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import gradio as gr
from gradio_client import Client
import os
import logging
from urllib.parse import parse_qs, urlparse
client_image = Client("mukaist/DALLE-4K")
resolutions = {
"896x1152": (896, 1152),
"1024x1024": (1024, 1024),
"1216x832": (1216, 832)
}
DEFAULT_STYLE = "3840 x 2160"
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
def generate_image(prompt, resolution_key, style=DEFAULT_STYLE):
resolution = resolutions.get(resolution_key, (1024, 1024))
width, height = resolution
full_prompt = f"{prompt}, Canon EOS R5, 4K, Photo-Realistic, appearing photorealistic with super fine details, high resolution, natural look, hyper realistic photography, cinematic lighting, --ar 64:37, --v 6.0, --style raw, --stylize 750"
try:
result = client_image.predict(
prompt=full_prompt,
negative_prompt="(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation",
use_negative_prompt=True,
style=style,
seed=0,
width=width,
height=height,
guidance_scale=5,
randomize_seed=True,
api_name="/run"
)
logger.info("Image generation successful.")
return result
except Exception as e:
logger.error(f"Error generating image: {e}")
return None
def gradio_interface(prompt, resolution_key):
result = generate_image(prompt, resolution_key)
if result and result[0]:
file_path = result[0][0].get('image')
if file_path and os.path.exists(file_path):
return file_path, "The image was generated successfully."
else:
return None, "The image file is not available. Please try again later."
else:
return None, "There was an error processing your photo. Please try again later."
def create_gradio_interface(username):
prompt_input = gr.Textbox(label="Prompt", placeholder="Enter your prompt here...")
resolution_dropdown = gr.Dropdown(choices=list(resolutions.keys()), label="Resolution", value="1024x1024")
generate_button = gr.Button("Generate")
result_output = gr.Image(label="Generated Image", type="pil")
message_output = gr.Textbox(label="Result", placeholder="Results will be shown here", interactive=False)
generate_button.click(fn=lambda prompt, resolution_key: gradio_interface(prompt, resolution_key),
inputs=[prompt_input, resolution_dropdown],
outputs=[result_output, message_output])
with gr.Blocks() as interface:
gr.HTML(f"""
<script src="https://telegram.org/js/telegram-web-app.js"></script>
<script>
document.addEventListener('DOMContentLoaded', function() {{
window.Telegram.WebApp.init();
window.Telegram.WebApp.setTitle("Welcome, {username}!");
}});
</script>
<h3>Welcome, {username}! Generate images based on prompts.</h3>
""")
gr.HTML("""
<style>
footer.svelte-1rjryqp {
display: none !important;
}
</style>
""")
return interface
def launch_gradio(username):
interface = create_gradio_interface(username)
interface.launch()
def extract_username_from_url(url):
parsed_url = urlparse(url)
params = parse_qs(parsed_url.query)
return params.get('username', ["Guest"])[0]
def get_username_from_url():
# Placeholder URL; replace with actual URL or method to get URL in deployment
url = 'https://measmonysuon-imagen.hf.space/?username=MoMo'
username = extract_username_from_url(url)
logger.info(f"Extracted username: {username}")
return username
username = get_username_from_url()
launch_gradio(username) |