Update app.py

app.py

@@ -1,99 +1,219 @@
-<?php
-// [En-tête PHP existant]
-?>
+import streamlit as st
+from transformers import pipeline
+from PIL import Image, ImageDraw
+import torch
 
-<div class="min-h-screen bg-gray-100 dark:bg-gray-900 pt-20 scrollable-content">
-    <div id="fraktur-root" class="w-2/3 min-w-[800px] mx-auto p-4 ml-0">
-        <div class="bg-white dark:bg-gray-800 shadow-md rounded-lg overflow-hidden">
-            <!-- Titre -->
-            <div class="p-4 border-b border-gray-200 dark:border-gray-700">
-                <div class="flex items-center gap-2">
-                    <svg class="w-6 h-6 text-blue-500 dark:text-blue-400" fill="none" stroke="currentColor" viewBox="0 0 24 24">
-                        <path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" d="M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2"/>
-                    </svg>
-                    <h1 class="text-xl font-bold text-gray-900 dark:text-white">Fraktur Detektion</h1>
-                </div>
-            </div>
-
-            <!-- Conteneur iframe adaptatif -->
-            <div class="iframe-container relative w-full" style="padding-top: 80%;">
-                <iframe
-                    src="https://yassonee-radpid.hf.space"
-                    class="absolute top-0 left-0 w-full h-full border-none"
-                    id="frakturFrame"
-                ></iframe>
-            </div>
-        </div>
-    </div>
-</div>
+st.set_page_config(
+    page_title="Fraktur Detektion",
+    layout="wide",
+    initial_sidebar_state="collapsed"
+)
 
+st.markdown("""
 <style>
-/* Styles pour l'iframe adaptatif */
-.iframe-container {
-    position: relative;
-    width: 100%;
-    height: 0;
-    padding-top: 80%; /* Ratio 4:5 pour l'iframe */
-    overflow: hidden;
-}
-
-.iframe-container iframe {
-    position: absolute;
-    top: 0;
-    left: 0;
-    width: 100%;
-    height: 100%;
-    border: none;
-}
-
-/* Ajustements responsifs */
-@media (max-width: 1280px) {
-    #fraktur-root {
-        width: 80%;
+    /* Reset et base */
+    .stApp {
+        background-color: var(--background-color) !important;
+        padding: 0 !important;
+        overflow: hidden !important;
     }
-    .iframe-container {
-        padding-top: 90%;
+    
+    /* Variables de thème */
+    [data-theme="light"] {
+        --background-color: #ffffff;
+        --text-color: #1f2937;
+        --border-color: #e5e7eb;
+        --secondary-bg: #f3f4f6;
     }
-}
-
-@media (max-width: 768px) {
-    #fraktur-root {
-        width: 95%;
-        min-width: 0;
+    
+    [data-theme="dark"] {
+        --background-color: #1f2937;
+        --text-color: #f3f4f6;
+        --border-color: #4b5563;
+        --secondary-bg: #374151;
     }
-    .iframe-container {
-        padding-top: 100%;
+    
+    /* Layout principal */
+    .block-container {
+        padding: 0.5rem !important;
+        max-width: 100% !important;
     }
-}
-</style>
-
-<script>
-document.addEventListener('DOMContentLoaded', function() {
-    const iframe = document.getElementById('frakturFrame');
     
-    function updateTheme() {
-        const isDark = document.documentElement.classList.contains('dark');
-        iframe.contentWindow.postMessage({
-            type: 'theme-change',
-            theme: isDark ? 'dark' : 'light'
-        }, '*');
+    /* Contrôles et upload */
+    .uploadedFile {
+        border: 1px dashed var(--border-color);
+        border-radius: 0.375rem;
+        padding: 0.25rem;
+        background: var(--secondary-bg);
     }
     
-    const observer = new MutationObserver((mutations) => {
-        mutations.forEach((mutation) => {
-            if (mutation.attributeName === 'class') {
-                updateTheme();
-            }
-        });
-    });
-
-    observer.observe(document.documentElement, {
-        attributes: true,
-        attributeFilter: ['class']
-    });
+    /* Ajustement des colonnes */
+    [data-testid="column"] {
+        padding: 0 0.5rem !important;
+    }
+    
+    /* Images adaptatives */
+    .stImage > img {
+        width: 100% !important;
+        height: auto !important;
+        max-height: 400px !important;
+        object-fit: contain !important;
+    }
+    
+    /* Résultats */
+    .result-box {
+        padding: 0.375rem;
+        border-radius: 0.375rem;
+        margin: 0.25rem 0;
+        background: var(--secondary-bg);
+        border: 1px solid var(--border-color);
+        color: var(--text-color);
+    }
+    
+    /* Titres */
+    h2, h3 {
+        margin: 0 !important;
+        padding: 0.5rem 0 !important;
+        font-size: 1rem !important;
+        color: var(--text-color) !important;
+    }
     
