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feat: DetailerForEachPipeForAnimateDiff

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modify: change display name of SEGSDetailerForAnimateDiff
This commit is contained in:
Dr.Lt.Data
2024-01-27 12:27:48 +09:00
parent 0a9327bb5d
commit b095838302
4 changed files with 151 additions and 93 deletions
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__init__.py
+5 -2
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@@ -106,6 +106,7 @@ from impact.special_samplers import *
from impact.hf_nodes import *
from impact.bridge_nodes import *
from impact.hook_nodes import *
from impact.animatediff_nodes import *
import threading
@@ -139,6 +140,7 @@ NODE_CLASS_MAPPINGS = {
"DetailerForEachDebug": DetailerForEachTest,
"DetailerForEachPipe": DetailerForEachPipe,
"DetailerForEachDebugPipe": DetailerForEachTestPipe,
"DetailerForEachPipeForAnimateDiff": DetailerForEachPipeForAnimateDiff,
"SAMDetectorCombined": SAMDetectorCombined,
"SAMDetectorSegmented": SAMDetectorSegmented,
@@ -349,12 +351,13 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"DetailerForEachPipe": "Detailer (SEGS/pipe)",
"DetailerForEachDebug": "DetailerDebug (SEGS)",
"DetailerForEachDebugPipe": "DetailerDebug (SEGS/pipe)",
"SEGSDetailerForAnimateDiff": "Detailer For AnimateDiff (SEGS/pipe)",
"SEGSDetailerForAnimateDiff": "SEGSDetailer For AnimateDiff (SEGS/pipe)",
"DetailerForEachPipeForAnimateDiff": "Detailer For AnimateDiff (SEGS/pipe)",
"SAMDetectorCombined": "SAMDetector (combined)",
"SAMDetectorSegmented": "SAMDetector (segmented)",
"FaceDetailerPipe": "FaceDetailer (pipe)",
"MaskDetailerPipe": "MaskDetailer (Pipe)",
"MaskDetailerPipe": "MaskDetailer (pipe)",
"FromDetailerPipeSDXL": "FromDetailer (SDXL/pipe)",
"BasicPipeToDetailerPipeSDXL": "BasicPipe -> DetailerPipe (SDXL)",
modules/impact/animatediff_nodes.py
+145
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@@ -0,0 +1,145 @@
from nodes import MAX_RESOLUTION
from impact.utils import *
import impact.core as core
from impact.core import SEG
from impact.segs_nodes import SEGSPaste
class SEGSDetailerForAnimateDiff:
@classmethod
def INPUT_TYPES(cls):
return {"required": {
"image_frames": ("IMAGE", ),
"segs": ("SEGS", ),
"guide_size": ("FLOAT", {"default": 256, "min": 64, "max": MAX_RESOLUTION, "step": 8}),
"guide_size_for": ("BOOLEAN", {"default": True, "label_on": "bbox", "label_off": "crop_region"}),
"max_size": ("FLOAT", {"default": 768, "min": 64, "max": MAX_RESOLUTION, "step": 8}),
"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
"steps": ("INT", {"default": 20, "min": 1, "max": 10000}),
"cfg": ("FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0}),
"sampler_name": (comfy.samplers.KSampler.SAMPLERS,),
"scheduler": (comfy.samplers.KSampler.SCHEDULERS,),
"denoise": ("FLOAT", {"default": 0.5, "min": 0.0001, "max": 1.0, "step": 0.01}),
"basic_pipe": ("BASIC_PIPE",),
"refiner_ratio": ("FLOAT", {"default": 0.2, "min": 0.0, "max": 1.0})
},
"optional": {
"refiner_basic_pipe_opt": ("BASIC_PIPE",),
# TODO: "inpaint_model": ("BOOLEAN", {"default": False, "label_on": "enabled", "label_off": "disabled"}),
# TODO: "noise_mask_feather": ("INT", {"default": 10, "min": 0, "max": 100, "step": 1}),
}
}
RETURN_TYPES = ("SEGS",)
RETURN_NAMES = ("segs",)
OUTPUT_IS_LIST = (False,)
FUNCTION = "doit"
CATEGORY = "ImpactPack/Detailer"
@staticmethod
def do_detail(image_frames, segs, guide_size, guide_size_for, max_size, seed, steps, cfg, sampler_name, scheduler,
denoise, basic_pipe, refiner_ratio=None, refiner_basic_pipe_opt=None, inpaint_model=False, noise_mask_feather=0):
model, clip, vae, positive, negative = basic_pipe
if refiner_basic_pipe_opt is None:
refiner_model, refiner_clip, refiner_positive, refiner_negative = None, None, None, None
else:
refiner_model, refiner_clip, _, refiner_positive, refiner_negative = refiner_basic_pipe_opt
segs = core.segs_scale_match(segs, image_frames.shape)
new_segs = []
for seg in segs[1]:
cropped_image_frames = None
for image in image_frames:
image = image.unsqueeze(0)
