Support transmitting partial tiles/crops of the canvas in Krita workflows

Author: Acly

krita.py

@@ -90,9 +90,11 @@ def define_schema(cls):
             category="krita",
             inputs=[
                 io.Image.Input("images"),
+                io.Int.Input("x", "offset x", default=0),
+                io.Int.Input("y", "offset y", default=0),
                 io.String.Input("name", default=""),
                 io.Combo.Input(
-                    "batch_mode", OutputBatchMode, "batch_mode", default=OutputBatchMode.default
+                    "batch_mode", OutputBatchMode, "batch mode", default=OutputBatchMode.default
                 ),
                 io.Boolean.Input("resize_canvas", "resize canvas", default=False),
             ],
@@ -103,13 +105,17 @@ def define_schema(cls):
     def execute(
         cls,
         images: torch.Tensor,
+        x: int = 0,
+        y: int = 0,
         name="",
         batch_mode: OutputBatchMode | str = OutputBatchMode.default,
         resize_canvas=False,
     ):
         batch_mode = batch_mode.value if isinstance(batch_mode, OutputBatchMode) else batch_mode
         info = {
             "name": name,
+            "offset_x": x,
+            "offset_y": y,
             "batch_mode": batch_mode,
             "resize_canvas": resize_canvas,
         }
@@ -171,19 +177,48 @@ def execute(cls):
         return io.NodeOutput(_placeholder_image(), 512, 512, 0)
 
 
+class SelectionContext(Enum):
+    automatic = "automatic"
+    entire_image = "entire image"
+    mask_bounds = "mask bounds"
+
+
+_selection_context_help = """
+Determines the section (crop bounding box) of the image and mask to transmit:
+- automatic: area around the selection determined by Krita settings
+- entire image: always use the entire canvas area
+- mask bounds: tight bounding box of the current selection
+
+This affects the Selection and Canvas nodes. The offset x/y outputs indicate the top-left corner of the context area relative to the full canvas."""
+
+
 class KritaSelection(io.ComfyNode):
     @classmethod
     def define_schema(cls):
         return io.Schema(
             node_id="ETN_KritaSelection",
             display_name="Krita Selection",
             category="krita",
-            outputs=[io.Mask.Output(display_name="mask"), io.Boolean.Output(display_name="active")],
+            inputs=[
+                io.Combo.Input(
+                    "context",
+                    options=SelectionContext,
+                    default=SelectionContext.entire_image,
+                    tooltip=_selection_context_help,
+                ),
+                io.Int.Input("padding", "padding", default=0, min=0),
+            ],
+            outputs=[
+                io.Mask.Output("mask", "mask"),
+                io.Boolean.Output("active", "active"),
+                io.Int.Output("x", "offset x"),
+                io.Int.Output("y", "offset y"),
+            ],
         )
 
     @classmethod
-    def execute(cls):
-        return io.NodeOutput(torch.ones(1, 512, 512), False)
+    def execute(cls, **kwargs):
+        return io.NodeOutput(torch.ones(1, 512, 512), False, 0, 0)
 
 
 class KritaImageLayer(io.ComfyNode):