nodes/Jokimbe-ComfyUI-DrawThings-gRPC
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fixed control nets

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This commit is contained in:
Kelly Jerrell
2025-04-08 14:54:00 -07:00
parent 37943f966e
commit 5acfe4c1e6
1 changed files with 52 additions and 63 deletions
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nodes.py
+52 -63
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@@ -189,7 +189,6 @@ async def dt_sampler(
builder = flatbuffers.Builder(0)
loras_out = None
if lora is not None and len(lora):
fin_loras = []
for l in lora:
@@ -206,32 +205,29 @@ async def dt_sampler(
builder.PrependUOffsetTRelative(fl)
loras_out = builder.EndVector()
controls = None
controls_prefix = []
if control_net is not None:
controls_out = None
if control_net is not None and len(control_net):
fin_controls = []
for control_cfg in control_net["control_nets"]:
if control_cfg["prefix"] not in controls_prefix:
controls_prefix.append(control_cfg["prefix"])
control_name = builder.CreateString(control_cfg["control_name"])
Control.Start(builder)
Control.AddFile(builder, control_name)
Control.AddInputOverride(builder, DrawThingsLists.control_input_type.index(control_cfg["control_input_type"]))
Control.AddControlMode(builder, DrawThingsLists.control_mode.index(control_cfg["control_mode"]))
Control.AddWeight(builder, control_cfg["control_weight"])
Control.AddGuidanceStart(builder, control_cfg["control_start"])
Control.AddGuidanceEnd(builder, control_cfg["control_end"])
Control.AddNoPrompt(builder, False)
Control.AddGlobalAveragePooling(builder, False)
Control.AddDownSamplingRate(builder, 0)
Control.AddTargetBlocks(builder, 0)
fin_control = Control.End(builder)
fin_controls.append(fin_control)
for c in control_net:
control_name = builder.CreateString(c["file"])
Control.Start(builder)
Control.AddFile(builder, control_name)
Control.AddInputOverride(builder, DrawThingsLists.control_input_type.index(c["input_type"]))
Control.AddControlMode(builder, DrawThingsLists.control_mode.index(c["mode"]))
Control.AddWeight(builder, c["weight"])
Control.AddGuidanceStart(builder, c["start"])
Control.AddGuidanceEnd(builder, c["end"])
Control.AddNoPrompt(builder, False)
Control.AddGlobalAveragePooling(builder, False)
Control.AddDownSamplingRate(builder, 0)
Control.AddTargetBlocks(builder, 0)
fin_control = Control.End(builder)
fin_controls.append(fin_control)
GenerationConfiguration.StartControlsVector(builder, len(control_net["control_nets"]))
for i, control_cfg in enumerate(control_net["control_nets"]):
builder.PrependUOffsetTRelative(fin_controls[i])
controls = builder.EndVector()
GenerationConfiguration.StartControlsVector(builder, len(fin_controls))
for fc in fin_controls:
builder.PrependUOffsetTRelative(fc)
controls_out = builder.EndVector()
start_width = width // 64 // scale_factor
start_height = height // 64 // scale_factor
@@ -267,8 +263,8 @@ async def dt_sampler(
GenerationConfiguration.AddTiledDiffusion(builder, False)
# ti embed
GenerationConfiguration.AddBatchCount(builder, batch_count)
if controls is not None:
GenerationConfiguration.AddControls(builder, controls)
if controls_out is not None:
GenerationConfiguration.AddControls(builder, controls_out)
if loras_out is not None:
GenerationConfiguration.AddLoras(builder, loras_out)
builder.Finish(GenerationConfiguration.End(builder))
@@ -299,15 +295,15 @@ async def dt_sampler(
hints = []
if control_net is not None:
for control_cfg in control_net["control_nets"]:
for control_cfg in control_net:
control_image = control_cfg["image"]
if control_image is not None:
taw = imageService_pb2.TensorAndWeight()
taw.tensor = convert_image_for_request(control_image, control_cfg["control_input_type"].lower())
taw.weight = control_cfg["control_weight"]
taw.tensor = convert_image_for_request(control_image, control_cfg["input_type"].lower())
taw.weight = control_cfg["weight"]
hnt = imageService_pb2.HintProto()
hnt.hintType = control_cfg["control_input_type"].lower()
hnt.hintType = control_cfg["input_type"].lower()
hnt.tensors.append(taw)
hints.append(hnt)
@@ -509,7 +505,7 @@ class DrawThingsSampler:
"image": ("IMAGE", ),
"mask": ("MASK", ),
"lora": ("DT_LORA", ),
"control_net": ("dict", ),
"control_net": ("DT_CNET", ),
}
}
@@ -553,15 +549,13 @@ class DrawThingsSampler:
all_files = get_files(server, port)
model_file = next((m['file'] for m in all_files["models"] if m['name'] == model), None)
# def get_lora_file(lora_item):
# lora_file = next((m['file'] for m in all_files['loras'] if m['name'] == lora_item['lora_name']), None)
# return { 'lora_name': lora_file, 'lora_weight': lora_item['lora_weight'], 'prefix': lora_item['prefix'] }
if lora is not None:
for lora_item in lora:
lora_item['file'] = next((m['file'] for m in all_files['loras'] if m['name'] == lora_item['name']), None)
# lora_with_names = lora['loras'] if lora else []
# lora_with_files = [get_lora_file(lora_item) for lora_item in lora_with_names]
for lora_item in lora:
lora_item['file'] = next((m['file'] for m in all_files['loras'] if m['name'] == lora_item['name']), None)
if control_net is not None:
for cnet in control_net:
cnet['file'] = next((m['file'] for m in all_files['controlNets'] if m['name'] == cnet['name']), None)
return asyncio.run(dt_sampler(
server,
@@ -667,38 +661,33 @@ class DrawThingsControlNet:
"control_end": ("FLOAT", {"default": 1.00, "min": 0.00, "max": 1.00, "step": 0.01}),
},
"optional": {
"control_net": ("dict", {"forceInput": True}),
"control_net": ("DT_CNET",),
"image": ("IMAGE", ),
}
}
RETURN_TYPES = ("dict",)
RETURN_NAMES = ("CONTROL_NET",)
RETURN_TYPES = ("DT_CNET",)
RETURN_NAMES = ("control_net",)
CATEGORY = "DrawThings"
FUNCTION = "add_to_pipeline"
def add_to_pipeline(self, control_name, control_input_type, control_mode, control_weight, control_start, control_end, control_net={}, image=None):
graph = GraphBuilder()
this_node = graph.alloc_prefix()
# Check if 'control_nets' exists in the pipeline
if "control_nets" not in control_net:
# Create 'control_nets' as an empty list
control_net["control_nets"] = []
# Append the new entry as a dictionary to the list
control_net["control_nets"].append({
"prefix": this_node,
"control_name": control_name,
"control_input_type": control_input_type,
"control_mode": control_mode,
"control_weight": control_weight,
"control_start": control_start,
"control_end": control_end,
def add_to_pipeline(self, control_name, control_input_type, control_mode, control_weight, control_start, control_end, control_net=None, image=None):
cnet_list = list()
if control_net is not None:
cnet_list.extend(control_net)
cnet_list.append({
"name": control_name,
"input_type": control_input_type,
"mode": control_mode,
"weight": control_weight,
"start": control_start,
"end": control_end,
"image": image
})
return {
"result": (control_net,),
"expand": graph.finalize(),
}
return (cnet_list,)
# @classmethod
# def IS_CHANGED(s, **kwargs):