85 lines
2.4 KiB
Python
85 lines
2.4 KiB
Python
from PIL import Image, ImageOps
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from PIL.PngImagePlugin import PngInfo
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import requests
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import torch
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import numpy as np
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class LoadImgFromUrl:
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"""Load an image from the given URL"""
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"url": (
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"STRING",
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{
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"default": "http://swqqsa5wv.hb-bkt.clouddn.com/admin/comfyui_b46dcb7133234c549218bf957a6334ed.png"
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},
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),
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}
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}
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RETURN_TYPES = ("IMAGE",)
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RETURN_NAMES = ("image",)
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FUNCTION = "load"
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CATEGORY = "云服务"
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def load(self, url):
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response = requests.get(url, stream=True, timeout=10)
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response.raise_for_status()
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image = Image.open(response.raw)
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image = ImageOps.exif_transpose(image)
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np_image = np.array(image).astype(np.float32) / 255.0
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if np_image.ndim == 2: # 灰度图
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np_image = np.expand_dims(np_image, axis=-1)
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# 保证输出为 (1, H, W, C)
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tensor = torch.from_numpy(np_image).unsqueeze(0)
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return (tensor,)
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class LoadGifFromLocal:
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"""从本地路径加载GIF图片（返回所有帧的张量）"""
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"path": (
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"STRING",
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{
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"default": "your_local_gif_path.gif"
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},
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),
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}
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}
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RETURN_TYPES = ("IMAGE",)
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RETURN_NAMES = ("images",)
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FUNCTION = "load"
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CATEGORY = "本地文件"
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def load(self, path):
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images = []
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with Image.open(path) as im:
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for frame in range(im.n_frames):
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im.seek(frame)
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frame_img = ImageOps.exif_transpose(im.convert("RGBA"))
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np_image = np.array(frame_img).astype(np.float32) / 255.0
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if np_image.ndim == 2: # 灰度图
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np_image = np.expand_dims(np_image, axis=-1)
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images.append(torch.from_numpy(np_image))
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# 输出为 (帧数, H, W, C)
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tensor = torch.stack(images, dim=0)
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return (tensor,)
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NODE_CLASS_MAPPINGS = {
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"LoadImgFromUrl": LoadImgFromUrl,
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"LoadGifFromLocal": LoadGifFromLocal
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"LoadImgFromUrl": "☁️ 加载图片",
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"LoadGifFromLocal": "📂 加载本地GIF"
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} |