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2
.github/workflows/test-ci.yml
vendored
2
.github/workflows/test-ci.yml
vendored
@ -20,7 +20,6 @@ jobs:
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test-stable:
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strategy:
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fail-fast: false
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max-parallel: 1 # This forces sequential execution
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matrix:
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# os: [macos, linux, windows]
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# os: [macos, linux]
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@ -75,7 +74,6 @@ jobs:
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test-unix-nightly:
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strategy:
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fail-fast: false
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max-parallel: 1 # This forces sequential execution
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matrix:
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# os: [macos, linux]
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os: [linux]
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@ -479,8 +479,8 @@ class VAE:
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self.first_stage_model = comfy.ldm.lightricks.vae.causal_video_autoencoder.VideoVAE(version=version, config=vae_config)
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self.latent_channels = 128
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self.latent_dim = 3
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self.memory_used_decode = lambda shape, dtype: (900 * shape[2] * shape[3] * shape[4] * (8 * 8 * 8)) * model_management.dtype_size(dtype)
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self.memory_used_encode = lambda shape, dtype: (70 * max(shape[2], 7) * shape[3] * shape[4]) * model_management.dtype_size(dtype)
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self.memory_used_decode = lambda shape, dtype: (1200 * shape[2] * shape[3] * shape[4] * (8 * 8 * 8)) * model_management.dtype_size(dtype)
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self.memory_used_encode = lambda shape, dtype: (80 * max(shape[2], 7) * shape[3] * shape[4]) * model_management.dtype_size(dtype)
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self.upscale_ratio = (lambda a: max(0, a * 8 - 7), 32, 32)
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self.upscale_index_formula = (8, 32, 32)
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self.downscale_ratio = (lambda a: max(0, math.floor((a + 7) / 8)), 32, 32)
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@ -1113,6 +1113,22 @@ class DynamicSlot(ComfyTypeI):
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out_dict[input_type][finalized_id] = value
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out_dict["dynamic_paths"][finalized_id] = finalize_prefix(curr_prefix, curr_prefix[-1])
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@comfytype(io_type="IMAGECROP")
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class ImageCrop(ComfyTypeI):
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"""Widget for visual image cropping with x, y, width, height controls."""
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Type = dict
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class Input(WidgetInput):
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def __init__(self, id: str, display_name: str=None, optional=False, tooltip: str=None,
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socketless: bool=True,
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default: dict=None):
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super().__init__(id, display_name, optional, tooltip, None, default, socketless)
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if default is None:
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self.default = {"x": 0, "y": 0, "width": 512, "height": 512}
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def as_dict(self):
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return super().as_dict()
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DYNAMIC_INPUT_LOOKUP: dict[str, Callable[[dict[str, Any], dict[str, Any], tuple[str, dict[str, Any]], str, list[str] | None], None]] = {}
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def register_dynamic_input_func(io_type: str, func: Callable[[dict[str, Any], dict[str, Any], tuple[str, dict[str, Any]], str, list[str] | None], None]):
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DYNAMIC_INPUT_LOOKUP[io_type] = func
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@ -1958,4 +1974,5 @@ __all__ = [
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"add_to_dict_v1",
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"add_to_dict_v3",
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"V3Data",
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"ImageCrop",
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]
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@ -26,16 +26,18 @@ class ImageCrop(IO.ComfyNode):
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category="image/transform",
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inputs=[
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IO.Image.Input("image"),
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IO.Int.Input("width", default=512, min=1, max=nodes.MAX_RESOLUTION, step=1),
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IO.Int.Input("height", default=512, min=1, max=nodes.MAX_RESOLUTION, step=1),
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IO.Int.Input("x", default=0, min=0, max=nodes.MAX_RESOLUTION, step=1),
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IO.Int.Input("y", default=0, min=0, max=nodes.MAX_RESOLUTION, step=1),
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IO.ImageCrop.Input("crop_region"),
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],
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outputs=[IO.Image.Output()],
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)
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@classmethod
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def execute(cls, image, width, height, x, y) -> IO.NodeOutput:
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def execute(cls, image, crop_region) -> IO.NodeOutput:
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x = crop_region.get("x", 0)
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y = crop_region.get("y", 0)
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width = crop_region.get("width", 512)
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height = crop_region.get("height", 512)
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x = min(x, image.shape[2] - 1)
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y = min(y, image.shape[1] - 1)
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to_x = width + x
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@ -1,3 +1,3 @@
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# This file is automatically generated by the build process when version is
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# updated in pyproject.toml.
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__version__ = "0.8.0"
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__version__ = "0.8.2"
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@ -1 +1 @@
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comfyui_manager==4.0.4
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comfyui_manager==4.0.5
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@ -1,6 +1,6 @@
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[project]
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name = "ComfyUI"
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version = "0.8.0"
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version = "0.8.2"
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readme = "README.md"
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license = { file = "LICENSE" }
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requires-python = ">=3.10"
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