From 8c5d9ae4ad5f19725864d6de5a79c8511cfa3b3c Mon Sep 17 00:00:00 2001
From: kijai <40791699+kijai@users.noreply.github.com>
Date: Fri, 26 Apr 2024 01:18:36 +0300
Subject: [PATCH] Repeat output for spline editor

---
 nodes.py                | 23 ++++++++++-------------
 web/js/spline_editor.js |  2 +-
 2 files changed, 11 insertions(+), 14 deletions(-)

diff --git a/nodes.py b/nodes.py
index 3024295..cf1d5b2 100644
--- a/nodes.py
+++ b/nodes.py
@@ -4771,7 +4771,7 @@ class SplineEditor:
                 "default": 'cardinal'
                     }),
                 "tension": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}),
-                "segmented": ("BOOLEAN", {"default": False}),
+                "repeat_output": ("INT", {"default": 1, "min": 1, "max": 4096, "step": 1}),
                 "float_output_type": (
                 [   
                     'list',
@@ -4822,37 +4822,34 @@ output types:
         example compatible nodes: unknown
 """
 
-    def splinedata(self, mask_width, mask_height, coordinates, float_output_type, interpolation, points_to_sample, points_store, tension, segmented):
+    def splinedata(self, mask_width, mask_height, coordinates, float_output_type, interpolation, points_to_sample, points_store, tension, repeat_output):
         
         coordinates = json.loads(coordinates)
-
         normalized_y_values = [
             1.0 - (point['y'] / 512)
             for point in coordinates
         ]
         if float_output_type == 'list':
-            out_floats = normalized_y_values
+            out_floats = normalized_y_values * repeat_output
         elif float_output_type == 'list of lists':
-            out_floats = [[value] for value in normalized_y_values],
+            out_floats = ([[value] for value in normalized_y_values] * repeat_output),
         elif float_output_type == 'pandas series':
             try:
                 import pandas as pd
             except:
                 raise Exception("MaskOrImageToWeight: pandas is not installed. Please install pandas to use this output_type")
-            out_floats = pd.Series(normalized_y_values),
+            out_floats = pd.Series(normalized_y_values * repeat_output),
         elif float_output_type == 'tensor':
-            out_floats = torch.tensor(normalized_y_values, dtype=torch.float32)
+            out_floats = torch.tensor(normalized_y_values * repeat_output, dtype=torch.float32)
         # Create a color map for grayscale intensities
         color_map = lambda y: torch.full((mask_height, mask_width, 3), y, dtype=torch.float32)
 
         # Create image tensors for each normalized y value
-        image_tensors = [color_map(y) for y in normalized_y_values]
-
-        # Batch the tensors
-        masks_out = torch.stack(image_tensors)
+        mask_tensors = [color_map(y) for y in normalized_y_values]
+        masks_out = torch.stack(mask_tensors)
+        masks_out = masks_out.repeat(repeat_output, 1, 1, 1)
         masks_out = masks_out.mean(dim=-1)
-        print(masks_out.shape)
-        return (masks_out, coordinates, out_floats,)
+        return (masks_out, str(coordinates), out_floats,)
     
 class StabilityAPI_SD3:
 
diff --git a/web/js/spline_editor.js b/web/js/spline_editor.js
index 133e469..a1c966d 100644
--- a/web/js/spline_editor.js
+++ b/web/js/spline_editor.js
@@ -170,7 +170,7 @@ function createSplineEditor(context, reset=false) {
   const pointsWidget = context.widgets.find(w => w.name === "points_to_sample");
   const pointsStoreWidget = context.widgets.find(w => w.name === "points_store");
   const tensionWidget = context.widgets.find(w => w.name === "tension");
-  const segmentedWidget = context.widgets.find(w => w.name === "segmented");
+  //const segmentedWidget = context.widgets.find(w => w.name === "segmented");
 
   var interpolation = interpolationWidget.value
   var tension = tensionWidget.value