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import gradio as gr | |
import requests | |
from PIL import Image | |
from io import BytesIO | |
import base64 | |
api_url = "https://5cb20b40-572c-426f-9466-995256f9b6eb.id.repl.co/generate_image" | |
def generate_image(model, prompt, seed, negative_prompt, sampler, steps): | |
data = "?model=" + model + "&prompt=" + prompt + "&seed=" + str(seed) + "&negative_prompt=" + negative_prompt + "&sampler=" + sampler + "&steps=" + str(steps) | |
response = requests.post(api_url + data, timeout=400) | |
if response.status_code == 200: | |
img_base64 = response.json()["url"] | |
img_bytes = base64.b64decode(img_base64) | |
img = Image.open(BytesIO(img_bytes)) | |
return img | |
else: | |
return None | |
dropdown_model = gr.inputs.Dropdown(['Seek.art MEGA', 'Deliberate', 'Dreamlike Photoreal', 'Realistic Vision'], label="Model", default="Seek.art MEGA") | |
textbox_prompt = gr.inputs.Textbox(label="Prompt") | |
number_seed = gr.inputs.Number(label="Seed", default=0) | |
textbox_negative_prompt = gr.inputs.Textbox(label="Negative Prompt", default="") | |
dropdown_sampler = gr.inputs.Dropdown(["k_lms", "k_heun", "k_euler", "k_euler_a", "k_dpm_2", "k_dpm_2_a", "DDIM", "k_dpm_fast", "k_dpm_adaptive", "k_dpmpp_2m", "k_dpmpp_2s_a", "k_dpmpp_sde"], label="Sampler", default="k_dpmpp_2s_a") | |
number_steps = gr.inputs.Number(label="Steps", default=50) | |
inputs = [dropdown_model, textbox_prompt, number_seed, textbox_negative_prompt, dropdown_sampler, number_steps] | |
outputs = gr.outputs.Image(label="Generated Image", type="pil") | |
interface = gr.Interface( | |
fn=generate_image, | |
inputs=inputs, | |
outputs=outputs, | |
title="Image Generator", | |
description="Select options and enter a prompt to generate an image.", | |
examples=[], | |
layout="vertical", | |
theme="ParityError/Interstellar" # Ihr spezifiziertes Theme | |
) | |
interface.launch() | |