mirror of
https://github.com/comfyanonymous/ComfyUI.git
synced 2025-07-27 16:26:39 +00:00
107 lines
3.3 KiB
Python
107 lines
3.3 KiB
Python
import hashlib
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import numpy as np
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import torch
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from PIL import Image, ImageOps, ImageSequence
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import folder_paths
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import node_helpers
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import nodes
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from comfy_api.v3 import io
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MAX_RESOLUTION = nodes.MAX_RESOLUTION
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class WebcamCapture_V3(io.ComfyNodeV3):
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@classmethod
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def DEFINE_SCHEMA(cls):
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return io.SchemaV3(
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node_id="WebcamCapture_V3",
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display_name="Webcam Capture _V3",
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category="image",
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inputs=[
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io.Webcam.Input("image"),
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io.Int.Input(
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"width",
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default=0,
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min=0,
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max=MAX_RESOLUTION,
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step=1,
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),
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io.Int.Input(
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"height",
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default=0,
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min=0,
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max=MAX_RESOLUTION,
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step=1,
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),
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io.Boolean.Input("capture_on_queue", default=True),
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],
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outputs=[
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io.Image.Output(),
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],
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)
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@classmethod
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def execute(cls, image, **kwargs) -> io.NodeOutput:
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img = node_helpers.pillow(Image.open, folder_paths.get_annotated_filepath(image))
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output_images = []
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output_masks = []
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w, h = None, None
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excluded_formats = ["MPO"]
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for i in ImageSequence.Iterator(img):
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i = node_helpers.pillow(ImageOps.exif_transpose, i)
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if i.mode == "I":
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i = i.point(lambda i: i * (1 / 255))
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image = i.convert("RGB")
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if len(output_images) == 0:
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w = image.size[0]
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h = image.size[1]
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if image.size[0] != w or image.size[1] != h:
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continue
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image = np.array(image).astype(np.float32) / 255.0
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image = torch.from_numpy(image)[None,]
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if "A" in i.getbands():
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mask = np.array(i.getchannel("A")).astype(np.float32) / 255.0
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mask = 1.0 - torch.from_numpy(mask)
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elif i.mode == "P" and "transparency" in i.info:
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mask = np.array(i.convert("RGBA").getchannel("A")).astype(np.float32) / 255.0
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mask = 1.0 - torch.from_numpy(mask)
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else:
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mask = torch.zeros((64, 64), dtype=torch.float32, device="cpu")
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output_images.append(image)
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output_masks.append(mask.unsqueeze(0))
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if len(output_images) > 1 and img.format not in excluded_formats:
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output_image = torch.cat(output_images, dim=0)
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output_mask = torch.cat(output_masks, dim=0)
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else:
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output_image = output_images[0]
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output_mask = output_masks[0]
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return io.NodeOutput(output_image, output_mask)
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@classmethod
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def fingerprint_inputs(s, image, width, height, capture_on_queue):
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image_path = folder_paths.get_annotated_filepath(image)
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m = hashlib.sha256()
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with open(image_path, "rb") as f:
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m.update(f.read())
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return m.digest().hex()
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@classmethod
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def validate_inputs(s, image):
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if not folder_paths.exists_annotated_filepath(image):
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return "Invalid image file: {}".format(image)
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return True
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NODES_LIST: list[type[io.ComfyNodeV3]] = [WebcamCapture_V3]
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