Update app.py

app.py

@@ -14,7 +14,7 @@ class CustomLSTM(LSTM):
 # Caching the model loading function to optimize performance
 @st.cache_resource
 def load_captcha_model():
-    model_path = "captcha_ocr_model.h5"  # Ganti dengan path model CAPTCHA yang sebenarnya
+    model_path = "captcha_ocr_model.h5"  # Update with the actual CAPTCHA model path
     return tf.keras.models.load_model(model_path, custom_objects={'CustomLSTM': CustomLSTM})
 
 # Load the model
@@ -24,10 +24,10 @@ model = load_captcha_model()
 def prepare_captcha_image(img):
     try:
         # Resize image to the input shape required by the CAPTCHA model
-        img = img.resize((200, 50))  # Sesuaikan ukuran sesuai model yang dilatih
-        img_array = np.array(img.convert('L'))  # Konversi ke grayscale jika perlu
-        img_array = img_array / 255.0  # Normalisasi gambar
-        img_array = np.expand_dims(img_array, axis=0)  # Tambahkan dimensi batch
+        img = img.resize((200, 50))  # Adjust size according to the trained model
+        img_array = np.array(img.convert('L'))  # Convert to grayscale if necessary
+        img_array = img_array / 255.0  # Normalize image
+        img_array = np.expand_dims(img_array, axis=0)  # Add batch dimension
 
         # Predict the CAPTCHA characters
         predictions = model.predict(img_array)