cropped_image = seg.cropped_image if seg.cropped_image is not None else crop_tensor4(image, seg.crop_region)
cropped_image = to_tensor(cropped_image)
if cropped_image_frames is None:
cropped_image_frames = cropped_image
else:
cropped_image_frames = torch.concat((cropped_image_frames, cropped_image), dim=0)
cropped_image_frames = cropped_image_frames.numpy()
enhanced_image_tensor = core.enhance_detail_for_animatediff(cropped_image_frames, model, clip, vae, guide_size, guide_size_for, max_size,
seg.bbox, seed, steps, cfg, sampler_name, scheduler,
positive, negative, denoise, seg.cropped_mask,
refiner_ratio=refiner_ratio, refiner_model=refiner_model,
refiner_clip=refiner_clip, refiner_positive=refiner_positive,
refiner_negative=refiner_negative,
inpaint_model=inpaint_model, noise_mask_feather=noise_mask_feather)
if enhanced_image_tensor is None:
new_cropped_image = cropped_image_frames
else:
new_cropped_image = enhanced_image_tensor.numpy()
new_seg = SEG(new_cropped_image, seg.cropped_mask, seg.confidence, seg.crop_region, seg.bbox, seg.label, None)
new_segs.append(new_seg)
return (segs[0], new_segs)
def doit(self, image_frames, segs, guide_size, guide_size_for, max_size, seed, steps, cfg, sampler_name, scheduler,
denoise, basic_pipe, refiner_ratio=None, refiner_basic_pipe_opt=None, inpaint_model=False, noise_mask_feather=0):
segs = SEGSDetailerForAnimateDiff.do_detail(image_frames, segs, guide_size, guide_size_for, max_size, seed, steps, cfg, sampler_name,
scheduler, denoise, basic_pipe, refiner_ratio, refiner_basic_pipe_opt,
inpaint_model=inpaint_model, noise_mask_feather=noise_mask_feather)
return (segs,)
class DetailerForEachPipeForAnimateDiff:
@classmethod
def INPUT_TYPES(cls):
return {"required": {
"image_frames": ("IMAGE", ),
"segs": ("SEGS", ),
"guide_size": ("FLOAT", {"default": 384, "min": 64, "max": nodes.MAX_RESOLUTION, "step": 8}),
"guide_size_for": ("BOOLEAN", {"default": True, "label_on": "bbox", "label_off": "crop_region"}),
"max_size": ("FLOAT", {"default": 1024, "min": 64, "max": nodes.MAX_RESOLUTION, "step": 8}),
"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
"steps": ("INT", {"default": 20, "min": 1, "max": 10000}),
"cfg": ("FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0}),
"sampler_name": (comfy.samplers.KSampler.SAMPLERS,),
"scheduler": (comfy.samplers.KSampler.SCHEDULERS,),
"denoise": ("FLOAT", {"default": 0.5, "min": 0.0001, "max": 1.0, "step": 0.01}),
"feather": ("INT", {"default": 5, "min": 0, "max": 100, "step": 1}),
"basic_pipe": ("BASIC_PIPE", ),
"refiner_ratio": ("FLOAT", {"default": 0.2, "min": 0.0, "max": 1.0}),
},
"optional": {
"detailer_hook": ("DETAILER_HOOK",),
"refiner_basic_pipe_opt": ("BASIC_PIPE",),
# "inpaint_model": ("BOOLEAN", {"default": False, "label_on": "enabled", "label_off": "disabled"}),
# "noise_mask_feather": ("INT", {"default": 10, "min": 0, "max": 100, "step": 1}),
}
}
RETURN_TYPES = ("IMAGE", "SEGS", "BASIC_PIPE")
RETURN_NAMES = ("image", "segs", "basic_pipe")
OUTPUT_IS_LIST = (False, False, False, True)
FUNCTION = "doit"
CATEGORY = "ImpactPack/Detailer"
@staticmethod
def doit(image_frames, segs, guide_size, guide_size_for, max_size, seed, steps, cfg, sampler_name, scheduler,
denoise, feather, basic_pipe, refiner_ratio=None, detailer_hook=None, refiner_basic_pipe_opt=None,
inpaint_model=False, noise_mask_feather=0):
enhanced_segs = []
for sub_seg in segs[1]:
single_seg = segs[0], [sub_seg]
enhanced_seg = SEGSDetailerForAnimateDiff().do_detail(image_frames, single_seg, guide_size, guide_size_for, max_size, seed, steps, cfg, sampler_name, scheduler,
denoise, basic_pipe, refiner_ratio, refiner_basic_pipe_opt, inpaint_model, noise_mask_feather)
image_frames = SEGSPaste.doit(image_frames, enhanced_seg, feather, alpha=255)[0]
enhanced_segs += enhanced_seg[1]
new_segs = segs[0], enhanced_segs
return image_frames, new_segs, basic_pipe
modules/impact/config.py
+1 -1
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@@ -2,7 +2,7 @@ import configparser
import os
version_code = [4, 68]
