mirror of
https://github.com/comfyanonymous/ComfyUI.git
synced 2026-01-12 07:10:52 +08:00
Merge branch 'comfyanonymous:master' into master
This commit is contained in:
commit
a12b26c630
@ -95,6 +95,7 @@ import aiohttp
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import asyncio
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import logging
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import io
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import os
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import socket
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from aiohttp.client_exceptions import ClientError, ClientResponseError
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from typing import Dict, Type, Optional, Any, TypeVar, Generic, Callable, Tuple
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@ -499,7 +500,9 @@ class ApiClient:
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else:
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raise ValueError("File must be BytesIO or str path")
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operation_id = f"upload_{upload_url.split('/')[-1]}_{uuid.uuid4().hex[:8]}"
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parsed = urlparse(upload_url)
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basename = os.path.basename(parsed.path) or parsed.netloc or "upload"
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operation_id = f"upload_{basename}_{uuid.uuid4().hex[:8]}"
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request_logger.log_request_response(
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operation_id=operation_id,
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request_method="PUT",
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@ -4,16 +4,18 @@ import os
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import datetime
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import json
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import logging
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import re
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import hashlib
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from typing import Any
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import folder_paths
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# Get the logger instance
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logger = logging.getLogger(__name__)
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def get_log_directory():
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"""
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Ensures the API log directory exists within ComfyUI's temp directory
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and returns its path.
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"""
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"""Ensures the API log directory exists within ComfyUI's temp directory and returns its path."""
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base_temp_dir = folder_paths.get_temp_directory()
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log_dir = os.path.join(base_temp_dir, "api_logs")
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try:
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@ -24,42 +26,77 @@ def get_log_directory():
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return base_temp_dir
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return log_dir
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def _format_data_for_logging(data):
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def _sanitize_filename_component(name: str) -> str:
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if not name:
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return "log"
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sanitized = re.sub(r"[^A-Za-z0-9._-]+", "_", name) # Replace disallowed characters with underscore
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sanitized = sanitized.strip(" ._") # Windows: trailing dots or spaces are not allowed
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if not sanitized:
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sanitized = "log"
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return sanitized
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def _short_hash(*parts: str, length: int = 10) -> str:
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return hashlib.sha1(("|".join(parts)).encode("utf-8")).hexdigest()[:length]
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def _build_log_filepath(log_dir: str, operation_id: str, request_url: str) -> str:
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"""Build log filepath. We keep it well under common path length limits aiming for <= 240 characters total."""
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timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S_%f")
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slug = _sanitize_filename_component(operation_id) # Best-effort human-readable slug from operation_id
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h = _short_hash(operation_id or "", request_url or "") # Short hash ties log to the full operation and URL
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# Compute how much room we have for the slug given the directory length
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# Keep total path length reasonably below ~260 on Windows.
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max_total_path = 240
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prefix = f"{timestamp}_"
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suffix = f"_{h}.log"
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if not slug:
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slug = "op"
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max_filename_len = max(60, max_total_path - len(log_dir) - 1)
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max_slug_len = max(8, max_filename_len - len(prefix) - len(suffix))
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if len(slug) > max_slug_len:
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slug = slug[:max_slug_len].rstrip(" ._-")
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return os.path.join(log_dir, f"{prefix}{slug}{suffix}")
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def _format_data_for_logging(data: Any) -> str:
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"""Helper to format data (dict, str, bytes) for logging."""
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if isinstance(data, bytes):
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try:
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return data.decode('utf-8') # Try to decode as text
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return data.decode("utf-8") # Try to decode as text
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except UnicodeDecodeError:
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return f"[Binary data of length {len(data)} bytes]"
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elif isinstance(data, (dict, list)):
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try:
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return json.dumps(data, indent=2, ensure_ascii=False)
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except TypeError:
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return str(data) # Fallback for non-serializable objects
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return str(data) # Fallback for non-serializable objects
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return str(data)
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def log_request_response(
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operation_id: str,
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request_method: str,
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request_url: str,
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request_headers: dict | None = None,
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request_params: dict | None = None,
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request_data: any = None,
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request_data: Any = None,
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response_status_code: int | None = None,
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response_headers: dict | None = None,
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response_content: any = None,
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error_message: str | None = None
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response_content: Any = None,
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error_message: str | None = None,
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):
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"""
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Logs API request and response details to a file in the temp/api_logs directory.
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Filenames are sanitized and length-limited for cross-platform safety.
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If we still fail to write, we fall back to appending into api.log.
