nodes/melMass-comfy_mtb
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fix: 🔥 use BOOL everywhere

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This commit is contained in:
melMass
2023-07-22 20:09:31 +02:00
parent 119b4d6e16
commit a393793cfa
6 changed files with 28 additions and 36 deletions
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nodes/deep_bump.py
+3 -5
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@@ -264,7 +264,7 @@ class DeepBump:
"LARGEST",
],
),
"normals_to_height_seamless": (["TRUE", "FALSE"],),
"normals_to_height_seamless": ("BOOL", {"default": False}),
},
}
@@ -279,7 +279,7 @@ class DeepBump:
mode="Color to Normals",
color_to_normals_overlap="SMALL",
normals_to_curvature_blur_radius="SMALL",
normals_to_height_seamless="TRUE",
normals_to_height_seamless=True,
):
image = utils_inference.tensor2pil(image)
@@ -295,9 +295,7 @@ class DeepBump:
in_img, normals_to_curvature_blur_radius, None
)
if mode == "Normals to Height":
out_img = normals_to_height(
in_img, normals_to_height_seamless == "TRUE", None
)
out_img = normals_to_height(in_img, normals_to_height_seamless, None)
out_img = (np.transpose(out_img, (1, 2, 0)) * 255).astype(np.uint8)
nodes/faceenhance.py
+6 -10
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@@ -136,12 +136,12 @@ class RestoreFace:
"image": ("IMAGE",),
"model": ("FACEENHANCE_MODEL",),
# Input are aligned faces
"aligned": (["true", "false"], {"default": "false"}),
"aligned": ("BOOL", {"default": False}),
# Only restore the center face
"only_center_face": (["true", "false"], {"default": "false"}),
"only_center_face": ("BOOL", {"default": False}),
# Adjustable weights
"weight": ("FLOAT", {"default": 0.5}),
"save_tmp_steps": (["true", "false"], {"default": "true"}),
"save_tmp_steps": ("BOOL", {"default": True}),
}
}
@@ -183,15 +183,11 @@ class RestoreFace:
self,
image: torch.Tensor,
model: GFPGANer,
aligned="false",
only_center_face="false",
aligned=False,
only_center_face=False,
weight=0.5,
save_tmp_steps="true",
save_tmp_steps=True,
) -> Tuple[torch.Tensor]:
save_tmp_steps = save_tmp_steps == "true"
aligned = aligned == "true"
only_center_face = only_center_face == "true"
out = [
self.do_restore(
image[i], model, aligned, only_center_face, weight, save_tmp_steps
nodes/faceswap.py
+3 -2
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@@ -82,8 +82,9 @@ class FaceSwap:
"reference": ("IMAGE",),
"faces_index": ("STRING", {"default": "0"}),
"faceswap_model": ("FACESWAP_MODEL", {"default": "None"}),
"debug": ("BOOL", {"default": False}),
},
"optional": {"debug": (["true", "false"], {"default": "false"})},
"optional": {},
}
RETURN_TYPES = ("IMAGE",)
@@ -96,7 +97,7 @@ class FaceSwap:
reference: torch.Tensor,
faces_index: str,
faceswap_model,
debug="false",
debug=False,
):
def do_swap(img):
model_management.throw_exception_if_processing_interrupted()
nodes/fun.py
+3 -3
View File
@@ -72,7 +72,7 @@ class QrCode:
"error_correct": (("L", "M", "Q", "H"), {"default": "L"}),
"box_size": ("INT", {"default": 10, "max": 8096, "min": 0, "step": 1}),
"border": ("INT", {"default": 4, "max": 8096, "min": 0, "step": 1}),
"invert": (("True", "False"), {"default": "False"}),
"invert": (("BOOL",), {"default": False}),
}
}
@@ -99,8 +99,8 @@ class QrCode:
qr.add_data(url)
qr.make(fit=True)
