File size: 2,609 Bytes
ece86db |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 |
import warnings
warnings.filterwarnings("ignore")
import gradio as gr
from gradio_client import Client, handle_file
def generate_image(prompt, image_url=None, image_file=None):
# Initialize the client
client = Client("yanze/PuLID-FLUX")
# Determine input image
if image_url:
id_image = handle_file(image_url)
elif image_file:
id_image = handle_file(image_file.name)
else:
return "Error: Please provide an image URL or upload an image file."
# Predict
try:
result = client.predict(
prompt=prompt,
id_image=id_image,
start_step=0,
guidance=2,
seed="-1",
true_cfg=1,
width=896,
height=1152,
num_steps=20,
id_weight=1,
neg_prompt="bad quality, worst quality, text, signature, watermark, extra limbs",
timestep_to_start_cfg=1,
max_sequence_length=128,
api_name="/generate_image"
)
# Extract the base URL and file path
base_url = "https://yanze-pulid-flux.hf.space/file="
file_path = result[0] # The first element contains the file path of the primary result
full_url = f"{base_url}{file_path}"
return full_url
except Exception as e:
return f"Error during prediction: {str(e)}"
# Gradio interface
def gradio_interface():
with gr.Blocks() as demo:
gr.Markdown("# Image Generation App\nUpload an image or provide an image URL, and enter a prompt to generate a new image.")
with gr.Row():
prompt = gr.Textbox(label="Prompt", placeholder="Enter your prompt, e.g., portrait, color, cinematic")
image_url = gr.Textbox(label="Image URL", placeholder="Enter the image URL (optional)")
image_file = gr.File(label="Upload Image", file_types=["image"])
with gr.Row():
submit_button = gr.Button("Generate Image")
output = gr.Textbox(label="Generated Image URL")
output_image = gr.Image(label="Generated Image")
def process(prompt, image_url, image_file):
result_url = generate_image(prompt, image_url, image_file)
if result_url.startswith("http"):
return result_url, result_url
else:
return result_url, None
submit_button.click(
fn=process,
inputs=[prompt, image_url, image_file],
outputs=[output, output_image]
)
return demo
if __name__ == "__main__":
demo = gradio_interface()
demo.launch() |