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Merge branch 'comfyanonymous:master' into feature/maskpainting

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ltdrdata 2023-05-01 08:39:54 +09:00 committed by GitHub
commit 025fcacf0e
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2 changed files with 46 additions and 18 deletions
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32
nodes.py
View File

@ -59,6 +59,36 @@ class ConditioningCombine:
def combine(self, conditioning_1, conditioning_2):
return (conditioning_1 + conditioning_2, )
class ConditioningAverage :
@classmethod
def INPUT_TYPES(s):
return {"required": {"conditioning_to": ("CONDITIONING", ), "conditioning_from": ("CONDITIONING", ),
"conditioning_to_strength": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01})
}}
RETURN_TYPES = ("CONDITIONING",)
FUNCTION = "addWeighted"
CATEGORY = "conditioning"
def addWeighted(self, conditioning_to, conditioning_from, conditioning_to_strength):
out = []
if len(conditioning_from) > 1:
print("Warning: ConditioningAverage conditioning_from contains more than 1 cond, only the first one will actually be applied to conditioning_to.")
cond_from = conditioning_from[0][0]
for i in range(len(conditioning_to)):
t1 = conditioning_to[i][0]
t0 = cond_from[:,:t1.shape[1]]
if t0.shape[1] < t1.shape[1]:
t0 = torch.cat([t0] + [torch.zeros((1, (t1.shape[1] - t0.shape[1]), t1.shape[2]))], dim=1)
tw = torch.mul(t1, conditioning_to_strength) + torch.mul(t0, (1.0 - conditioning_to_strength))
n = [tw, conditioning_to[i][1].copy()]
out.append(n)
return (out, )
class ConditioningSetArea:
@classmethod
def INPUT_TYPES(s):
@ -1143,6 +1173,7 @@ NODE_CLASS_MAPPINGS = {
"ImageScale": ImageScale,
"ImageInvert": ImageInvert,
"ImagePadForOutpaint": ImagePadForOutpaint,
"ConditioningAverage ": ConditioningAverage ,
"ConditioningCombine": ConditioningCombine,
"ConditioningSetArea": ConditioningSetArea,
"ConditioningSetMask": ConditioningSetMask,
@ -1194,6 +1225,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"CLIPTextEncode": "CLIP Text Encode (Prompt)",
"CLIPSetLastLayer": "CLIP Set Last Layer",
"ConditioningCombine": "Conditioning (Combine)",
"ConditioningAverage ": "Conditioning (Average)",
"ConditioningSetArea": "Conditioning (Set Area)",
"ConditioningSetMask": "Conditioning (Set Mask)",
"ControlNetApply": "Apply ControlNet",

32
web/lib/litegraph.core.js
View File

@ -3628,6 +3628,18 @@
return size;
};
LGraphNode.prototype.inResizeCorner = function(canvasX, canvasY) {
var rows = this.outputs ? this.outputs.length : 1;
var outputs_offset = (this.constructor.slot_start_y || 0) + rows * LiteGraph.NODE_SLOT_HEIGHT;
return isInsideRectangle(canvasX,
canvasY,
this.pos[0] + this.size[0] - 15,
this.pos[1] + Math.max(this.size[1] - 15, outputs_offset),
20,
20
);
}
/**
* returns all the info available about a property of this node.
*
@ -5877,14 +5889,7 @@ LGraphNode.prototype.executeAction = function(action)
if ( !this.connecting_node && !node.flags.collapsed && !this.live_mode ) {
//Search for corner for resize
if ( !skip_action &&
node.resizable !== false &&
isInsideRectangle( e.canvasX,
e.canvasY,
node.pos[0] + node.size[0] - 15,
node.pos[1] + node.size[1] - 15,
20,
20
)
node.resizable !== false && node.inResizeCorner(e.canvasX, e.canvasY)
) {
this.graph.beforeChange();
this.resizing_node = node;
@ -6424,16 +6429,7 @@ LGraphNode.prototype.executeAction = function(action)
//Search for corner
if (this.canvas) {
if (
isInsideRectangle(
e.canvasX,
e.canvasY,
node.pos[0] + node.size[0] - 15,
node.pos[1] + node.size[1] - 15,
15,
15
)
) {
if (node.inResizeCorner(e.canvasX, e.canvasY)) {
this.canvas.style.cursor = "se-resize";
} else {
this.canvas.style.cursor = "crosshair";