back_color = (255, 255, 255) if invert == "True" else (0, 0, 0)
fill_color = (0, 0, 0) if invert == "True" else (255, 255, 255)
back_color = (255, 255, 255) if invert else (0, 0, 0)
fill_color = (0, 0, 0) if invert else (255, 255, 255)
code = img = qr.make_image(back_color=back_color, fill_color=fill_color)
nodes/image_processing.py
+7 -10
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@@ -392,7 +392,7 @@ class ImagePremultiply:
"required": {
"image": ("IMAGE",),
"mask": ("MASK",),
"invert": (["True", "False"], {"default": "False"}),
"invert": ("BOOL", {"default": False}),
}
}
@@ -401,8 +401,6 @@ class ImagePremultiply:
FUNCTION = "premultiply"
def premultiply(self, image, mask, invert):
invert = invert == "True"
images = tensor2pil(image)
if invert:
masks = tensor2pil(mask) # .convert("L")
@@ -445,7 +443,7 @@ class ImageResizeFactor:
"FLOAT",
{"default": 2, "min": 0.01, "max": 16.0, "step": 0.01},
),
"supersample": (["true", "false"], {"default": "true"}),
"supersample": ("BOOL", {"default": True}),
"resampling": (
["lanczos", "nearest", "bilinear", "bicubic"],
{"default": "lanczos"},
@@ -510,7 +508,7 @@ class ImageResizeFactor:
resample_filters = {"nearest": 0, "bilinear": 2, "bicubic": 3, "lanczos": 1}
# Apply supersample
if supersample == "true":
if supersample:
super_size = (new_width * 8, new_height * 8)
log.debug(f"Applying supersample: {super_size}")
img = img.resize(
@@ -529,12 +527,12 @@ class ImageResizeFactor:
self,
image: torch.Tensor,
factor: float,
supersample: str,
supersample: bool,
resampling: str,
mask=None,
):
log.debug(f"Resizing image with factor {factor} and resampling {resampling}")
supersample = supersample == "true"
batch_count = image.size(0)
log.debug(f"Batch count: {batch_count}")
if batch_count == 1:
@@ -566,7 +564,7 @@ class SaveImageGrid:
"required": {
"images": ("IMAGE",),
"filename_prefix": ("STRING", {"default": "ComfyUI"}),
"save_intermediate": (["true", "false"], {"default": "false"}),
"save_intermediate": ("BOOL", {"default": False}),
},
"hidden": {"prompt": "PROMPT", "extra_pnginfo": "EXTRA_PNGINFO"},
}
@@ -607,11 +605,10 @@ class SaveImageGrid:
self,
images,
filename_prefix="Grid",
save_intermediate="false",
save_intermediate=False,
prompt=None,
extra_pnginfo=None,
):
save_intermediate = save_intermediate == "true"
(
full_output_folder,
filename,
nodes/mask.py
+6 -6
View File
@@ -16,8 +16,8 @@ class ImageRemoveBackgroundRembg:
"required": {
"image": ("IMAGE",),
"alpha_matting": (
["True", "False"],
{"default": "False"},
"BOOL",
{"default": False},
),
"alpha_matting_foreground_threshold": (
"INT",
@@ -32,8 +32,8 @@ class ImageRemoveBackgroundRembg:
{"default": 10, "min": 0, "max": 255},
),
"post_process_mask": (
["True", "False"],
{"default": "False"},
"BOOL",
{"default": False},
),
"bgcolor": (
"COLOR",
@@ -76,13 +76,13 @@ class ImageRemoveBackgroundRembg:
for img in images:
img_rm = remove(
data=img,
alpha_matting=alpha_matting == "True",
alpha_matting=alpha_matting,
alpha_matting_foreground_threshold=alpha_matting_foreground_threshold,
alpha_matting_background_threshold=alpha_matting_background_threshold,
alpha_matting_erode_size=alpha_matting_erode_size,
session=None,
only_mask=False,
post_process_mask=post_process_mask == "True",
post_process_mask=post_process_mask,
bgcolor=None,
)