Update app.py

app.py

@@ -4,18 +4,19 @@ import pandas as pd
 import pickle
 import xgboost as xgb
 
-def predict(team, inning, venue, hits, errors, leftonbase, runs):
+def predict(team, inning, venue, hits, errors, leftonbase, runs, opp_team, opp_runs):
 
-    data = [team, inning, venue, hits, errors, runs, leftonbase]
-    df = pd.DataFrame([data], columns=["Team_Name", "Inning", "Home/Away", "Hits", "Errors", "Runs", "Leftonbase"])
+    data = [team, inning, venue, hits, errors, runs, leftonbase, opp_team, opp_runs]
+    df = pd.DataFrame([data], columns=["Team_Name", "Inning", "Home/Away", "Hits", "Errors", "Runs", "Leftonbase", "Opposition_Team", "Opp_Runs"])
 
     xgb_model = xgb.XGBRegressor()
-    xgb_model.load_model('xgbr3_model3.json')
+    xgb_model.load_model('xgbr3_model3_exp5.json')
     
     with open('label_encoder_teams3.pkl', 'rb') as f:
         label_encoder = pickle.load(f)
 
-    df['Team_Name'] = label_encoder.fit_transform(df['Team_Name'])
+    df['Team_Name'] = label_encoder.transform(df['Team_Name'])
+    df['Opposition_Team'] = label_encoder.transform(df['Opposition_Team'])
 
     home_away_status = {'Home': 0, 'Away': 1}
     df['Home/Away'] = df['Home/Away'].map(home_away_status)
@@ -77,11 +78,11 @@ with gr.Blocks() as demo:
             inning = gr.Number(None, label="Inning", minimum = 1, maximum = 8, scale=1)
     
     with gr.Row():
-        # with gr.Column():
-        venue = gr.Dropdown(choices = ["Home", "Away"], max_choices = 1, label="Home/Away Status", scale=1)  
+        with gr.Column():
+            venue = gr.Dropdown(choices = ["Home", "Away"], max_choices = 1, label="Home/Away Status", scale=1)  
             
-        # with gr.Column():
-        hits = gr.Number(None, minimum=0, label="Hits - (H)", scale=1)
+        with gr.Column():
+            hits = gr.Number(None, minimum=0, label="Hits - (H)", scale=1)
     
     # summarize_btn = gr.Button(value="Summarize Text", size = 'sm')
 
@@ -92,12 +93,19 @@ with gr.Blocks() as demo:
         
         runs = gr.Number(None, minimum=0, label="Runs - (R)", scale=1)
 
+    with gr.Row():
+        with gr.Column():
+            opp_team = gr.Dropdown(choices = team_names, max_choices = 1, label="Opposition Team", scale=1)  
+            
+        with gr.Column():
+            opp_runs = gr.Number(None, minimum=0, label="Opposition Runs - (R)", scale=1)
+
     with gr.Row():
         predict_btn = gr.Button(value="Predict", size = 'sm')
 
     with gr.Row():
         final_score = gr.Textbox(label="Predicted Score", scale=1)
     # patent_doc.upload(document_to_text, inputs = [patent_doc, slider, select_model], outputs=summary_doc)
-    predict_btn.click(predict, inputs=[team, inning, venue, hits, errors, leftonbase, runs], outputs=final_score)
+    predict_btn.click(predict, inputs=[team, inning, venue, hits, errors, leftonbase, runs, opp_team, opp_runs], outputs=final_score)
 
 demo.launch(inline=False)