Update app.py

app.py

@@ -5,18 +5,63 @@ import numpy as np
 
 # Load the model and unique brand values
 model = joblib.load('model.joblib')
-unique_values = joblib.load('unique_values.joblib')
-brand_values = unique_values['Brand']
+college_values = joblib.load('unique_values.joblib')
+conf_values = joblib.load('conf_values.joblib')
 
 # Define the prediction function
-def predict(brand, screen_size, resolution_width, resolution_height):
+def predict(college,conf,year_drafted,qb_num_picked,rd_picked,num_picked,coach_tenure,height,weight,drafted_team_winpr,drafted_team_ppg_rk,conf_str,p_cmp,p_att,cmp_pct,p_yds,p_ypa,p_adj_ypa,ints,rate,r_att,r_yds,r_avg,r_tds):
     # Convert inputs to appropriate types
-    screen_size = float(screen_size)
-    resolution_width = int(resolution_width)
-    resolution_height = int(resolution_height)
+    year_drafted = int(year_drafted) 
+    qb_num_picked = int(qb_num_picked)
+    rd_picked = int(rd_picked)
+    coach_tenure = int(coach_tenure)
+    weight = int(weight)
+    height = int(height)
+    drafted_team_winpr = float(drafted_team_winpr)
+    drafted_team_ppg_rk = int(drafted_team_ppg_rk)
+    conf_str = float(conf_str)
+    p_cmp = int(p_cmp)
+    p_att = int(p_att)
+    cmp_pct = float(cmp_pct)
+    p_yds = int(p_yds)
+    p_ypa = float(p_ypa)
+    p_adj_ypa = float(p_adj_ypa)
+    p_td = int(p_td)
+    ints = int(ints)
+    rate = float(rate)
+    r_att = int(r_att)
+    r_yds = int(r_yds)
+    r_avg = float(r_avg)
+    r_tds = int(r_tds)
     
     # Prepare the input array for prediction
-    input_data = pd.DataFrame({'Brand' : brand,'screen size': screen_size, "resolution width": resolution_width,'resolution height': resolution_height})
+    input_data = pd.DataFrame({
+        'college': college,
+        'conf': conf,
+        'year_drafted': year_drafted,
+        'qb_num_picked': qb_num_picked,
+        'rd_picked': rd_picked,
+        'num_picked': num_picked,
+        'coach_tenure': coach_tenure,
+        'height': height,
+        'weight': weight,
+        'drafted_team_winpr': drafted_team_winpr,
+        'drafted_team_ppg_rk': drafted_team_ppg_rk,
+        'conf_str': conf_str,
+        'p_cmp': p_cmp,
+        'p_att': p_att,
+        'cmp_pct': cmp_pct,
+        'p_yds': p_yd],
+        'p_ypa': p_ypa,
+        'p_adj_ypa': p_adj_ypa,
+        'p_td': p_td,
+        'ints': ints,
+        'rate': rate,
+        'r_att': r_att,
+        'r_yds': r_yds,
+        'r_avg': r_avg,
+        'r_tds': r_tds
+    })
     
     # Perform the prediction
     prediction = model.predict(input_data)
@@ -27,14 +72,35 @@ def predict(brand, screen_size, resolution_width, resolution_height):
 interface = gr.Interface(
     fn=predict,
     inputs=[
-        gr.Dropdown(choices=brand_values, label="Brand"),
-        gr.Textbox(label="Screen Size"),
-        gr.Textbox(label="Resolution (Width)"),
-        gr.Textbox(label="Resolution (Height)")
+        gr.Dropdown(choices=college_values, label="College"),
+        gr.Dropdown(choices=conf_values, label="Conference"),
+        gr.Textbox(label="Year Drafted"),
+        gr.Textbox(label="QB Number Picked"),
+        gr.Textbox(label="Round Picked"),
+        gr.Textbox(label="Number Picked"),
+        gr.Textbox(label="Coach Tenure"),
+        gr.Textbox(label="Height (inches)"),
+        gr.Textbox(label="Weight (pounds)"),
+        gr.Textbox(label="Drafted Team Win %"),
+        gr.Textbox(label="Drafted Team PPG Rank"),
+        gr.Textbox(label="Conference Strength"),
+        gr.Textbox(label="Pass Completions"),
+        gr.Textbox(label="Pass Attempts"),
+        gr.Textbox(label="Completion Percentage"),
+        gr.Textbox(label="Pass Yards"),
+        gr.Textbox(label="Pass Yards per Attempt"),
+        gr.Textbox(label="Adjusted Yards per Attempt"),
+        gr.Textbox(label="Pass Touchdowns"),
+        gr.Textbox(label="Interceptions"),
+        gr.Textbox(label="Passer Rating"),
+        gr.Textbox(label="Rush Attempts"),
+        gr.Textbox(label="Rush Yards"),
+        gr.Textbox(label="Rush Average"),
+        gr.Textbox(label="Rush Touchdowns")
     ],
     outputs="text",
-    title="Monitor Predictor",
-    description="Enter the brand, screen size, and resolution to predict the target value."
+    title="passing to touchdown Predictor",
+    description="Enter all you see."
 )
 
 # Launch the app