Update app.py

app.py

@@ -170,14 +170,15 @@ def main():
     
     with st.container():
         st.write("### 📤 Röntgenbild hochladen")
-        uploaded_file = st.file_uploader("", type=['png', 'jpg', 'jpeg'])
+        uploaded_file = st.file_uploader("Bild auswählen", type=['png', 'jpg', 'jpeg'], label_visibility="collapsed")
         
         col1, col2 = st.columns([2, 1])
         with col1:
             conf_threshold = st.slider(
                 "Konfidenzschwelle",
                 min_value=0.0, max_value=1.0,
-                value=0.60, step=0.05
+                value=0.60, step=0.05,
+                label_visibility="visible"
             )
         with col2:
             analyze_button = st.button("Analysieren")
@@ -196,13 +197,18 @@ def main():
                 # KnochenWächter
                 predictions_watcher = models["KnochenWächter"](image)
                 has_fracture = False
+                max_fracture_score = 0
+
+                st.write("#### 🛡️ KnochenWächter")
                 for pred in predictions_watcher:
                     if pred['score'] >= conf_threshold:
                         confidence_color = '#0066cc' if pred['score'] > 0.7 else '#ffa500'
-                        if 'fracture' in pred['label'].lower():
+                        label_lower = pred['label'].lower()
+                        if 'fracture' in label_lower:
                             has_fracture = True
+                            max_fracture_score = max(max_fracture_score, pred['score'])
                         st.markdown(f"""
-                            <div class="result-box">
+                            <div class="result-box" style="color: #1a1a1a;">
                                 <span style="color: {confidence_color}; font-weight: 500;">
                                     {pred['score']:.1%}
                                 </span> - {translate_label(pred['label'])}
@@ -210,40 +216,42 @@ def main():
                         """, unsafe_allow_html=True)
                 
                 # RöntgenMeister
+                st.write("#### 🎓 RöntgenMeister")
                 predictions_master = models["RöntgenMeister"](image)
                 for pred in predictions_master:
                     if pred['score'] >= conf_threshold:
                         confidence_color = '#0066cc' if pred['score'] > 0.7 else '#ffa500'
                         st.markdown(f"""
-                            <div class="result-box">
+                            <div class="result-box" style="color: #1a1a1a;">
                                 <span style="color: {confidence_color}; font-weight: 500;">
                                     {pred['score']:.1%}
                                 </span> - {translate_label(pred['label'])}
                             </div>
                         """, unsafe_allow_html=True)
                 
-                # Calculate and display fracture probability
-                fracture_prob = max((p['score'] for p in predictions_watcher 
-                                   if 'fracture' in p['label'].lower()), default=0)
-                no_fracture_prob = 1 - fracture_prob
-                
-                st.write("#### 📊 Wahrscheinlichkeit")
-                st.markdown(f"""
-                    <div class="result-box">
-                        Knochenbruch: <strong>{fracture_prob:.1%}</strong><br>
-                        Kein Knochenbruch: <strong>{no_fracture_prob:.1%}</strong>
-                    </div>
-                """, unsafe_allow_html=True)
+                # Probabilités actualisées
+                if max_fracture_score > 0:
+                    st.write("#### 📊 Wahrscheinlichkeit")
+                    no_fracture_prob = 1 - max_fracture_score
+                    st.markdown(f"""
+                        <div class="result-box" style="color: #1a1a1a;">
+                            Knochenbruch: <strong style="color: #0066cc">{max_fracture_score:.1%}</strong><br>
+                            Kein Knochenbruch: <strong style="color: #ffa500">{no_fracture_prob:.1%}</strong>
+                        </div>
+                    """, unsafe_allow_html=True)
             
             with col2:
-                st.write("#### 🎯 Visualisierung")
+                # Vérification et localisation des fractures
                 predictions = models["KnochenAuge"](image)
-                filtered_preds = [p for p in predictions if p['score'] >= conf_threshold]
+                filtered_preds = [p for p in predictions if p['score'] >= conf_threshold 
+                                and 'fracture' in p['label'].lower()]
                 
-                if filtered_preds and has_fracture:
+                if filtered_preds:
+                    st.write("#### 🎯 Fraktur Lokalisation")
                     result_image = draw_boxes(image, filtered_preds)
                     st.image(result_image, use_container_width=True)
                 else:
+                    st.write("#### 🖼️ Röntgenbild")
                     st.image(image, use_container_width=True)
 
 if __name__ == "__main__":