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import gradio as gr
import requests
from PIL import Image
import io
from gradio.themes.base import Base
import os
from dotenv import load_dotenv
load_dotenv()
def process_images(face_image, model_image, watermark = False, vignette = False, quality = 100):
# Convertir las imágenes PIL a bytes
model_img_bytes = io.BytesIO()
model_image.save(model_img_bytes, format='PNG')
face_img_bytes = io.BytesIO()
face_image.save(face_img_bytes, format='PNG')
# Configurar los datos para la solicitud HTTP
url = os.getenv('URL')
files = [
('images', ('face.png', face_img_bytes.getvalue(), 'image/jpeg')),
('images', ('model.png', model_img_bytes.getvalue(), 'image/png'))
]
data = {
'watermark': 0,
}
response = requests.post(url, files=files, data=data)
if response.status_code == 200:
# Log the Content-Type to ensure it's an image
#print("Content-Type:", response.headers.get('Content-Type'))
#print(response.content)
# Attempt to open the response content as an image
try:
return Image.open(io.BytesIO(response.content))
except Exception as e:
print(f"Error opening image: {e}")
return None # Return None or handle the error as needed
else:
raise ValueError(f"Error in the request: Status Code {response.status_code}")
# Crear la interfaz de Gradio
iface = gr.Interface(
fn=process_images,
inputs=[
gr.Image(type="pil", label="Face Image"),
gr.Image(type="pil", label="Model Image")
],
outputs=gr.Image(type="pil", label="Result Image"),
title="StoryFace Internal Tool",
description="<h2 style='text-align: center; font-size: 24px;'>Take a photo or upload a clear photo of your face, upload a photo of the model you want to see yourself in, and press the submit button..</h2>",
allow_flagging="never"
)
# Ejecutar la aplicación
iface.launch()
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