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Update app.py
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app.py
CHANGED
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import gradio as gr
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import random
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import time
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from PIL import Image
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import requests
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from io import BytesIO
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# Styles disponibles
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STYLES = {
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]
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}
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def
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"""
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"""
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#
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def update_suggestions(style):
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"""
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"""
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return gr.Dropdown(choices=PROMPT_SUGGESTIONS.get(style, []))
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def get_example_prompt(style):
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"""
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Obtenir un prompt exemple du style sélectionné
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"""
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suggestions = PROMPT_SUGGESTIONS.get(style, [])
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return random.choice(suggestions) if suggestions else ""
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown(
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"""
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)
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with gr.Row():
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# Panneau de gauche - Contrôles
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with gr.Column(scale=1):
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# Section Style
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style = gr.Radio(
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choices=list(STYLES.keys()),
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value="signage",
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info="Choisissez le type de design souhaité"
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)
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# Section Format
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format_size = gr.Radio(
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choices=FORMATS,
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value="A4",
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info="Sélectionnez la taille de votre création"
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)
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# Section Matériau
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material = gr.Radio(
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choices=MATERIALS,
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value="Lisse",
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info="Choisissez votre matériau"
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)
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# Section Prompt
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prompt = gr.Textbox(
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lines=3,
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label="Description",
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placeholder="Décrivez votre vision..."
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)
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# Suggestions de prompts
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suggestions = gr.Dropdown(
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choices=PROMPT_SUGGESTIONS["signage"],
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label="Suggestions de prompts",
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info="Sélectionnez une suggestion ou écrivez votre propre description"
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)
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# Bouton de génération
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generate_btn = gr.Button("🪄 Générer", variant="primary")
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# Panneau de droite - Prévisualisation
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with gr.Column(scale=2):
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output = gr.Image(label="Image générée")
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# Interactions
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style.change(
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fn=update_suggestions,
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inputs=[style],
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)
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generate_btn.click(
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fn=
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inputs=[prompt, style, format_size, material],
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outputs=[output]
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)
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"""
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)
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# Lancement de l'interface
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demo.launch()
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import gradio as gr
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import random
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from PIL import Image
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import requests
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from io import BytesIO
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import os
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# Token Hugging Face - À remplacer par votre token
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HF_TOKEN = "hf_..." # Mettez votre token ici
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# Styles disponibles
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STYLES = {
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]
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}
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def generate_image(prompt, style, format_size, material):
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"""
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Génération d'image via l'API Hugging Face
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"""
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API_URL = "https://api-inference.huggingface.co/models/runwayml/stable-diffusion-v1-5"
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headers = {"Authorization": f"Bearer {HF_TOKEN}"}
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# Style prompts pour améliorer la génération
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style_prompts = {
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"signage": "professional signage design, minimalist, clean",
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"poster": "artistic poster design, creative, expressive",
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"silhouette": "decorative silhouette, elegant cutout design"
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}
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# Enrichir le prompt
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enhanced_prompt = f"{prompt}, {style_prompts[style]}, made of {material} cardboard, eco-friendly design, high quality, professional, detailed"
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payload = {
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"inputs": enhanced_prompt,
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"negative_prompt": "low quality, blurry, bad anatomy, distorted, pixelated",
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}
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try:
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response = requests.post(API_URL, headers=headers, json=payload)
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if response.status_code == 200:
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image_bytes = response.content
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return Image.open(BytesIO(image_bytes))
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else:
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print(f"Erreur API : {response.status_code}")
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return Image.new('RGB', (512, 512), color='lightgray')
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except Exception as e:
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print(f"Erreur de génération : {e}")
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return Image.new('RGB', (512, 512), color='lightgray')
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def update_suggestions(style):
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"""
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"""
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return gr.Dropdown(choices=PROMPT_SUGGESTIONS.get(style, []))
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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gr.Markdown(
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"""
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)
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with gr.Row():
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with gr.Column(scale=1):
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style = gr.Radio(
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choices=list(STYLES.keys()),
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value="signage",
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info="Choisissez le type de design souhaité"
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)
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format_size = gr.Radio(
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choices=FORMATS,
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value="A4",
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info="Sélectionnez la taille de votre création"
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)
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material = gr.Radio(
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choices=MATERIALS,
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value="Lisse",
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info="Choisissez votre matériau"
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)
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prompt = gr.Textbox(
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lines=3,
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label="Description",
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placeholder="Décrivez votre vision..."
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)
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suggestions = gr.Dropdown(
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choices=PROMPT_SUGGESTIONS["signage"],
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label="Suggestions de prompts",
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info="Sélectionnez une suggestion ou écrivez votre propre description"
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)
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generate_btn = gr.Button("🪄 Générer", variant="primary")
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with gr.Column(scale=2):
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output = gr.Image(label="Image générée")
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style.change(
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fn=update_suggestions,
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inputs=[style],
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)
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generate_btn.click(
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fn=generate_image,
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inputs=[prompt, style, format_size, material],
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outputs=[output]
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)
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"""
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)
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demo.launch()
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