chore: import upstream snapshot with attribution

invokeai/backend/image_util/segment_anything/shared.py

@@ -0,0 +1,49 @@
+from enum import Enum
+
+from pydantic import BaseModel, model_validator
+from pydantic.fields import Field
+
+
+class BoundingBox(BaseModel):
+    x_min: int = Field(..., description="The minimum x-coordinate of the bounding box (inclusive).")
+    x_max: int = Field(..., description="The maximum x-coordinate of the bounding box (exclusive).")
+    y_min: int = Field(..., description="The minimum y-coordinate of the bounding box (inclusive).")
+    y_max: int = Field(..., description="The maximum y-coordinate of the bounding box (exclusive).")
+
+    @model_validator(mode="after")
+    def check_coords(self):
+        if self.x_min > self.x_max:
+            raise ValueError(f"x_min ({self.x_min}) is greater than x_max ({self.x_max}).")
+        if self.y_min > self.y_max:
+            raise ValueError(f"y_min ({self.y_min}) is greater than y_max ({self.y_max}).")
+        return self
+
+    def tuple(self) -> tuple[int, int, int, int]:
+        """
+        Returns the bounding box as a tuple suitable for use with PIL's `Image.crop()` method.
+        This method returns a tuple of the form (left, upper, right, lower) == (x_min, y_min, x_max, y_max).
+        """
+        return (self.x_min, self.y_min, self.x_max, self.y_max)
+
+
+class SAMPointLabel(Enum):
+    negative = -1
+    neutral = 0
+    positive = 1
+
+
+class SAMPoint(BaseModel):
+    x: int = Field(..., description="The x-coordinate of the point")
+    y: int = Field(..., description="The y-coordinate of the point")
+    label: SAMPointLabel = Field(..., description="The label of the point")
+
+
+class SAMInput(BaseModel):
+    bounding_box: BoundingBox | None = Field(None, description="The bounding box to use for segmentation")
+    points: list[SAMPoint] | None = Field(None, description="The points to use for segmentation")
+
+    @model_validator(mode="after")
+    def check_input(self):
+        if not self.bounding_box and not self.points:
+            raise ValueError("Either bounding_box or points must be provided")
+        return self