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"""
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log_dir = get_log_directory()
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timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S_%f")
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filename = f"{timestamp}_{operation_id.replace('/', '_').replace(':', '_')}.log"
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filepath = os.path.join(log_dir, filename)
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log_content = []
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filepath = _build_log_filepath(log_dir, operation_id, request_url)
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log_content: list[str] = []
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log_content.append(f"Timestamp: {datetime.datetime.now().isoformat()}")
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log_content.append(f"Operation ID: {operation_id}")
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log_content.append("-" * 30 + " REQUEST " + "-" * 30)
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@ -69,7 +106,7 @@ def log_request_response(
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log_content.append(f"Headers:\n{_format_data_for_logging(request_headers)}")
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if request_params:
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log_content.append(f"Params:\n{_format_data_for_logging(request_params)}")
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if request_data:
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if request_data is not None:
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log_content.append(f"Data/Body:\n{_format_data_for_logging(request_data)}")
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log_content.append("\n" + "-" * 30 + " RESPONSE " + "-" * 30)
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@ -77,7 +114,7 @@ def log_request_response(
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log_content.append(f"Status Code: {response_status_code}")
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if response_headers:
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log_content.append(f"Headers:\n{_format_data_for_logging(response_headers)}")
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if response_content:
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if response_content is not None:
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log_content.append(f"Content:\n{_format_data_for_logging(response_content)}")
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if error_message:
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log_content.append(f"Error:\n{error_message}")
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@ -89,6 +126,7 @@ def log_request_response(
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except Exception as e:
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logger.error(f"Error writing API log to {filepath}: {e}")
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if __name__ == '__main__':
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# Example usage (for testing the logger directly)
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logger.setLevel(logging.DEBUG)
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@ -1,24 +1,34 @@
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import torch
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import comfy.model_management
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from typing_extensions import override
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from comfy_api.latest import ComfyExtension, io
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from kornia.morphology import dilation, erosion, opening, closing, gradient, top_hat, bottom_hat
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import kornia.color
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class Morphology:
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class Morphology(io.ComfyNode):
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {"image": ("IMAGE",),
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"operation": (["erode", "dilate", "open", "close", "gradient", "bottom_hat", "top_hat"],),
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"kernel_size": ("INT", {"default": 3, "min": 3, "max": 999, "step": 1}),
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}}
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def define_schema(cls):
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return io.Schema(
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node_id="Morphology",
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display_name="ImageMorphology",
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category="image/postprocessing",
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inputs=[
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io.Image.Input("image"),
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io.Combo.Input(
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"operation",
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options=["erode", "dilate", "open", "close", "gradient", "bottom_hat", "top_hat"],
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),
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io.Int.Input("kernel_size", default=3, min=3, max=999, step=1),
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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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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "process"
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CATEGORY = "image/postprocessing"
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def process(self, image, operation, kernel_size):
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@classmethod
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def execute(cls, image, operation, kernel_size) -> io.NodeOutput:
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device = comfy.model_management.get_torch_device()
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kernel = torch.ones(kernel_size, kernel_size, device=device)
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image_k = image.to(device).movedim(-1, 1)
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@ -39,49 +49,63 @@ class Morphology:
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else:
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raise ValueError(f"Invalid operation {operation} for morphology. Must be one of 'erode', 'dilate', 'open', 'close', 'gradient', 'tophat', 'bottomhat'")
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img_out = output.to(comfy.model_management.intermediate_device()).movedim(1, -1)
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return (img_out,)
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return io.NodeOutput(img_out)
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class ImageRGBToYUV:
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class ImageRGBToYUV(io.ComfyNode):
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@classmethod
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def INPUT_TYPES(s):
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return {"required": { "image": ("IMAGE",),
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}}
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def define_schema(cls):
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return io.Schema(
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node_id="ImageRGBToYUV",
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category="image/batch",
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inputs=[
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io.Image.Input("image"),
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],
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outputs=[
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io.Image.Output(display_name="Y"),
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io.Image.Output(display_name="U"),
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io.Image.Output(display_name="V"),
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],
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)
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RETURN_TYPES = ("IMAGE", "IMAGE", "IMAGE")
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RETURN_NAMES = ("Y", "U", "V")
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FUNCTION = "execute"
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CATEGORY = "image/batch"
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def execute(self, image):
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@classmethod
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def execute(cls, image) -> io.NodeOutput:
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out = kornia.color.rgb_to_ycbcr(image.movedim(-1, 1)).movedim(1, -1)
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return (out[..., 0:1].expand_as(image), out[..., 1:2].expand_as(image), out[..., 2:3].expand_as(image))
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return io.NodeOutput(out[..., 0:1].expand_as(image), out[..., 1:2].expand_as(image), out[..., 2:3].expand_as(image))
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class ImageYUVToRGB:
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class ImageYUVToRGB(io.ComfyNode):
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@classmethod
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def INPUT_TYPES(s):
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return {"required": {"Y": ("IMAGE",),
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"U": ("IMAGE",),
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"V": ("IMAGE",),
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}}
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def define_schema(cls):
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return io.Schema(
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node_id="ImageYUVToRGB",
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category="image/batch",
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inputs=[
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io.Image.Input("Y"),
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io.Image.Input("U"),
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io.Image.Input("V"),
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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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RETURN_TYPES = ("IMAGE",)
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FUNCTION = "execute"
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CATEGORY = "image/batch"
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def execute(self, Y, U, V):
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@classmethod
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def execute(cls, Y, U, V) -> io.NodeOutput:
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image = torch.cat([torch.mean(Y, dim=-1, keepdim=True), torch.mean(U, dim=-1, keepdim=True), torch.mean(V, dim=-1, keepdim=True)], dim=-1)
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out = kornia.color.ycbcr_to_rgb(image.movedim(-1, 1)).movedim(1, -1)
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return (out,)
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return io.NodeOutput(out)
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NODE_CLASS_MAPPINGS = {
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"Morphology": Morphology,
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"ImageRGBToYUV": ImageRGBToYUV,
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"ImageYUVToRGB": ImageYUVToRGB,
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"Morphology": "ImageMorphology",
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}
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class MorphologyExtension(ComfyExtension):
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@override
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async def get_node_list(self) -> list[type[io.ComfyNode]]:
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return [
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Morphology,
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ImageRGBToYUV,
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ImageYUVToRGB,
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]
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async def comfy_entrypoint() -> MorphologyExtension:
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return MorphologyExtension()
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