version_code = [4, 69]
version = f"V{version_code[0]}.{version_code[1]}" + (f'.{version_code[2]}' if len(version_code) > 2 else '')
dependency_version = 20
modules/impact/segs_nodes.py
-90
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@@ -1,8 +1,6 @@
import os
import sys
import torch
import impact.impact_server
from nodes import MAX_RESOLUTION
@@ -125,94 +123,6 @@ class SEGSDetailer:
return (segs, cnet_pil_list)
class SEGSDetailerForAnimateDiff:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"image_frames": ("IMAGE", ),
"segs": ("SEGS", ),
"guide_size": ("FLOAT", {"default": 256, "min": 64, "max": MAX_RESOLUTION, "step": 8}),
"guide_size_for": ("BOOLEAN", {"default": True, "label_on": "bbox", "label_off": "crop_region"}),
"max_size": ("FLOAT", {"default": 768, "min": 64, "max": MAX_RESOLUTION, "step": 8}),
"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff}),
"steps": ("INT", {"default": 20, "min": 1, "max": 10000}),
"cfg": ("FLOAT", {"default": 8.0, "min": 0.0, "max": 100.0}),
"sampler_name": (comfy.samplers.KSampler.SAMPLERS,),
"scheduler": (comfy.samplers.KSampler.SCHEDULERS,),
"denoise": ("FLOAT", {"default": 0.5, "min": 0.0001, "max": 1.0, "step": 0.01}),
"basic_pipe": ("BASIC_PIPE",),
"refiner_ratio": ("FLOAT", {"default": 0.2, "min": 0.0, "max": 1.0})
},
"optional": {
"refiner_basic_pipe_opt": ("BASIC_PIPE",),
# TODO: "inpaint_model": ("BOOLEAN", {"default": False, "label_on": "enabled", "label_off": "disabled"}),
# TODO: "noise_mask_feather": ("INT", {"default": 10, "min": 0, "max": 100, "step": 1}),
}
}
RETURN_TYPES = ("SEGS",)
RETURN_NAMES = ("segs",)
OUTPUT_IS_LIST = (False,)
FUNCTION = "doit"
CATEGORY = "ImpactPack/Detailer"
@staticmethod
def do_detail(image_frames, segs, guide_size, guide_size_for, max_size, seed, steps, cfg, sampler_name, scheduler,
denoise, basic_pipe, refiner_ratio=None, refiner_basic_pipe_opt=None, inpaint_model=False, noise_mask_feather=0):
model, clip, vae, positive, negative = basic_pipe
if refiner_basic_pipe_opt is None:
refiner_model, refiner_clip, refiner_positive, refiner_negative = None, None, None, None
else:
refiner_model, refiner_clip, _, refiner_positive, refiner_negative = refiner_basic_pipe_opt
segs = core.segs_scale_match(segs, image_frames.shape)
new_segs = []
for seg in segs[1]:
cropped_image_frames = None
for image in image_frames:
image = image.unsqueeze(0)
cropped_image = seg.cropped_image if seg.cropped_image is not None else crop_tensor4(image, seg.crop_region)
cropped_image = to_tensor(cropped_image)
if cropped_image_frames is None:
cropped_image_frames = cropped_image
else:
cropped_image_frames = torch.concat((cropped_image_frames, cropped_image), dim=0)
cropped_image_frames = cropped_image_frames.numpy()
enhanced_image_tensor = core.enhance_detail_for_animatediff(cropped_image_frames, model, clip, vae, guide_size, guide_size_for, max_size,
seg.bbox, seed, steps, cfg, sampler_name, scheduler,
positive, negative, denoise, seg.cropped_mask,
refiner_ratio=refiner_ratio, refiner_model=refiner_model,
refiner_clip=refiner_clip, refiner_positive=refiner_positive,
refiner_negative=refiner_negative,
inpaint_model=inpaint_model, noise_mask_feather=noise_mask_feather)
if enhanced_image_tensor is None:
new_cropped_image = cropped_image_frames
else:
new_cropped_image = enhanced_image_tensor.numpy()
new_seg = SEG(new_cropped_image, seg.cropped_mask, seg.confidence, seg.crop_region, seg.bbox, seg.label, None)
new_segs.append(new_seg)
return (segs[0], new_segs)
def doit(self, image_frames, segs, guide_size, guide_size_for, max_size, seed, steps, cfg, sampler_name, scheduler,
denoise, basic_pipe, refiner_ratio=None, refiner_basic_pipe_opt=None, inpaint_model=False, noise_mask_feather=0):
segs = SEGSDetailerForAnimateDiff.do_detail(image_frames, segs, guide_size, guide_size_for, max_size, seed, steps, cfg, sampler_name,
scheduler, denoise, basic_pipe, refiner_ratio, refiner_basic_pipe_opt,
inpaint_model=inpaint_model, noise_mask_feather=noise_mask_feather)
return (segs,)
class SEGSPaste:
@classmethod
def INPUT_TYPES(s):