functional v1

Predictor.py

@@ -253,8 +253,8 @@ def predict_file(input_file):
 
     print('====Predict====')
     pred = eval_step(dataloader, model)
-
-    print(pred)
+    return pred
+    # print(pred)
     # print('====Save Results====')         
     # if not os.path.exists(args.outdir): os.makedirs(args.outdir)
     # pred.to_csv(f'{args.outdir}/{args.outfilename}_prediction_results.csv', index = False)
@@ -272,4 +272,5 @@ def predict_raw(raw_input):
     print('====Predict====')
     pred = eval_step(dataloader, model)
 
-    print(pred)
+    # print(pred)
+    return pred

app.py

@@ -1,22 +1,26 @@
 import streamlit as st
-from Bio import SeqIO
+# from Bio import SeqIO
 from Predictor import predict_file, predict_raw
+from io import StringIO
 
 st.title("5' UTR prediction")
 
 st.subheader("Input sequence")
 #x = st.slider('Select a value')
 # seq = ""
-seq = st.text_input("Input your sequence here", value="")
+seq = st.text_area("Input your sequence here", value="")
 st.subheader("Upload sequence file")
 uploaded = st.file_uploader("Sequence file in FASTA format")
 # if uploaded:
+#     st.write(StringIO(uploaded.getvalue().decode("utf-8")))
+    # seq = uploaded.read()
+    # print(seq)
     # predict_file(uploaded)
     # seq = SeqIO.read(uploaded, "fasta").seq
-st.subheader("Prediction result:")
+# st.subheader("Prediction result:")
 if st.button("Predict"):
+    st.write("Prediction result:")
     if uploaded:
-        predict_file(uploaded)
+        st.write(predict_raw(uploaded.getvalue().decode()))
     else:
-        predict_raw(seq)
-    # st.write("Sequence length = ", len(seq))
+        st.write(predict_raw(seq))