2.4 KiB
2.4 KiB
Documentation
- Class name: ImageUpscaleWithModel
- Category: image/upscaling
- Output node: False
- Repo Ref: https://github.com/comfyanonymous/ComfyUI
ImageUpscaleWithModel节点旨在使用指定的放大模型增强输入图像的分辨率。它智能地管理系统内存,以防止内存不足错误,确保平滑的放大过程。节点的功能集中在提高图像质量,同时不牺牲性能。
Input types
Required
- upscale_model
- upscale_model参数对于节点至关重要,因为它定义了用于放大图像的模型。它直接影响上采样过程和生成的图像质量。
- Comfy dtype: torch.nn.Module
- Python dtype: torch.nn.Module
- image
- image参数是必需的,因为它代表了节点将处理的输入图像数据。其结构和内容是上采样操作成功的关键。
- Comfy dtype: torch.Tensor
- Python dtype: torch.Tensor
Output types
- IMAGE
- 输出参数IMAGE代表了节点生成的放大图像。它标志着上采样过程的成功完成,是节点功能的主要成果。
- Comfy dtype: torch.Tensor
- Python dtype: torch.Tensor
Usage tips
- Infra type: GPU
Source code
class ImageUpscaleWithModel:
@classmethod
def INPUT_TYPES(s):
return {'required': {'upscale_model': ('UPSCALE_MODEL',), 'image': ('IMAGE',)}}
RETURN_TYPES = ('IMAGE',)
FUNCTION = 'upscale'
CATEGORY = 'image/upscaling'
def upscale(self, upscale_model, image):
device = model_management.get_torch_device()
upscale_model.to(device)
in_img = image.movedim(-1, -3).to(device)
free_memory = model_management.get_free_memory(device)
tile = 512
overlap = 32
oom = True
while oom:
try:
steps = in_img.shape[0] * comfy.utils.get_tiled_scale_steps(in_img.shape[3], in_img.shape[2], tile_x=tile, tile_y=tile, overlap=overlap)
pbar = comfy.utils.ProgressBar(steps)
s = comfy.utils.tiled_scale(in_img, lambda a: upscale_model(a), tile_x=tile, tile_y=tile, overlap=overlap, upscale_amount=upscale_model.scale, pbar=pbar)
oom = False
except model_management.OOM_EXCEPTION as e:
tile //= 2
if tile < 128:
raise e
upscale_model.cpu()
s = torch.clamp(s.movedim(-3, -1), min=0, max=1.0)
return (s,)