✨ Visualization Initial Scaffold

model_api/python/model_api/models/__init__.py

@@ -11,7 +11,7 @@
 from .instance_segmentation import MaskRCNNModel
 from .keypoint_detection import KeypointDetectionModel, TopDownKeypointDetectionPipeline
 from .model import Model
-from .result_types import (
+from .result import (
     AnomalyResult,
     ClassificationResult,
     Contour,

model_api/python/model_api/models/action_classification.py

@@ -10,10 +10,10 @@
 import numpy as np
 
 from model_api.adapters.utils import RESIZE_TYPES, InputTransform
-from model_api.models.result_types import Label
+from model_api.models.result import Label
 
 from .model import Model
-from .result_types import ClassificationResult
+from .result import ClassificationResult
 from .types import BooleanValue, ListValue, NumericalValue, StringValue
 from .utils import load_labels
 

model_api/python/model_api/models/anomaly.py

@@ -15,7 +15,7 @@
 import numpy as np
 
 from model_api.models.image_model import ImageModel
-from model_api.models.result_types import AnomalyResult
+from model_api.models.result import AnomalyResult
 from model_api.models.types import ListValue, NumericalValue, StringValue
 
 if TYPE_CHECKING:

model_api/python/model_api/models/classification.py

@@ -17,7 +17,7 @@
 from openvino.runtime import opset10 as opset
 
 from model_api.models.image_model import ImageModel
-from model_api.models.result_types import ClassificationResult, Label
+from model_api.models.result import ClassificationResult, Label
 from model_api.models.types import BooleanValue, ListValue, NumericalValue, StringValue
 from model_api.models.utils import softmax
 

model_api/python/model_api/models/detection_model.py

@@ -6,7 +6,7 @@
 import numpy as np
 
 from .image_model import ImageModel
-from .result_types import DetectionResult
+from .result import DetectionResult
 from .types import ListValue, NumericalValue, StringValue
 from .utils import load_labels
 

model_api/python/model_api/models/instance_segmentation.py

@@ -9,7 +9,7 @@
 from model_api.adapters.inference_adapter import InferenceAdapter
 
 from .image_model import ImageModel
-from .result_types import InstanceSegmentationResult
+from .result import InstanceSegmentationResult
 from .types import BooleanValue, ListValue, NumericalValue, StringValue
 from .utils import load_labels
 

model_api/python/model_api/models/keypoint_detection.py

@@ -10,7 +10,7 @@
 import numpy as np
 
 from .image_model import ImageModel
-from .result_types import DetectedKeypoints, DetectionResult
+from .result import DetectedKeypoints, DetectionResult
 from .types import ListValue
 
 

model_api/python/model_api/models/result/__init__.py

@@ -0,0 +1,36 @@
+"""Model results."""
+
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+from .types import (
+    AnomalyResult,
+    ClassificationResult,
+    Contour,
+    DetectedKeypoints,
+    DetectionResult,
+    ImageResultWithSoftPrediction,
+    InstanceSegmentationResult,
+    Label,
+    PredictedMask,
+    Result,
+    RotatedSegmentationResult,
+    VisualPromptingResult,
+    ZSLVisualPromptingResult,
+)
+
+__all__ = [
+    "AnomalyResult",
+    "ClassificationResult",
+    "Contour",
+    "DetectionResult",
+    "DetectedKeypoints",
+    "ImageResultWithSoftPrediction",
+    "InstanceSegmentationResult",
+    "Label",
+    "PredictedMask",
+    "Result",
+    "VisualPromptingResult",
+    "ZSLVisualPromptingResult",
+    "RotatedSegmentationResult",
+]

model_api/python/model_api/models/result/scene/__init__.py

@@ -0,0 +1,4 @@
+"""Result visualization Scene."""
+
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0

model_api/python/model_api/models/result_types/__init__.py → model_api/python/model_api/models/result/types/__init__.py

@@ -4,6 +4,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 from .anomaly import AnomalyResult
+from .base import Result
 from .classification import ClassificationResult, Label
 from .detection import DetectionResult
 from .keypoint import DetectedKeypoints
@@ -25,6 +26,7 @@
     "ImageResultWithSoftPrediction",
     "InstanceSegmentationResult",
     "PredictedMask",
+    "Result",
     "VisualPromptingResult",
     "ZSLVisualPromptingResult",
     "RotatedSegmentationResult",

model_api/python/model_api/models/result_types/anomaly.py → model_api/python/model_api/models/result/types/anomaly.py

