From f84df53f5baab6aebefa484bebc79813f39f43af Mon Sep 17 00:00:00 2001 From: TenserTensor Date: Wed, 4 Mar 2026 00:09:48 +0300 Subject: [PATCH] Removed create mask switch --- nodes_image.py | 23 ++++++++++------------- 1 file changed, 10 insertions(+), 13 deletions(-) diff --git a/nodes_image.py b/nodes_image.py index 7929c36..b211a32 100644 --- a/nodes_image.py +++ b/nodes_image.py @@ -96,7 +96,7 @@ def get_torch_device(device=None): ) -def load_image(filename, create_mask, device=None) -> tuple[torch.Tensor, torch.Tensor]: +def load_image(filename, device=None) -> tuple[torch.Tensor, torch.Tensor]: tdevice = get_torch_device(device) path = folder_paths.get_annotated_filepath(filename) pil_image = pillow(Image.open, path) @@ -116,14 +116,13 @@ def load_image(filename, create_mask, device=None) -> tuple[torch.Tensor, torch. if pil_frame.size != (width, height,): continue - if create_mask: - alpha = numpy.zeros((height, width,), dtype=numpy.float32) - if 'A' in pil_frame.getbands(): - alpha = numpy.array(pil_frame.getchannel('A'), dtype=numpy.float32) / 255.0 - elif pil_frame.mode == 'P' and 'transparency' in pil_frame.info: - alpha = numpy.array(pil_frame.convert('RGBA').getchannel('A'), dtype=numpy.float32) / 255.0 - tmask = torch.from_numpy(1.0 - alpha).to(tdevice) - masks.append(tmask) + alpha = numpy.zeros((height, width,), dtype=numpy.float32) + if 'A' in pil_frame.getbands(): + alpha = numpy.array(pil_frame.getchannel('A'), dtype=numpy.float32) / 255.0 + elif pil_frame.mode == 'P' and 'transparency' in pil_frame.info: + alpha = numpy.array(pil_frame.convert('RGBA').getchannel('A'), dtype=numpy.float32) / 255.0 + tmask = torch.from_numpy(1.0 - alpha).to(tdevice) + masks.append(tmask) rgb_frame = pil_frame.convert("RGB") np_image = numpy.array(rgb_frame, dtype=numpy.float32) / 255.0 @@ -170,7 +169,6 @@ class TT_ImageLoaderResizerNode(IO.ComfyNode): IO.Combo.Input("resize_method", options=RESIZE_METHODS, advanced=True), IO.Int.Input("dimension_step", default=1, min=1, max=256, advanced=True), IO.Combo.Input("megapixels", options=MEGAPIXELS, advanced=True), - IO.Boolean.Input("create_mask", default=False, label_on="Mask", label_off="Empty"), IO.Combo.Input("image", options=get_image_files(), upload=UploadType.image) ], outputs=[ @@ -188,7 +186,6 @@ class TT_ImageLoaderResizerNode(IO.ComfyNode): "resize_image": resize, "resize_method": kwargs.get("resize_method"), "dimension_step": kwargs.get("dimension_step"), - "create_mask": kwargs.get("create_mask"), } if resize: @@ -206,7 +203,7 @@ class TT_ImageLoaderResizerNode(IO.ComfyNode): @classmethod def execute(cls, **kwargs) -> IO.NodeOutput: - timage, tmask = load_image(kwargs.get("image"), kwargs.get("create_mask")) + timage, tmask = load_image(kwargs.get("image")) if kwargs.get("resize_image"): resize_method, megapixels, dimension_step = ( kwargs.get("resize_method"), @@ -462,7 +459,7 @@ class TT_GuiderImageReferenceNode(IO.ComfyNode): @classmethod def execute(cls, **kwargs) -> IO.NodeOutput: - timage, _ = load_image(kwargs.get("image"), create_mask=False) + timage, _ = load_image(kwargs.get("image")) vae, guider, resize_method, megapixels, dimension_step = ( kwargs.get("vae"), kwargs.get("guider"),