_std_from_data_processing(self.config)
+
         return MMdeployExporter(
             model_builder=self._create_model,
             model_cfg=deepcopy(self.config),
             deploy_cfg="otx.algo.instance_segmentation.mmdeploy.rtmdet_inst",
             test_pipeline=self._make_fake_test_pipeline(),
             task_level_export_parameters=self._export_parameters,
             input_size=self.image_size,
+            mean=mean,
+            std=std,
             resize_mode="fit_to_window_letterbox",
             pad_value=114,
             swap_rgb=False,