@@ -7,8 +7,10 @@
 
 import numpy as np
 
+from .base import Result
 
-class AnomalyResult:
+
+class AnomalyResult(Result):
     """Results for anomaly models."""
 
     def __init__(

model_api/python/model_api/models/result/types/base.py

@@ -0,0 +1,10 @@
+"""Base result type"""
+
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+from abc import ABC
+
+
+class Result(ABC):
+    """Base result type."""

model_api/python/model_api/models/result_types/classification.py → model_api/python/model_api/models/result/types/classification.py

@@ -7,6 +7,7 @@
 
 from typing import TYPE_CHECKING, Generator
 
+from .base import Result
 from .utils import array_shape_to_str
 
 if TYPE_CHECKING:
@@ -35,7 +36,7 @@ def __str__(self) -> str:
         return f"{self.id} ({self.name}): {self.confidence:.3f}"
 
 
-class ClassificationResult:
+class ClassificationResult(Result):
     """Results for classification models."""
 
     def __init__(

model_api/python/model_api/models/result_types/detection.py → model_api/python/model_api/models/result/types/detection.py

@@ -7,10 +7,11 @@
 
 import numpy as np
 
+from .base import Result
 from .utils import array_shape_to_str
 
 
-class DetectionResult:
+class DetectionResult(Result):
     """Result for detection model.
 
     Args:

model_api/python/model_api/models/result_types/keypoint.py → model_api/python/model_api/models/result/types/keypoint.py

@@ -5,8 +5,10 @@
 
 import numpy as np
 
+from .base import Result
 
-class DetectedKeypoints:
+
+class DetectedKeypoints(Result):
     def __init__(self, keypoints: np.ndarray, scores: np.ndarray) -> None:
         self.keypoints = keypoints
         self.scores = scores

model_api/python/model_api/models/result_types/segmentation.py → model_api/python/model_api/models/result/types/segmentation.py

@@ -10,6 +10,7 @@
 import cv2
 import numpy as np
 
+from .base import Result
 from .detection import DetectionResult
 from .utils import array_shape_to_str
 
@@ -157,7 +158,7 @@ def __str__(self):
         return f"{self.label}: {self.probability:.3f}, {len(self.shape)}"
 
 
-class ImageResultWithSoftPrediction:
+class ImageResultWithSoftPrediction(Result):
     def __init__(
         self,
         resultImage: np.ndarray,

model_api/python/model_api/models/result_types/visual_prompting.py → model_api/python/model_api/models/result/types/visual_prompting.py

@@ -7,8 +7,10 @@
 
 import numpy as np
 
+from .base import Result
 
-class VisualPromptingResult:
+
+class VisualPromptingResult(Result):
     def __init__(
         self,
         upscaled_masks: list[np.ndarray] | None = None,
@@ -79,7 +81,7 @@ def __str__(self) -> str:
         return obj_str.strip()
 
 
-class ZSLVisualPromptingResult:
+class ZSLVisualPromptingResult(Result):
     def __init__(self, data: dict[int, PredictedMask]) -> None:
         self.data = data
 

model_api/python/model_api/models/segmentation.py

@@ -11,7 +11,7 @@
 import numpy as np
 
 from model_api.models.image_model import ImageModel
-from model_api.models.result_types import Contour, ImageResultWithSoftPrediction
+from model_api.models.result import Contour, ImageResultWithSoftPrediction
 from model_api.models.types import BooleanValue, ListValue, NumericalValue, StringValue
 from model_api.models.utils import load_labels
 

model_api/python/model_api/models/ssd.py

@@ -6,7 +6,7 @@
 import numpy as np
 
 from .detection_model import DetectionModel
-from .result_types import DetectionResult
+from .result import DetectionResult
 
