Update app.py

app.py

@@ -1,11 +1,12 @@
 import gradio as gr
 import numpy as np
 from PIL import Image
-import joblib
+from tensorflow.keras.models import load_model
 
 # Load the trained model
-model = joblib.load("model.pkl")
+model = load_model("model.h5")
 
+# Define class labels 
 class_names = ["Monkeypox", "Not Monkeypox"]
 
 def predict(img):
@@ -14,15 +15,11 @@ def predict(img):
     img = np.array(img) / 255.0  # normalize
     img = np.expand_dims(img, axis=0)
 
+    # Predict
     preds = model.predict(img)
 
-    probs = preds[0]
-    result = {class_names[i]: float(probs[i]) for i in range(len(class_names))}
-
-    pred_idx = np.argmax(probs)
-    pred_label = class_names[pred_idx]
-
-    return result
+    # Convert predictions to dictionary
+    return {class_names[i]: float(preds[0][i]) for i in range(len(class_names))}
 
 demo = gr.Interface(
     fn=predict,