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Running
on
Zero
File size: 3,027 Bytes
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import gradio as gr
import os
import tempfile
from main import process_face
from PIL import Image
def enhance_face_gradio(input_image, ref_image):
"""
Wrapper function for process_face that works with Gradio.
Args:
input_image: Input image from Gradio
ref_image: Reference face image from Gradio
Returns:
PIL Image: Enhanced image
"""
# Create temporary files for input, reference, and output
with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as input_file, \
tempfile.NamedTemporaryFile(suffix=".png", delete=False) as ref_file, \
tempfile.NamedTemporaryFile(suffix=".png", delete=False) as output_file:
input_path = input_file.name
ref_path = ref_file.name
output_path = output_file.name
# Save uploaded images to temporary files
input_image.save(input_path)
ref_image.save(ref_path)
try:
# Process the face
process_face(
input_path=input_path,
ref_path=ref_path,
crop=False,
upscale=False,
output_path=output_path
)
except Exception as e:
# Handle the error, log it, and return an error message
print(f"Error processing face: {e}")
return "An error occurred while processing the face. Please try again."
finally:
# Clean up temporary input and reference files
os.unlink(input_path)
os.unlink(ref_path)
return Image.open(output_path)
def create_gradio_interface():
# Create the Gradio interface
with gr.Blocks(title="Face Enhancement Demo") as demo:
gr.Markdown("# Face Enhancement Demo")
gr.Markdown("Upload an input image and a reference face image to enhance the input.")
with gr.Row():
with gr.Column():
input_image = gr.Image(label="Input Image", type="pil")
ref_image = gr.Image(label="Reference Face", type="pil")
enhance_button = gr.Button("Enhance Face")
with gr.Column():
output_image = gr.Image(label="Enhanced Result")
enhance_button.click(
fn=enhance_face_gradio,
inputs=[input_image, ref_image],
outputs=output_image,
queue=True # Enable queue for sequential processing
)
gr.Markdown("""
## Instructions
1. Upload an image you want to enhance
2. Upload a reference face image
3. Click 'Enhance Face' to start the process
4. Processing takes about 60 seconds
""")
# Launch the Gradio app with queue
demo.queue(max_size=20) # Configure queue size
demo.launch(
share=False, # Set to True if you want a public link
server_name="0.0.0.0", # Make available on all network interfaces
server_port=7860, # Default Gradio port
)
if __name__ == "__main__":
create_gradio_interface() |