7.2 KiB
7.2 KiB
Documentation
- Class name: StabilityAPI_SD3
- Category: KJNodes/experimental
- Output node: False
- Repo Ref: https://github.com/comfyanonymous/ComfyUI
StabilityAPI_SD3节点旨在与StabilityAI API进行交互，用于生成图像或对现有图像进行转换。该节点简化了与API交互的复杂性，使用户能够专注于创意任务。
Input types
Required
- prompt
- 接受文本描述或提示来引导图像生成过程，基于提供的文本影响视觉输出。
- Comfy dtype: STRING
- Python dtype: str
- n_prompt
- 指定要使用的提示数量，允许多个提示影响生成过程。
- Comfy dtype: STRING
- Python dtype: int
- seed
- 随机数生成器的种子值，确保生成图像的可重复性。
- Comfy dtype: INT
- Python dtype: int
- model
- 定义用于图像生成的模型，允许根据所需特征或功能进行选择。
- Comfy dtype: COMBO[STRING]
- Python dtype: str
- aspect_ratio
- 设置输出图像的宽高比，实现对图像尺寸的控制。
- Comfy dtype: COMBO[STRING]
- Python dtype: str
- output_format
- 确定输出图像的格式，如JPEG或PNG，以满足用户偏好。
- Comfy dtype: COMBO[STRING]
- Python dtype: str
Optional
- api_key
- 访问StabilityAI API所需的API密钥，确保授权使用。
- Comfy dtype: STRING
- Python dtype: str
- image
- 用于img2img任务的初始图像，作为转换或增强的基础。
- Comfy dtype: IMAGE
- Python dtype: PIL.Image
- img2img_strength
- 控制在img2img任务中应用于初始图像的转换强度，调整变化程度。
- Comfy dtype: FLOAT
- Python dtype: float
- disable_metadata
- 禁用在生成图像中嵌入元数据的选项，提供对隐私和数据存储的控制。
- Comfy dtype: BOOLEAN
- Python dtype: bool
Output types
- image
- 节点执行结果生成或转换的图像。
- Comfy dtype: IMAGE
- Python dtype: PIL.Image
- ui
- 节点返回一个用户界面组件，通常用于显示生成或转换后的图像。
Usage tips
- Infra type:
CPU - Common nodes: unknown
Source code
class StabilityAPI_SD3:
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"prompt": ("STRING", {"multiline": True}),
"n_prompt": ("STRING", {"multiline": True}),
"seed": ("INT", {"default": 123,"min": 0, "max": 4294967294, "step": 1}),
"model": (
[
'sd3',
'sd3-turbo',
],
{
"default": 'sd3'
}),
"aspect_ratio": (
[
'1:1',
'16:9',
'21:9',
'2:3',
'3:2',
'4:5',
'5:4',
'9:16',
'9:21',
],
{
"default": '1:1'
}),
"output_format": (
[
'png',
'jpeg',
],
{
"default": 'jpeg'
}),
},
"optional": {
"api_key": ("STRING", {"multiline": True}),
"image": ("IMAGE",),
"img2img_strength": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}),
"disable_metadata": ("BOOLEAN", {"default": True}),
},
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "apicall"
CATEGORY = "KJNodes/experimental"
DESCRIPTION = """
## Calls StabilityAI API
Although you may have multiple keys in your account,
you should use the same key for all requests to this API.
Get your API key here: https://platform.stability.ai/account/keys
Recommended to set the key in the config.json -file under this
node packs folder.
# WARNING:
Otherwise the API key may get saved in the image metadata even
with "disable_metadata" on if the workflow includes save nodes
separate from this node.
sd3 requires 6.5 credits per generation
sd3-turbo requires 4 credits per generation
If no image is provided, mode is set to text-to-image
"""
def apicall(self, prompt, n_prompt, model, seed, aspect_ratio, output_format,
img2img_strength=0.5, image=None, disable_metadata=True, api_key=""):
from comfy.cli_args import args
if disable_metadata:
args.disable_metadata = True
else:
args.disable_metadata = False
import requests
from io import BytesIO
from torchvision import transforms
data = {
"mode": "text-to-image",
"prompt": prompt,
"model": model,
"seed": seed,
"output_format": output_format
}
if image is not None:
image = image.permute(0, 3, 1, 2).squeeze(0)
to_pil = transforms.ToPILImage()
pil_image = to_pil(image)
# Save the PIL Image to a BytesIO object
buffer = BytesIO()
pil_image.save(buffer, format='PNG')
buffer.seek(0)
files = {"image": ("image.png", buffer, "image/png")}
data["mode"] = "image-to-image"
data["image"] = pil_image
data["strength"] = img2img_strength
else:
data["aspect_ratio"] = aspect_ratio,
files = {"none": ''}
if model != "sd3-turbo":
data["negative_prompt"] = n_prompt
headers={
"accept": "image/*"
}
if api_key != "":
headers["authorization"] = api_key
else:
config_file_path = os.path.join(script_directory,"config.json")
with open(config_file_path, 'r') as file:
config = json.load(file)
api_key_from_config = config.get("sai_api_key")
headers["authorization"] = api_key_from_config
response = requests.post(
f"https://api.stability.ai/v2beta/stable-image/generate/sd3",
headers=headers,
files = files,
data = data,
)
if response.status_code == 200:
# Convert the response content to a PIL Image
image = Image.open(BytesIO(response.content))
# Convert the PIL Image to a PyTorch tensor
transform = transforms.ToTensor()
tensor_image = transform(image)
tensor_image = tensor_image.unsqueeze(0)
tensor_image = tensor_image.permute(0, 2, 3, 1).cpu().float()
return (tensor_image,)
else:
try:
# Attempt to parse the response as JSON
error_data = response.json()
raise Exception(f"Server error: {error_data}")
except json.JSONDecodeError:
# If the response is not valid JSON, raise a different exception
raise Exception(f"Server error: {response.text}")