FaceDetailer (pipe)¶
Documentation¶
- Class name:
FaceDetailerPipe
- Category:
ImpactPack/Simple
- Output node:
False
The FaceDetailerPipe node specializes in enhancing facial details within images, leveraging advanced processing techniques to refine and accentuate facial features for improved visual quality.
Input types¶
Required¶
image
- unknown
- Comfy dtype:
IMAGE
- Python dtype:
unknown
detailer_pipe
- Represents the core data structure for detailing operations, essential for processing and enhancing facial details within images.
- Comfy dtype:
DETAILER_PIPE
- Python dtype:
tuple
guide_size
- unknown
- Comfy dtype:
FLOAT
- Python dtype:
unknown
guide_size_for
- unknown
- Comfy dtype:
BOOLEAN
- Python dtype:
unknown
max_size
- unknown
- Comfy dtype:
FLOAT
- Python dtype:
unknown
seed
- unknown
- Comfy dtype:
INT
- Python dtype:
unknown
steps
- unknown
- Comfy dtype:
INT
- Python dtype:
unknown
cfg
- unknown
- Comfy dtype:
FLOAT
- Python dtype:
unknown
sampler_name
- unknown
- Comfy dtype:
COMBO[STRING]
- Python dtype:
unknown
scheduler
- unknown
- Comfy dtype:
COMBO[STRING]
- Python dtype:
unknown
denoise
- unknown
- Comfy dtype:
FLOAT
- Python dtype:
unknown
feather
- unknown
- Comfy dtype:
INT
- Python dtype:
unknown
noise_mask
- unknown
- Comfy dtype:
BOOLEAN
- Python dtype:
unknown
force_inpaint
- unknown
- Comfy dtype:
BOOLEAN
- Python dtype:
unknown
bbox_threshold
- unknown
- Comfy dtype:
FLOAT
- Python dtype:
unknown
bbox_dilation
- unknown
- Comfy dtype:
INT
- Python dtype:
unknown
bbox_crop_factor
- unknown
- Comfy dtype:
FLOAT
- Python dtype:
unknown
sam_detection_hint
- unknown
- Comfy dtype:
COMBO[STRING]
- Python dtype:
unknown
sam_dilation
- unknown
- Comfy dtype:
INT
- Python dtype:
unknown
sam_threshold
- unknown
- Comfy dtype:
FLOAT
- Python dtype:
unknown
sam_bbox_expansion
- unknown
- Comfy dtype:
INT
- Python dtype:
unknown
sam_mask_hint_threshold
- unknown
- Comfy dtype:
FLOAT
- Python dtype:
unknown
sam_mask_hint_use_negative
- unknown
- Comfy dtype:
COMBO[STRING]
- Python dtype:
unknown
drop_size
- unknown
- Comfy dtype:
INT
- Python dtype:
unknown
refiner_ratio
- unknown
- Comfy dtype:
FLOAT
- Python dtype:
unknown
cycle
- unknown
- Comfy dtype:
INT
- Python dtype:
unknown
Optional¶
inpaint_model
- unknown
- Comfy dtype:
BOOLEAN
- Python dtype:
unknown
noise_mask_feather
- unknown
- Comfy dtype:
INT
- Python dtype:
unknown
Output types¶
image
- Comfy dtype:
IMAGE
- unknown
- Python dtype:
unknown
- Comfy dtype:
cropped_refined
- Comfy dtype:
IMAGE
- unknown
- Python dtype:
unknown
- Comfy dtype:
cropped_enhanced_alpha
- Comfy dtype:
IMAGE
- unknown
- Python dtype:
unknown
- Comfy dtype:
mask
- Comfy dtype:
MASK
- unknown
- Python dtype:
unknown
- Comfy dtype:
detailer_pipe
- Comfy dtype:
DETAILER_PIPE
- Outputs the enhanced detailer_pipe structure, encapsulating the refined facial details for subsequent processing or visualization.