-    iframe.addEventListener('load', updateTheme);
-});
-</script>
+    /* Nettoyage des éléments inutiles */
+    #MainMenu, footer, header, .viewerBadge_container__1QSob, .stDeployButton {
+        display: none !important;
+    }
+    
+    /* Ajustements espacement */
+    div[data-testid="stVerticalBlock"] {
+        gap: 0.5rem !important;
+    }
+    
+    .element-container {
+        margin: 0.25rem 0 !important;
+    }
+</style>
+""", unsafe_allow_html=True)
+
+@st.cache_resource
+def load_models():
+    return {
+        "KnochenAuge": pipeline("object-detection", model="D3STRON/bone-fracture-detr"),
+        "KnochenWächter": pipeline("image-classification", model="Heem2/bone-fracture-detection-using-xray"),
+        "RöntgenMeister": pipeline("image-classification", 
+            model="nandodeomkar/autotrain-fracture-detection-using-google-vit-base-patch-16-54382127388")
+    }
+
+def translate_label(label):
+    translations = {
+        "fracture": "Knochenbruch",
+        "no fracture": "Kein Bruch",
+        "normal": "Normal",
+        "abnormal": "Auffällig"
+    }
+    return translations.get(label.lower(), label)
+
+def draw_boxes(image, predictions):
+    draw = ImageDraw.Draw(image)
+    for pred in predictions:
+        box = pred['box']
+        label = f"{translate_label(pred['label'])} ({pred['score']:.2%})"
+        color = "#2563eb" if pred['score'] > 0.7 else "#eab308"
+        
+        draw.rectangle(
+            [(box['xmin'], box['ymin']), (box['xmax'], box['ymax'])],
+            outline=color,
+            width=2
+        )
+        
+        # Label plus compact
+        text_bbox = draw.textbbox((box['xmin'], box['ymin']-15), label)
+        draw.rectangle(text_bbox, fill=color)
+        draw.text((box['xmin'], box['ymin']-15), label, fill="white")
+    return image
+
+def main():
+    models = load_models()
+
+    # Disposition en deux colonnes principales
+    col1, col2 = st.columns([1, 2])
+
+    with col1:
+        st.markdown("### 📤 Röntgenbild Upload")
+        uploaded_file = st.file_uploader("", type=['png', 'jpg', 'jpeg'])
+        
+        if uploaded_file:
+            conf_threshold = st.slider(
+                "Konfidenzschwelle",
+                min_value=0.0, max_value=1.0,
+                value=0.60, step=0.05
+            )
+
+    with col2:
+        if uploaded_file:
+            image = Image.open(uploaded_file)
+            
+            st.markdown("### 🔍 Meinung der KI-Experten")
+            
+            # Analyse avec KnochenAuge (localisierung)
+            st.markdown("#### 👁️ Das KnochenAuge - Lokalisation")
+            predictions = models["KnochenAuge"](image)
+            filtered_preds = [p for p in predictions if p['score'] >= conf_threshold]
+            
+            if filtered_preds:
+                result_image = image.copy()
+                result_image = draw_boxes(result_image, filtered_preds)
+                st.image(result_image, use_container_width=True)
+            
+            # Autres modèles
+            st.markdown("#### 🎯 KI-Analyse")
+            col_left, col_right = st.columns(2)
+            
+            with col_left:
+                st.markdown("**🛡️ Der KnochenWächter**")
+                predictions = models["KnochenWächter"](image)
+                for pred in predictions:
+                    if pred['score'] >= conf_threshold:
+                        score_color = "#22c55e" if pred['score'] > 0.7 else "#eab308"
+                        st.markdown(f"""
+                            <div class='result-box'>
+                                <span style='color: {score_color}; font-weight: 500;'>
+                                    {pred['score']:.1%}
+                                </span> - {translate_label(pred['label'])}
+                            </div>
+                        """, unsafe_allow_html=True)
+            
+            with col_right:
+                st.markdown("**🎓 Der RöntgenMeister**")
+                predictions = models["RöntgenMeister"](image)
+                for pred in predictions:
+                    if pred['score'] >= conf_threshold:
+                        score_color = "#22c55e" if pred['score'] > 0.7 else "#eab308"
+                        st.markdown(f"""
+                            <div class='result-box'>
+                                <span style='color: {score_color}; font-weight: 500;'>
+                                    {pred['score']:.1%}
+                                </span> - {translate_label(pred['label'])}
+                            </div>
+                        """, unsafe_allow_html=True)
+        else:
+            st.info("Bitte laden Sie ein Röntgenbild hoch (JPEG, PNG)")
+
+    # Script pour la synchronisation du thème
+    st.markdown("""
+        <script>
+            function updateTheme(isDark) {
+                document.documentElement.setAttribute('data-theme', isDark ? 'dark' : 'light');
+            }
+            
+            window.addEventListener('message', function(e) {
+                if (e.data.type === 'theme-change') {
+                    updateTheme(e.data.theme === 'dark');
+                }
+            });
+            
+            updateTheme(window.matchMedia('(prefers-color-scheme: dark)').matches);
+        </script>
+    """, unsafe_allow_html=True)
 
-<?php include 'includes/footer.php'; ?>
+if __name__ == "__main__":
+    main()