Move OV semantic segmentation tiler to use MAPI (#3978)

* Use sseg tiler from MAPI

* Upgrade MAPI

* Update seg tiling tests

pyproject.toml

@@ -80,7 +80,7 @@ xpu = [
     "timm==1.0.3",
     "openvino==2024.4",
     "openvino-dev==2024.4",
-    "openvino-model-api==0.2.3",
+    "openvino-model-api==0.2.4",
     "onnx==1.16.2",
     "onnxconverter-common==1.14.0",
     "nncf==2.13.0",
@@ -94,7 +94,7 @@ base = [
     "timm==1.0.3",
     "openvino==2024.4",
     "openvino-dev==2024.4",
-    "openvino-model-api==0.2.3",
+    "openvino-model-api==0.2.4",
     "onnx==1.16.2",
     "onnxconverter-common==1.14.0",
     "nncf==2.13.0",

src/otx/core/exporter/exportable_code/demo/requirements.txt

@@ -1,3 +1,3 @@
 openvino==2024.4.0
-openvino-model-api==0.2.3
+openvino-model-api==0.2.4
 numpy==1.26.4

src/otx/core/model/segmentation.py

@@ -13,6 +13,7 @@
 
 import torch
 import torch.nn.functional as f
+from model_api.tilers import SemanticSegmentationTiler
 from torch import nn
 from torchvision import tv_tensors
 
@@ -26,7 +27,6 @@
 from otx.core.metrics import MetricInput
 from otx.core.metrics.dice import SegmCallable
 from otx.core.model.base import DefaultOptimizerCallable, DefaultSchedulerCallable, OTXModel, OVModel
-from otx.core.model.seg_tiler import SegTiler
 from otx.core.schedulers import LRSchedulerListCallable
 from otx.core.types.export import OTXExportFormatType, TaskLevelExportParameters
 from otx.core.types.label import LabelInfo, LabelInfoTypes, SegLabelInfo
@@ -360,7 +360,7 @@ def _setup_tiler(self) -> None:
         execution_mode = "async" if self.async_inference else "sync"
         # Note: Disable async_inference as tiling has its own sync/async implementation
         self.async_inference = False
-        self.model = SegTiler(self.model, execution_mode=execution_mode)
+        self.model = SemanticSegmentationTiler(self.model, execution_mode=execution_mode)
         log.info(
             f"Enable tiler with tile size: {self.model.tile_size} \
                 and overlap: {self.model.tiles_overlap}",

tests/unit/core/data/test_tiling.py

@@ -15,6 +15,7 @@
 from datumaro import Polygon
 from model_api.models import Model
 from model_api.models.utils import ImageResultWithSoftPrediction
+from model_api.tilers import SemanticSegmentationTiler
 from omegaconf import OmegaConf
 from otx.algo.detection.atss import ATSS
 from otx.algo.instance_segmentation.maskrcnn import MaskRCNN
@@ -31,7 +32,6 @@
 from otx.core.data.entity.tile import TileBatchDetDataEntity, TileBatchInstSegDataEntity, TileBatchSegDataEntity
 from otx.core.data.module import OTXDataModule
 from otx.core.model.detection import OTXDetectionModel
-from otx.core.model.seg_tiler import SegTiler
 from otx.core.types.task import OTXTaskType
 from otx.core.types.transformer_libs import TransformLibType
 from torchvision import tv_tensors
@@ -522,11 +522,11 @@ def test_seg_tiler(self, mocker):
 
         mock_model = MagicMock(spec=Model)
         mocker.patch("model_api.tilers.tiler.Tiler.__init__", return_value=None)
-        mocker.patch.multiple(SegTiler, __abstractmethods__=set())
+        mocker.patch.multiple(SemanticSegmentationTiler, __abstractmethods__=set())
 
         num_labels = rng.integers(low=1, high=10)
 
-        tiler = SegTiler(model=mock_model)
+        tiler = SemanticSegmentationTiler(model=mock_model)
         tiler.model = mock_model
         tiler.model.labels = [f"label{i}" for i in range(num_labels)]
         tiler.tile_with_full_img = True