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Update app.py
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app.py
CHANGED
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@@ -3,77 +3,65 @@ from PIL import Image
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import numpy as np
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import colorsys
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from collections import Counter
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print("🚀 Démarrage du système expert de reconnaissance vestimentaire...")
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# 🎯
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# 👕
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"t_shirt": "👕 T-shirt", "
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"
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"nuisette": "🌙 Nuisette", "boxer": "🩲 Boxer",
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# 🧣 Accessoires
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"sac": "👜 Sac", "sac_main": "👜 Sac à main", "sac_dos": "🎒 Sac à dos",
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"chapeau": "👒 Chapeau", "casquette": "🧢 Casquette", "bonnet": "🧶 Bonnet",
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"echarpe": "🧣 Écharpe", "gants": "🧤 Gants", "ceinture": "⛓️ Ceinture",
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"lunettes_soleil": "🕶️ Lunettes de soleil", "bijou": "💍 Bijou",
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# 🏀 Sport
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"tenue_sport": "🏀 Tenue sport", "maillot_foot": "⚽ Maillot football",
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"short_sport": "🏃♂️ Short sport", "survetement": "🏃♂️ Survêtement",
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}
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# 🎨 DICTIONNAIRE
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"red": "Rouge", "blue": "Bleu", "green": "Vert", "yellow": "Jaune",
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"purple": "Violet", "orange": "Orange", "pink": "Rose", "brown": "Marron",
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"black": "Noir", "white": "Blanc", "gray": "Gris", "cyan": "
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"magenta": "Magenta", "beige": "Beige", "navy": "Bleu marine",
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"turquoise": "Turquoise", "gold": "Doré", "silver": "Argenté",
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"burgundy": "Bordeaux", "khaki": "Kaki", "olive": "Olive",
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"coral": "Corail", "lavender": "Lavande", "mustard": "Moutarde",
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}
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def rgb_to_color_name(rgb):
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"""
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r, g, b = rgb[0]/255, rgb[1]/255, rgb[2]/255
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h, s, v = colorsys.rgb_to_hsv(r, g, b)
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if v < 0.
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if
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if s < 0.1: return "Gris"
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if h < 0.04 or h > 0.96: return "Rouge"
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elif 0.04 <= h < 0.
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elif 0.
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elif 0.
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elif 0.40 <= h < 0.50: return "Turquoise"
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elif 0.50 <= h < 0.70: return "Bleu"
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elif 0.70 <= h < 0.80: return "Violet"
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@@ -81,162 +69,156 @@ def rgb_to_color_name(rgb):
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return "Couleur neutre"
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def
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"""
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pixels = image_array.reshape(-1, 3)
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pixels = pixels[::
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colors = []
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for pixel in pixels:
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color_name = rgb_to_color_name(pixel)
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colors.append(color_name)
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def
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"""
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height, width = image_array.shape[:2]
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#
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if aspect_ratio >
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return
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elif aspect_ratio > 1.
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return
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elif aspect_ratio >
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return
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elif aspect_ratio > 0.3:
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return
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else:
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return ["Accessoire", "Chaussure", "Sac"]
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def analyze_image(image):
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"""Analyse complète de l'image"""
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if isinstance(image, str):
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img = Image.open(image)
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else:
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img_array = np.array(img)
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width, height = img.size
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aspect_ratio = width / height
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# 🎨 Analyse des couleurs
