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import gradio as gr
import requests
import io
import random
import os
from PIL import Image
list_models = [
"SDXL-1.0",
"SD-1.5",
"OpenJourney-V4",
"Anything-V4",
"Disney-Pixar-Cartoon",
"Pixel-Art-XL",
"Dalle-3-XL",
"Midjourney-V4-XL",
]
def generate_txt2img(current_model, prompt, is_negative=False, image_style="None style", steps=50, cfg_scale=7,
seed=None):
if current_model == "SD-1.5":
API_URL = "https://api-inference.huggingface.co/models/runwayml/stable-diffusion-v1-5"
elif current_model == "SDXL-1.0":
API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
elif current_model == "OpenJourney-V4":
API_URL = "https://api-inference.huggingface.co/models/prompthero/openjourney"
elif current_model == "Anything-V4":
API_URL = "https://api-inference.huggingface.co/models/xyn-ai/anything-v4.0"
elif current_model == "Disney-Pixar-Cartoon":
API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/disney-pixar-cartoon"
elif current_model == "Pixel-Art-XL":
API_URL = "https://api-inference.huggingface.co/models/nerijs/pixel-art-xl"
elif current_model == "Dalle-3-XL":
API_URL = "https://api-inference.huggingface.co/models/openskyml/dalle-3-xl"
elif current_model == "Midjourney-V4-XL":
API_URL = "https://api-inference.huggingface.co/models/openskyml/midjourney-v4-xl"
API_TOKEN = os.environ.get("HF_READ_TOKEN")
headers = {"Authorization": f"Bearer {API_TOKEN}"}
if image_style == "None style":
payload = {
"inputs": prompt + ", 8k",
"is_negative": is_negative,
"steps": steps,
"cfg_scale": cfg_scale,
"seed": seed if seed is not None else random.randint(-1, 2147483647)
}
elif image_style == "Cinematic":
payload = {
"inputs": prompt + ", realistic, detailed, textured, skin, hair, eyes, by Alex Huguet, Mike Hill, Ian Spriggs, JaeCheol Park, Marek Denko",
"is_negative": is_negative + ", abstract, cartoon, stylized",
"steps": steps,
"cfg_scale": cfg_scale,
"seed": seed if seed is not None else random.randint(-1, 2147483647)
}
elif image_style == "Digital Art":
payload = {
"inputs": prompt + ", faded , vintage , nostalgic , by Jose Villa , Elizabeth Messina , Ryan Brenizer , Jonas Peterson , Jasmine Star",
"is_negative": is_negative + ", sharp , modern , bright",
"steps": steps,
"cfg_scale": cfg_scale,
"seed": seed if seed is not None else random.randint(-1, 2147483647)
}
elif image_style == "Portrait":
payload = {
"inputs": prompt + ", soft light, sharp, exposure blend, medium shot, bokeh, (hdr:1.4), high contrast, (cinematic, teal and orange:0.85), (muted colors, dim colors, soothing tones:1.3), low saturation, (hyperdetailed:1.2), (noir:0.4), (natural skin texture, hyperrealism, soft light, sharp:1.2)",
"is_negative": is_negative,
"steps": steps,
"cfg_scale": cfg_scale,
"seed": seed if seed is not None else random.randint(-1, 2147483647)
}
image_bytes = requests.post(API_URL, headers=headers, json=payload).content
image = Image.open(io.BytesIO(image_bytes))
return image
gr.Interface(
fn=generate_txt2img,
inputs=[
gr.inputs.Dropdown(label="Current Model", choices=list_models, default=list_models[1]),
gr.inputs.Textbox(label="Prompt", placeholder="a cute dog", lines=1),
gr.inputs.Checkbox(label="Negative Prompt"),
gr.inputs.Dropdown(label="Style", choices=["None style", "Cinematic", "Digital Art", "Portrait"], default="None style"),
gr.inputs.Number(label="Steps", default=50),
gr.inputs.Number(label="Cfg Scale", default=7),
gr.inputs.Number(label="Seed (Optional)"),
],
outputs=gr.outputs.Image(type="pil", label="Output Image"),
title="AI Diffusion",
css="""
/* Add your custom CSS styles here */
""",
).launch()
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