- Python dtype:
tuple
- Comfy dtype:
cnet_images
- Comfy dtype:
IMAGE
- unknown
- Python dtype:
unknown
- Comfy dtype:
Usage tips¶
- Infra type:
CPU
- Common nodes:
Source code¶
class FaceDetailerPipe:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"image": ("IMAGE", ),
"detailer_pipe": ("DETAILER_PIPE",),
"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": (core.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}),
"noise_mask": ("BOOLEAN", {"default": True, "label_on": "enabled", "label_off": "disabled"}),
"force_inpaint": ("BOOLEAN", {"default": False, "label_on": "enabled", "label_off": "disabled"}),
"bbox_threshold": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}),
"bbox_dilation": ("INT", {"default": 10, "min": -512, "max": 512, "step": 1}),
"bbox_crop_factor": ("FLOAT", {"default": 3.0, "min": 1.0, "max": 10, "step": 0.1}),
"sam_detection_hint": (["center-1", "horizontal-2", "vertical-2", "rect-4", "diamond-4", "mask-area", "mask-points", "mask-point-bbox", "none"],),
"sam_dilation": ("INT", {"default": 0, "min": -512, "max": 512, "step": 1}),
"sam_threshold": ("FLOAT", {"default": 0.93, "min": 0.0, "max": 1.0, "step": 0.01}),
"sam_bbox_expansion": ("INT", {"default": 0, "min": 0, "max": 1000, "step": 1}),
"sam_mask_hint_threshold": ("FLOAT", {"default": 0.7, "min": 0.0, "max": 1.0, "step": 0.01}),
"sam_mask_hint_use_negative": (["False", "Small", "Outter"],),
"drop_size": ("INT", {"min": 1, "max": MAX_RESOLUTION, "step": 1, "default": 10}),
"refiner_ratio": ("FLOAT", {"default": 0.2, "min": 0.0, "max": 1.0}),
"cycle": ("INT", {"default": 1, "min": 1, "max": 10, "step": 1}),
},
"optional": {
"inpaint_model": ("BOOLEAN", {"default": False, "label_on": "enabled", "label_off": "disabled"}),
"noise_mask_feather": ("INT", {"default": 20, "min": 0, "max": 100, "step": 1}),
}
}
RETURN_TYPES = ("IMAGE", "IMAGE", "IMAGE", "MASK", "DETAILER_PIPE", "IMAGE")
RETURN_NAMES = ("image", "cropped_refined", "cropped_enhanced_alpha", "mask", "detailer_pipe", "cnet_images")
OUTPUT_IS_LIST = (False, True, True, False, False, True)
FUNCTION = "doit"
CATEGORY = "ImpactPack/Simple"
def doit(self, image, detailer_pipe, guide_size, guide_size_for, max_size, seed, steps, cfg, sampler_name, scheduler,
denoise, feather, noise_mask, force_inpaint, bbox_threshold, bbox_dilation, bbox_crop_factor,
sam_detection_hint, sam_dilation, sam_threshold, sam_bbox_expansion,
sam_mask_hint_threshold, sam_mask_hint_use_negative, drop_size, refiner_ratio=None,
cycle=1, inpaint_model=False, noise_mask_feather=0):
result_img = None
result_mask = None
result_cropped_enhanced = []
result_cropped_enhanced_alpha = []
result_cnet_images = []
if len(image) > 1:
print(f"[Impact Pack] WARN: FaceDetailer is not a node designed for video detailing. If you intend to perform video detailing, please use Detailer For AnimateDiff.")
model, clip, vae, positive, negative, wildcard, bbox_detector, segm_detector, sam_model_opt, detailer_hook, \
refiner_model, refiner_clip, refiner_positive, refiner_negative = detailer_pipe
for i, single_image in enumerate(image):
enhanced_img, cropped_enhanced, cropped_enhanced_alpha, mask, cnet_pil_list = FaceDetailer.enhance_face(
single_image.unsqueeze(0), model, clip, vae, guide_size, guide_size_for, max_size, seed + i, steps, cfg, sampler_name, scheduler,
positive, negative, denoise, feather, noise_mask, force_inpaint,
bbox_threshold, bbox_dilation, bbox_crop_factor,
sam_detection_hint, sam_dilation, sam_threshold, sam_bbox_expansion, sam_mask_hint_threshold,
sam_mask_hint_use_negative, drop_size, bbox_detector, segm_detector, sam_model_opt, wildcard, detailer_hook,
refiner_ratio=refiner_ratio, refiner_model=refiner_model,
refiner_clip=refiner_clip, refiner_positive=refiner_positive, refiner_negative=refiner_negative,
cycle=cycle, inpaint_model=inpaint_model, noise_mask_feather=noise_mask_feather)
result_img = torch.cat((result_img, enhanced_img), dim=0) if result_img is not None else enhanced_img
result_mask = torch.cat((result_mask, mask), dim=0) if result_mask is not None else mask
result_cropped_enhanced.extend(cropped_enhanced)
result_cropped_enhanced_alpha.extend(cropped_enhanced_alpha)
result_cnet_images.extend(cnet_pil_list)
if len(result_cropped_enhanced) == 0:
result_cropped_enhanced = [empty_pil_tensor()]
if len(result_cropped_enhanced_alpha) == 0:
result_cropped_enhanced_alpha = [empty_pil_tensor()]
if len(result_cnet_images) == 0:
result_cnet_images = [empty_pil_tensor()]
return result_img, result_cropped_enhanced, result_cropped_enhanced_alpha, result_mask, detailer_pipe, result_cnet_images