Update main.py

main.py

@@ -120,34 +120,16 @@ def model_prediction(compound_feature, enz_feature, model):
     return prediction_vals[0][0]
 
 
-# loaded_model = load_modelfile('./../CNN_results/model_final.model')
-
-# KEGG_compound_read = pd.read_csv('./../CNN_data/Final_test/kegg_compound.csv', index_col = 'Compound_ID')
-# kegg_df = KEGG_compound_read.reset_index()
-
-
 def main():
 	graph = tf.compat.v1.get_default_graph()
-	ld_model = tf.keras.models.load_model('./../CNN_results_split_final/Final_model.model')
+	ld_model = tf.keras.models.load_model('./CNN_results_split_final/Final_model.model')
 
-	KEGG_compound_read = pd.read_csv('./../CNN_data/Final_test/kegg_compound.csv', index_col = 'Compound_ID')
+	KEGG_compound_read = pd.read_csv('./CNN_data/Final_test/kegg_compound.csv', index_col = 'Compound_ID')
 	kegg_df = KEGG_compound_read.reset_index()
 	
 	
-    # def img_to_bytes(img_path):
-    #     img_bytes = Path(img_path).read_bytes()
-    #     encoded = base64.b64encode(img_bytes).decode()
-    #     return encoded
-    # # st.title('dGPredictor')
-
-    # header_html = "<img src='../figures/header.png'>"
-
-    # st.markdown(
-    #     header_html, unsafe_allow_html=True,
-    # )
-
 
-	st.image('./header.png', use_column_width=True)
+	st.image('./Streamlit/header.png', use_column_width=True)
 
 	st.subheader('Enzyme-Substrate Activity Predictor ')