Files
Bjornulf_custom_nodes/API_StableDiffusion.py
justumen 50ee5779c0 0.62
2024-12-17 14:38:57 +01:00

116 lines
3.6 KiB
Python

import os
import time
import requests
from PIL import Image
import numpy as np
import torch
import base64
class APIGenerateStability:
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"api_key": ("STRING", {
"multiline": False,
"default": ""
}),
"prompt": ("STRING", {
"multiline": True,
"default": "A beautiful landscape"
}),
},
"optional": {
"negative_prompt": ("STRING", {
"multiline": True,
"default": ""
}),
"aspect_ratio": (["16:9", "1:1", "21:9", "2:3", "3:2", "4:5", "5:4", "9:16", "9:21"], {
"default": "1:1"
}),
"seed": ("INT", {
"default": 0,
"min": 0,
"max": 4294967294
}),
"output_format": (["jpeg", "png", "webp"], {
"default": "png"
}),
"strength": ("FLOAT", {
"default": 1.0,
"min": 0.0,
"max": 1.0,
"step": 0.01
}),
}
}
RETURN_TYPES = ("IMAGE",)
FUNCTION = "generate"
CATEGORY = "Bjornulf"
def get_next_number(self):
save_dir = "output/API/Stability"
os.makedirs(save_dir, exist_ok=True)
files = [f for f in os.listdir(save_dir) if f.endswith(('.webp', '.png', '.jpeg'))]
if not files:
return 1
numbers = [int(f.split('.')[0]) for f in files]
return max(numbers) + 1
def generate(self, api_key, prompt, negative_prompt="", aspect_ratio="1:1",
seed=0, output_format="png", strength=1.0):
headers = {
"Authorization": f"Bearer {api_key}",
"Accept": "image/*"
}
# Prepare the form data
form_data = {
"prompt": prompt,
"output_format": output_format,
"aspect_ratio": aspect_ratio
}
# Add optional parameters if they're provided
if negative_prompt:
form_data["negative_prompt"] = negative_prompt
if seed != 0:
form_data["seed"] = seed
if strength != 1.0:
form_data["strength"] = strength
# Include a placeholder in the 'files' argument to trigger multipart/form-data
files = {"placeholder": ("filename", b"")}
# Make the API request
response = requests.post(
"https://api.stability.ai/v2beta/stable-image/generate/ultra",
headers=headers,
files=files,
data=form_data
)
if response.status_code == 200:
next_num = self.get_next_number()
filename = f"{next_num:03d}.{output_format}"
filepath = os.path.join("output/API/Stability", filename)
# Save the image
with open(filepath, 'wb') as file:
file.write(response.content)
# Load and process the image for ComfyUI
img = Image.open(filepath)
if img.mode != 'RGB':
img = img.convert('RGB')
# Convert to tensor format expected by ComfyUI
img_tensor = torch.from_numpy(np.array(img).astype(np.float32) / 255.0)
img_tensor = img_tensor.unsqueeze(0)
return (img_tensor,)
else:
raise Exception(str(response.json()))