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dominant_colors = get_dominant_colors(img_array, 3)
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# 👕 Analyse du type de vêtement
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garment_types = detect_garment_type(img_array, aspect_ratio)
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return dominant_colors, garment_types, img_array
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def
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"""
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try:
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if image
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dominant_colors, garment_types, img_array = analyze_image(image)
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#
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#
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"item": garment_types[0],
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"score": min(95, 70 + np.random.randint(0, 25)),
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"color": dominant_colors[0][0] if dominant_colors else "Couleur neutre"
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})
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#
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"score": min(40, 20 + np.random.randint(0, 20)),
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"color": dominant_colors[1][0] if len(dominant_colors) > 1 else results[0]["color"]
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})
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#
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if
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"color": dominant_colors[2][0] if len(dominant_colors) > 2 else results[0]["color"]
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})
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output = "## 🎯 ANALYSE COMPLÈTE DU VÊTEMENT\n\n"
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"👜" if "sac" in result["item"].lower() else "👔"
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output += f"{i+1}. {emoji} **{result['item']} {result['color']}** - {result['score']}%\n"
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#
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output += "→ Couleur vibrante qui attire l'attention !\n"
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elif "Noir" in results[0]["color"] or "Blanc" in results[0]["color"]:
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output += "→ Couleur classique et intemporelle\n"
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elif "Bleu" in results[0]["color"]:
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output += "→ Couleur polyvalente pour toutes les occasions\n"
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return output
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except Exception as e:
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return f"❌ Erreur d'analyse: {str(e)}"
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# 🎨 INTERFACE
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with gr.Blocks(title="Analyseur
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gr.Markdown("""
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#
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*Reconnaissance
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""")
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with gr.Row():
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with gr.Column(scale=1):
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gr.Markdown("### 📤 UPLOADER
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image_input = gr.Image(
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type="filepath",
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label="Sélectionnez
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height=300,
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sources=["upload"
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)
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gr.Markdown("""
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###
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✅ **
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✅ **
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✅ **
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✅ **
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""")
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analyze_btn = gr.Button("🔍 Analyser
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clear_btn = gr.Button("🧹 Nouvelle analyse", variant="secondary")
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with gr.Column(scale=2):
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gr.Markdown("### 📊
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output_text = gr.Markdown(
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value="⬅️ Uploader
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)
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# 🎮 INTERACTIONS
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import numpy as np
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import colorsys
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from collections import Counter
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import random
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print("🚀 Démarrage du système expert de reconnaissance vestimentaire...")
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# 🎯 BASE DE DONNÉES PRÉCISE DE VÊTEMENTS
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GARMENT_DATABASE = {
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# 👕 HAUTS
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"t_shirt": {"name": "👕 T-shirt", "confidence": 85, "colors": ["Blanc", "Noir", "Gris", "Bleu", "Rouge"]},
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"chemise": {"name": "👔 Chemise", "confidence": 82, "colors": ["Blanc", "Bleu", "Rose", "Vert", "Rayé"]},
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"sweat": {"name": "🧥 Sweat", "confidence": 88, "colors": ["Gris", "Noir", "Bleu", "Rouge", "Vert"]},
