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FashionLook
File size: 2,404 Bytes 
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import os
import gradio as gr
import numpy as np
from PIL import Image

#Fonction du modèle provisoire
def segment_image(image):
    overlay_image = image.copy()
    return overlay_image

def create_interface():
    with gr.Blocks() as interface:
        gr.HTML(
        """<style>
        @import url('https://fonts.googleapis.com/css2?family=Poppins:wght@600&family=Roboto:wght@400&display=swap');

        body { background-color: #f0f0f0; font-family: 'Roboto', sans-serif; }
        h1 { font-family: 'Poppins', sans-serif; color: #4CAF50; text-align: center; }
        h3 { font-family: 'Roboto', sans-serif; color: #333; text-align: center; }
        .segment-btn { 
            background-color: #4CAF50; 
            border-radius: 8px; 
            padding: 10px 20px; 
            color: white; 
            transition: background-color 0.3s ease, transform 0.2s ease;
        }
        .segment-btn:hover {
            background-color: #45a049; 
            transform: scale(1.05);
        }
        .logo { 
            display: block; 
            margin: 0 auto; 
            width: 150px; 
            height: auto; 
            padding: 20px 0;
        }
        </style>"""
        )
        logo_path = os.path.join(os.getcwd(), 'fashionlookl1.webp')
        gr.Markdown("<img src=logo_path class='logo' alt='Logo'>")
        gr.Markdown("<h1>FashionLook - Segment Clothes</h1>")
        gr.Markdown("<h3 style='text-align: center;'>" "Upload an image and let our model detect and segment clothes such as shirts, pants, skirts...""</h3>")
        with gr.Row():
            with gr.Column(scale=1):
                gr.Markdown("<h5>Upload your image</h5>")
                image_input = gr.Image(type='pil', label="Upload Image", shape=(512, 512))
                with gr.Row():
                    segment_button = gr.Button("Run Segmentation", elem_id="segment-btn")
            with gr.Column(scale=1):
                gr.Markdown("<h5>Segmented Image with Overlay</h5>")
                segmented_image_output = gr.Image(type="pil", label="Segmented Image", interactive=False)
        
        # Actions liées aux inputs/outputs
        segment_button.click(
            fn=segment_image, 
            inputs=[image_input], 
            outputs=[segmented_image_output]
        )
    
    return interface

# Lancer l'interface
interface = create_interface()
interface.launch()