 BBOX_AREA_THRESHOLD = 1.0
 SALIENCY_MAP_NAME = "saliency_map"

model_api/python/model_api/models/utils.py

@@ -11,10 +11,10 @@
 import cv2
 import numpy as np
 
-from model_api.models.result_types import Contour, InstanceSegmentationResult, RotatedSegmentationResult
+from model_api.models.result import Contour, InstanceSegmentationResult, RotatedSegmentationResult
 
 if TYPE_CHECKING:
-    from model_api.models.result_types.detection import DetectionResult
+    from model_api.models.result.detection import DetectionResult
 
 
 def add_rotated_rects(inst_seg_result: InstanceSegmentationResult) -> RotatedSegmentationResult:

model_api/python/model_api/models/yolo.py

@@ -10,7 +10,7 @@
 from model_api.adapters.utils import INTERPOLATION_TYPES, resize_image_ocv
 
 from .detection_model import DetectionModel
-from .result_types import DetectionResult
+from .result import DetectionResult
 from .types import BooleanValue, ListValue, NumericalValue
 from .utils import clip_detections, multiclass_nms, nms
 

model_api/python/model_api/visualizer/__init__.py

@@ -0,0 +1,9 @@
+"""Visualizer."""
+
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+from .scene import Scene
+from .visualizer import Visualizer
+
+__all__ = ["Scene", "Visualizer"]

model_api/python/model_api/visualizer/layout.py

@@ -0,0 +1,28 @@
+"""Visualization Layout"""
+
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+from __future__ import annotations
+
+from abc import ABC
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    import PIL
+
+    from model_api.visualizer.primitive import Primitive
+
+    from .scene import Scene
+
+
+class Layout(ABC):
+    """Base class for layouts."""
+
+    def _compute_on_primitive(self, primitive: Primitive, image: PIL.Image, scene: Scene) -> PIL.Image | None:
+        if scene.has_primitives(type(primitive)):
+            primitives = scene.get_primitives(type(primitive))
+            for primitive in primitives:
+                image = primitive.compute(image)
+            return image
+        return None

model_api/python/model_api/visualizer/primitive.py

@@ -0,0 +1,20 @@
+"""Base class for primitives."""
+
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    import PIL
+
+
+class Primitive(ABC):
+    """Primitive class."""
+
+    @abstractmethod
+    def compute(self, image: PIL.Image, **kwargs) -> PIL.Image:
+        pass

model_api/python/model_api/visualizer/scene.py

@@ -0,0 +1,40 @@
+"""Scene object."""
+
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+from abc import abstractmethod
+from typing import Type, Union
+
+import PIL
+
+from .layout import Layout
+from .primitive import Primitive
+
+
+class Scene:
+    """Scene object.
+
+    Used by the visualizer to render.
+    """
+
+    def __init__(
+        self,
+        base: PIL.Image,
+        layout: Union[Layout, list[Layout], None] = None,
+    ) -> None: ...
+
+    def show(self) -> PIL.Image: ...
+
+    def save(self, path: str) -> None: ...
+
+    def has_primitives(self, primitive: Type[Primitive]) -> bool:
+        return False
+
+    def get_primitives(self, primitive: Type[Primitive]) -> list[Primitive]:
+        return []
+
+    @property
+    @abstractmethod
+    def default_layout(self) -> Layout:
+        """Default layout for the media."""

model_api/python/model_api/visualizer/visualizer.py

@@ -0,0 +1,12 @@
+"""Visualizer for modelAPI."""
+
+# Copyright (C) 2024 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import PIL
+
+from model_api.models.result import Result
+
+
+class Visualizer:
+    def show(self, image: PIL.Image, result: Result) -> PIL.Image: ...

model_api/python/pyproject.toml

@@ -30,6 +30,7 @@ dependencies = [
     "openvino>=2024.0",
     "openvino-dev>=2024.0",
     "omz_tools @ git+https://github.com/openvinotoolkit/open_model_zoo.git@master#egg=omz_tools&subdirectory=tools/model_tools",
+    "pillow",
 ]
 
 [project.optional-dependencies]

tests/python/unit/results/test_cls_result.py

@@ -4,7 +4,7 @@
 #
 
 import numpy as np
-from model_api.models.result_types import ClassificationResult, Label
+from model_api.models.result import ClassificationResult, Label
 
 
 def test_cls_result():