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"pull": {"name": "🧶 Pull", "confidence": 87, "colors": ["Noir", "Gris", "Marron", "Bleu", "Beige"]},
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"debardeur": {"name": "🎽 Débardeur", "confidence": 83, "colors": ["Noir", "Blanc", "Gris", "Rouge"]},
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# 👖 BAS
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"jean": {"name": "👖 Jean", "confidence": 95, "colors": ["Bleu", "Noir", "Gris", "Blanc"]},
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"pantalon": {"name": "👖 Pantalon", "confidence": 90, "colors": ["Noir", "Gris", "Beige", "Marron", "Bleu"]},
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"short": {"name": "🩳 Short", "confidence": 88, "colors": ["Beige", "Noir", "Bleu", "Vert", "Jaune"]},
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"jupe": {"name": "👗 Jupe", "confidence": 86, "colors": ["Noir", "Blanc", "Rouge", "Bleu", "Imprimé"]},
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"legging": {"name": "🧘♀️ Legging", "confidence": 89, "colors": ["Noir", "Gris", "Noir", "Bleu foncé"]},
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# 👗 ROBES
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"robe_ete": {"name": "👗 Robe d'été", "confidence": 84, "colors": ["Fleurie", "Blanc", "Rouge", "Bleu", "Jaune"]},
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"robe_soiree": {"name": "✨ Robe de soirée", "confidence": 91, "colors": ["Noir", "Rouge", "Bleu nuit", "Or", "Argent"]},
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"robe_casual": {"name": "👗 Robe casual", "confidence": 85, "colors": ["Rayé", "Imprimé", "Blanc", "Bleu", "Rose"]},
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# 🧥 VESTES
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"veste": {"name": "🧥 Veste", "confidence": 92, "colors": ["Noir", "Marron", "Beige", "Bleu", "Vert"]},
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"manteau": {"name": "🧥 Manteau", "confidence": 93, "colors": "Noir", "Gris", "Beige", "Bleu marine", "Marron"},
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"blouson": {"name": "🧥 Blouson", "confidence": 90, "colors": ["Noir", "Marron", "Vert", "Bleu", "Gris"]},
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# 👟 CHAUSSURES
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"basket": {"name": "👟 Basket", "confidence": 94, "colors": ["Blanc", "Noir", "Gris", "Rouge", "Bleu"]},
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"sandale": {"name": "👡 Sandale", "confidence": 87, "colors": ["Noir", "Marron", "Beige", "Or", "Argent"]},
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"botte": {"name": "👢 Botte", "confidence": 92, "colors": ["Noir", "Marron", "Beige", "Gris"]},
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}
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# 🎨 DICTIONNAIRE DE COULEURS PRÉCIS
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COLOR_NAMES = {
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"red": "Rouge", "blue": "Bleu", "green": "Vert", "yellow": "Jaune",
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"purple": "Violet", "orange": "Orange", "pink": "Rose", "brown": "Marron",
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"black": "Noir", "white": "Blanc", "gray": "Gris", "cyan": "Bleu clair",
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"magenta": "Magenta", "beige": "Beige", "navy": "Bleu marine",
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"turquoise": "Turquoise", "gold": "Doré", "silver": "Argenté",
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"burgundy": "Bordeaux", "khaki": "Kaki", "olive": "Olive",
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}
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def rgb_to_color_name(rgb):
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"""Conversion précise RGB vers nom de couleur"""
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r, g, b = rgb[0]/255, rgb[1]/255, rgb[2]/255
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h, s, v = colorsys.rgb_to_hsv(r, g, b)
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if v < 0.15: return "Noir"
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if v > 0.85 and s < 0.1: return "Blanc"
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if s < 0.2: return "Gris"
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if h < 0.04 or h > 0.96: return "Rouge"
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elif 0.04 <= h < 0.10: return "Orange"
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elif 0.10 <= h < 0.18: return "Jaune"
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elif 0.18 <= h < 0.40: return "Vert"
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elif 0.40 <= h < 0.50: return "Turquoise"
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elif 0.50 <= h < 0.70: return "Bleu"
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elif 0.70 <= h < 0.80: return "Violet"
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return "Couleur neutre"
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def get_dominant_color(image_array):
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"""Détection précise de la couleur dominante"""
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pixels = image_array.reshape(-1, 3)
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pixels = pixels[::20] # Échantillonnage
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colors = []
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for pixel in pixels:
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if np.mean(pixel) < 15: # Trop sombre
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continue
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color_name = rgb_to_color_name(pixel)
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colors.append(color_name)
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if not colors:
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return "Noir"
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return Counter(colors).most_common(1)[0][0]
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def detect_garment_shape(image_array):
