Update app.py

app.py

@@ -28,6 +28,70 @@ class_labels = [
     'Tomate: Healthy'
 ]
 
+# Treatment dictionary mapping disease classes to treatment options
+treatment_dict = {
+    'Piment: Bacterial_spot': {
+        'treatment': 'Apply Copper Fungicide',
+        'medicines': ['Fungicide A', 'Fungicide B']
+    },
+    'Piment: healthy': {
+        'treatment': 'No treatment required',
+        'medicines': []
+    },
+    'Pomme de terre: Early_blight': {
+        'treatment': 'Use Neem Oil',
+        'medicines': ['Neem Oil', 'Fungicide C']
+    },
+    'Pomme de terre: Late_blight': {
+        'treatment': 'Apply Systemic Fungicide',
+        'medicines': ['Fungicide D']
+    },
+    'Pomme de terre: Healthy': {
+        'treatment': 'No treatment required',
+        'medicines': []
+    },
+    'Tomate: Bacterial Spot': {
+        'treatment': 'Remove infected leaves and apply bactericide',
+        'medicines': ['Bactericide A']
+    },
+    'Tomate: Early Blight': {
+        'treatment': 'Apply preventative fungicides',
+        'medicines': ['Fungicide E']
+    },
+    'Tomate: Late Blight': {
+        'treatment': 'Use fungicides with metalaxyl',
+        'medicines': ['Fungicide F']
+    },
+    'Tomate: Leaf mold': {
+        'treatment': 'Improve air circulation',
+        'medicines': ['Fungicide G']
+    },
+    'Tomate: Septoria leaf spot': {
+        'treatment': 'Remove infected leaves and spray with fungicide',
+        'medicines': ['Fungicide H']
+    },
+    'Tomate: Spider mites': {
+        'treatment': 'Use miticides or insecticidal soap',
+        'medicines': ['Miticide A']
+    },
+    'Tomate: Spot': {
+        'treatment': 'Check for pest issues and apply appropriate treatment',
+        'medicines': []
+    },
+    'Tomate: Yellow Leaf Curl': {
+        'treatment': 'Remove infected plants',
+        'medicines': []
+    },
+    'Tomate: Virus Mosaïque': {
+        'treatment': 'Remove infected plants',
+        'medicines': []
+    },
+    'Tomate: Healthy': {
+        'treatment': 'No treatment required',
+        'medicines': []
+    }
+}
+
 def preprocess_image(image, image_size=(224, 224)):
     # Convert image to grayscale
     image = np.array(image.convert('L'))
@@ -66,4 +130,13 @@ if uploaded_file is not None:
 
     # Show predicted class
     predicted_class = class_labels[np.argmax(probabilities)]
-    st.write(f"Classe prédite: {predicted_class}")
+    st.write(f"Classe prédite: {predicted_class}")
+
+    # Display treatment information
+    if predicted_class in treatment_dict:
+        treatment_info = treatment_dict[predicted_class]
+        st.write("Traitement recommandé:", treatment_info['treatment'])
+        if treatment_info['medicines']:
+            st.write("Médicaments recommandés:", ', '.join(treatment_info['medicines']))
+        else:
+            st.write("Aucun médicament requis.")