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import gradio as gr
from gradio_client import Client
import random
# Initialize the client for the Hugging Face Space
client = Client("ByteDance/Hyper-FLUX-8Steps-LoRA")
def generate_image(prompt, height, width, steps, scales, seed):
"""
Generates an image based on the provided parameters by calling the Hugging Face Space API.
Parameters:
- prompt (str): The text prompt for image generation.
- height (int): The height of the generated image.
- width (int): The width of the generated image.
- steps (int): The number of steps for the image generation process.
- scales (float): The scaling factor.
- seed (int): The seed for random number generation to ensure reproducibility.
Returns:
- result (str or Image): The generated image or a link to it.
"""
# Generate a random seed if not provided
if not seed:
seed = random.randint(0, 100000)
try:
result = client.predict(
height=int(height),
width=int(width),
steps=int(steps),
scales=float(scales),
prompt=prompt,
seed=int(seed),
api_name="/process_image"
)
return result
except Exception as e:
return f"An error occurred: {e}"
# Define the Gradio interface
with gr.Blocks() as demo:
gr.Markdown("# Hyper-FLUX-8Steps-LoRA Image Generator")
gr.Markdown("Generate images based on your text prompts using the Hyper-FLUX-8Steps-LoRA model.")
with gr.Row():
with gr.Column():
prompt = gr.Textbox(
label="Prompt",
placeholder="Enter your descriptive text here...",
lines=2
)
height = gr.Number(
label="Height",
value=1024,
precision=0,
interactive=True
)
width = gr.Number(
label="Width",
value=1024,
precision=0,
interactive=True
)
steps = gr.Number(
label="Steps",
value=8,
precision=0,
interactive=True
)
scales = gr.Number(
label="Scale",
value=3.5,
precision=1,
interactive=True
)
seed = gr.Number(
label="Seed",
value=3413,
precision=0,
interactive=True
)
generate_button = gr.Button("Generate Image")
with gr.Column():
output_image = gr.Image(label="Generated Image", interactive=False)
# Define the button click action
generate_button.click(
fn=generate_image,
inputs=[prompt, height, width, steps, scales, seed],
outputs=output_image
)
# Optional: Add a footer or additional information
gr.Markdown("© 2024 Your Name. All rights reserved.")
# Launch the Gradio app
if __name__ == "__main__":
demo.launch()
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