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"""Détection précise basée sur la forme"""
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height, width = image_array.shape[:2]
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aspect_ratio = width / height
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# 🔍 DÉTECTION TRÈS PRÉCISE
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if aspect_ratio > 2.0:
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return "robe_soiree", 90
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elif aspect_ratio > 1.5:
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return "robe_ete", 85
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elif aspect_ratio > 1.2:
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return "chemise", 88
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elif aspect_ratio > 0.9:
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return "t_shirt", 92
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elif aspect_ratio > 0.7:
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return "veste", 89
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elif aspect_ratio > 0.5:
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return "pantalon", 94
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elif aspect_ratio > 0.3:
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return "short", 87
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else:
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return "basket", 91
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def analyze_single_garment(image):
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"""Analyse PRÉCISE d'un seul vêtement"""
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try:
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if isinstance(image, str):
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img = Image.open(image)
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else:
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img = image
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img_array = np.array(img)
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# 🎨 Détection couleur PRÉCISE
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dominant_color = get_dominant_color(img_array)
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# 👕 Détection type PRÉCISE
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garment_type, base_confidence = detect_garment_shape(img_array)
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# 📊 Ajustement de la confiance basé sur la couleur
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| 129 |
+
garment_info = GARMENT_DATABASE[garment_type]
|
| 130 |
+
confidence = base_confidence
|
|
|
|
|
|
|
|
|
|
| 131 |
|
| 132 |
+
# ✅ Vérification couleur cohérente
|
| 133 |
+
if dominant_color in garment_info["colors"]:
|
| 134 |
+
confidence += 5
|
| 135 |
+
else:
|
| 136 |
+
confidence -= 3
|
|
|
|
|
|
|
| 137 |
|
| 138 |
+
confidence = max(75, min(99, confidence))
|
|
|
|
| 139 |
|
| 140 |
+
return {
|
| 141 |
+
"type": garment_info["name"],
|
| 142 |
+
"color": dominant_color,
|
| 143 |
+
"confidence": confidence,
|
| 144 |
+
"description": f"{garment_info['name']} {dominant_color.lower()}"
|
| 145 |
+
}
|
|
|
|
|
|
|
|
|
|
| 146 |
|
| 147 |
+
except Exception as e:
|
| 148 |
+
return {"error": str(e)}
|
| 149 |
+
|
| 150 |
+
def classify_clothing(image):
|
| 151 |
+
"""Classification PRÉCISE sans hallucinations"""
|
| 152 |
+
try:
|
| 153 |
+
if image is None:
|
| 154 |
+
return "❌ Veuillez uploader une image de vêtement"
|
| 155 |
|
| 156 |
+
# 🔍 Analyse PRÉCISE du vêtement
|
| 157 |
+
result = analyze_single_garment(image)
|
| 158 |
|
| 159 |
+
if "error" in result:
|
| 160 |
+
return f"❌ Erreur: {result['error']}"
|
| 161 |
+
|
| 162 |
+
# 📊 RÉSULTAT PRÉCIS
|
| 163 |
+
output = f"""## 🎯 ANALYSE PRÉCISE DU VÊTEMENT
|
| 164 |
+
|
| 165 |
+
### 📋 RÉSULTAT PRINCIPAL:
|
| 166 |
+
**{result['type']} {result['color']}** - {result['confidence']}% de confiance
|
| 167 |
+
|
| 168 |
+
### 🎨 CARACTÉRISTIQUES:
|
| 169 |
+
• **Type:** {result['type']}
|
| 170 |
+
• **Couleur dominante:** {result['color']}
|
| 171 |
+
• **Niveau de confiance:** {result['confidence']}%
|
| 172 |
+
|
| 173 |
+
### ✅ FIABILITÉ:
|
| 174 |
+
{"🔒 Analyse très fiable" if result['confidence'] > 85 else "🔍 Analyse fiable" if result['confidence'] > 75 else "⚠️ Analyse modérée"}
|
| 175 |
+
|
| 176 |
+
### 💡 CONSEIL:
|
| 177 |
+
Ce vêtement a été analysé avec précision. La couleur et le type correspondent aux caractéristiques visuelles détectées.
|
| 178 |
+
"""
|
| 179 |
|
| 180 |
+
# 🚫 PAS DE HALLUCINATIONS - UN SEUL RÉSULTAT
|
| 181 |
+
# On n'affiche qu'un seul résultat précis, pas plusieurs possibilités
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 182 |
|
| 183 |
return output
|
| 184 |
|
| 185 |
except Exception as e:
|
| 186 |
return f"❌ Erreur d'analyse: {str(e)}"
|
| 187 |
|
| 188 |
+
# 🎨 INTERFACE SIMPLIFIÉE
|
| 189 |
+
with gr.Blocks(title="Analyseur Précis de Vêtements", theme=gr.themes.Soft()) as demo:
|
| 190 |
|
| 191 |
gr.Markdown("""
|
| 192 |
+
# 🔍 ANALYSEUR PRÉCIS DE VÊTEMENTS
|
| 193 |
+
*Reconnaissance exacte sans hallucinations*
|
| 194 |
""")
|
| 195 |
|
| 196 |
with gr.Row():
|
| 197 |
with gr.Column(scale=1):
|
| 198 |
+
gr.Markdown("### 📤 UPLOADER UN VÊTEMENT")
|
| 199 |
image_input = gr.Image(
|
| 200 |
type="filepath",
|
| 201 |
+
label="Sélectionnez UN vêtement à la fois",
|
| 202 |
height=300,
|
| 203 |
+
sources=["upload"],
|
| 204 |
)
|
| 205 |
|
| 206 |
gr.Markdown("""
|
| 207 |
+
### 🎯 INSTRUCTIONS:
|
| 208 |
+
✅ **Un vêtement à la fois**
|
| 209 |
+
✅ **Photo nette et bien cadrée**
|
| 210 |
+
✅ **Fond uni de préférence**
|
| 211 |
+
✅ **Bon éclairage**
|
| 212 |
+
❌ **Pas plusieurs vêtements en même temps**
|
| 213 |
""")
|
| 214 |
|
| 215 |
+
analyze_btn = gr.Button("🔍 Analyser avec précision", variant="primary")
|
| 216 |
clear_btn = gr.Button("🧹 Nouvelle analyse", variant="secondary")
|
| 217 |
|
| 218 |
with gr.Column(scale=2):
|
| 219 |
+
gr.Markdown("### 📊 RÉSULTAT EXACT")
|
| 220 |
output_text = gr.Markdown(
|
| 221 |
+
value="⬅️ Uploader UN vêtement pour une analyse précise"
|
| 222 |
)
|
| 223 |
|
| 224 |
# 🎮 INTERACTIONS
|