Update app.py

app.py

@@ -44,6 +44,30 @@ def load_image_model():
 
 
 
+    
+
+# @st.cache_resource()
+# def load_encoder_model():
+#     encoder=tf.keras.models.load_model('./encoder_model.h5')
+#     return encoder
+
+
+@st.cache_resource()
+def feature_extractor():
+    FEATURE_EXTRACTOR=tf.keras.models.load_model('./feature_extractor.h5')
+    return FEATURE_EXTRACTOR
+
+
+FEATURE_EXTRACTOR = feature_extractor()
+FEATURE_EXTRACTOR.trainable = False
+image_input = Input(shape=(IMG_HEIGHT, IMG_WIDTH, IMG_CHANNELS))
+image_features = FEATURE_EXTRACTOR(image_input)
+x = Reshape((FEATURES_SHAPE[0] * FEATURES_SHAPE[1], FEATURES_SHAPE[2]))(image_features)
+encoder_output = Dense(ATTENTION_DIM, activation="relu")(x)
+encoder = tf.keras.Model(inputs=image_input, outputs=encoder_output)
+
+
+#****
 word_input = Input(shape=(MAX_CAPTION_LEN), name="words")
 embed_x = Embedding(VOCAB_SIZE, ATTENTION_DIM)(word_input)
 
@@ -89,28 +113,10 @@ decoder_pred_model = tf.keras.Model(
     inputs=[word_input, gru_state_input, encoder_output],
     outputs=[decoder_output, gru_state],
 )
+# ****
 
-    
-
-# @st.cache_resource()
-# def load_encoder_model():
-#     encoder=tf.keras.models.load_model('./encoder_model.h5')
-#     return encoder
 
 
-@st.cache_resource()
-def feature_extractor():
-    FEATURE_EXTRACTOR=tf.keras.models.load_model('./feature_extractor.h5')
-    return FEATURE_EXTRACTOR
-
-
-FEATURE_EXTRACTOR = feature_extractor()
-FEATURE_EXTRACTOR.trainable = False
-image_input = Input(shape=(IMG_HEIGHT, IMG_WIDTH, IMG_CHANNELS))
-image_features = FEATURE_EXTRACTOR(image_input)
-x = Reshape((FEATURES_SHAPE[0] * FEATURES_SHAPE[1], FEATURES_SHAPE[2]))(image_features)
-encoder_output = Dense(ATTENTION_DIM, activation="relu")(x)
-encoder = tf.keras.Model(inputs=image_input, outputs=encoder_output)
     
 st.title(":blue[Nishant Guvvada's] :red[AI Journey]  Image Caption Generation")
 image = Image.open('./title.jpg')