Update app.py

app.py

@@ -3,18 +3,18 @@ from transformers import AutoImageProcessor, AutoModelForImageClassification, pi
 from PIL import Image
 import torch
 
-st.set_page_config(page_title="Détection de fractures", layout="wide")
+st.set_page_config(page_title="Détection maladies pulmonaires", layout="wide")
 
 @st.cache_resource
 def load_model():
-    return pipeline("image-classification", model="Heem2/bone-fracture-detection-using-xray")
+    return pipeline("image-classification", model="gianlab/swin-tiny-patch4-window7-224-finetuned-lungs-disease")
 
 def main():
-    st.title("Détection de fractures osseuses")
+    st.title("Détection de maladies pulmonaires")
     
     model = load_model()
     
-    uploaded_file = st.file_uploader("Télécharger une radiographie", type=["jpg", "jpeg", "png"])
+    uploaded_file = st.file_uploader("Télécharger une radiographie thoracique", type=["jpg", "jpeg", "png"])
     
     if uploaded_file:
         image = Image.open(uploaded_file)
@@ -24,7 +24,7 @@ def main():
             with st.spinner("Analyse en cours..."):
                 try:
                     result = model(image)
-                    st.write(f"Résultat: {result[0]['label']}")
+                    st.write(f"Diagnostic: {result[0]['label']}")
                     st.write(f"Confiance: {result[0]['score']:.2%}")
                 except Exception as e:
                     st.error(f"Erreur: {str(e)}")