Update app.py

app.py

@@ -2,6 +2,8 @@ from sklearn.preprocessing import LabelEncoder
 import pandas as pd
 import pickle
 import gradio as gr
+import gradio as gr
+
 svc=pickle.load(open('svc.pickle','rb'))
 def predict_class(cap_shape, cap_surface, cap_color, bruises, odor, gill_attachment, 
                   gill_spacing, gill_size, gill_color, stalk_shape, stalk_root, 
@@ -13,19 +15,49 @@ def predict_class(cap_shape, cap_surface, cap_color, bruises, odor, gill_attachm
                   stalk_surface_above_ring, stalk_surface_below_ring, stalk_color_above_ring, 
                   stalk_color_below_ring, veil_color, ring_number, ring_type, spore_print_color, 
                   population, habitat]
-    encoder=LabelEncoder()
-    real_df=pd.read_csv('mushrooms.csv')
-    real_df.drop(['class','veil-type'],axis=1,inplace=True)
-    encoded_value=[]
+
     features = [ 'cap-shape', 'cap-surface', 'cap-color', 'bruises', 'odor',
            'gill-attachment', 'gill-spacing', 'gill-size', 'gill-color',
            'stalk-shape', 'stalk-root', 'stalk-surface-above-ring',
            'stalk-surface-below-ring', 'stalk-color-above-ring',
            'stalk-color-below-ring', 'veil-color', 'ring-number',
            'ring-type', 'spore-print-color', 'population', 'habitat']
-    randomly_selected_values = ['s', 'y', 'g', 'f', 'c', 'a', 'w', 'n', 'b', 't', 'e', 's', 'k', 'o', 'y', 'w', 'o', 'f', 'r', 'y', 'p']
-    random=pd.DataFrame([input_data],columns=features)
+    mushroom_data = {
+    'cap-shape': {'bell': 'b', 'conical': 'c', 'convex': 'x', 'flat': 'f', 'knobbed': 'k', 'sunken': 's'},
+    'cap-surface': {'fibrous': 'f', 'grooves': 'g', 'scaly': 'y', 'smooth': 's'},
+    'cap-color': {'brown': 'n', 'buff': 'b', 'cinnamon': 'c', 'gray': 'g', 'green': 'r', 'pink': 'p', 'purple': 'u', 'red': 'e', 'white': 'w', 'yellow': 'y'},
+    'bruises': {'bruises': 't', 'no': 'f'},
+    'odor': {'almond': 'a', 'anise': 'l', 'creosote': 'c', 'fishy': 'y', 'foul': 'f', 'musty': 'm', 'none': 'n', 'pungent': 'p', 'spicy': 's'},
+    'gill-attachment': {'attached': 'a', 'descending': 'd', 'free': 'f', 'notched': 'n'},
+    'gill-spacing': {'close': 'c', 'crowded': 'w', 'distant': 'd'},
+    'gill-size': {'broad': 'b', 'narrow': 'n'},
+    'gill-color': {'black': 'k', 'brown': 'n', 'buff': 'b', 'chocolate': 'h', 'gray': 'g', 'green': 'r', 'orange': 'o', 'pink': 'p', 'purple': 'u', 'red': 'e', 'white': 'w', 'yellow': 'y'},
+    'stalk-shape': {'enlarging': 'e', 'tapering': 't'},
+    'stalk-root': {'bulbous': 'b', 'club': 'c', 'cup': 'u', 'equal': 'e', 'rhizomorphs': 'z', 'rooted': 'r', 'missing': '?'},
+    'stalk-surface-above-ring': {'fibrous': 'f', 'scaly': 'y', 'silky': 'k', 'smooth': 's'},
+    'stalk-surface-below-ring': {'fibrous': 'f', 'scaly': 'y', 'silky': 'k', 'smooth': 's'},
+    'stalk-color-above-ring': {'brown': 'n', 'buff': 'b', 'cinnamon': 'c', 'gray': 'g', 'orange': 'o', 'pink': 'p', 'red': 'e', 'white': 'w', 'yellow': 'y'},
+    'stalk-color-below-ring': {'brown': 'n', 'buff': 'b', 'cinnamon': 'c', 'gray': 'g', 'orange': 'o', 'pink': 'p', 'red': 'e', 'white': 'w', 'yellow': 'y'},
+    'veil-type': {'partial': 'p', 'universal': 'u'},
+    'veil-color': {'brown': 'n', 'orange': 'o', 'white': 'w', 'yellow': 'y'},
+    'ring-number': {'none': 'n', 'one': 'o', 'two': 't'},
+    'ring-type': {'cobwebby': 'c', 'evanescent': 'e', 'flaring': 'f', 'large': 'l', 'none': 'n', 'pendant': 'p', 'sheathing': 's', 'zone': 'z'},
+    'spore-print-color': {'black': 'k', 'brown': 'n', 'buff': 'b', 'chocolate': 'h', 'green': 'r', 'orange': 'o', 'purple': 'u', 'white': 'w', 'yellow': 'y'},
+    'population': {'abundant': 'a', 'clustered': 'c', 'numerous': 'n', 'scattered': 's', 'several': 'v', 'solitary': 'y'},
+    'habitat': {'grasses': 'g', 'leaves': 'l', 'meadows': 'm', 'paths': 'p', 'urban': 'u', 'waste': 'w', 'woods': 'd'}
+    }
+
+    encoder=LabelEncoder()
+    real_df=pd.read_csv('mushrooms.csv')
+    real_df.drop(['class','veil-type'],axis=1,inplace=True)
+    encoded_value=[]
+    valueforprediction=[]
+    for i in range(21):
+        valueforprediction.append(mushroom_data[features[i]][input_data[i]])
+
+    random=pd.DataFrame([valueforprediction],columns=features)
     for i in real_df.columns:
+        print(i,real_df[i].unique())
         encoder.fit_transform(real_df[i])
         encoded_value.append(encoder.transform(random[i])[0])
     
@@ -38,35 +70,29 @@ def predict_class(cap_shape, cap_surface, cap_color, bruises, odor, gill_attachm
 
 
 
-
-import gradio as gr
-input_features = {
-    'cap-shape': ['x', 'b', 's', 'f', 'k', 'c'],
-    'cap-surface': ['s', 'y', 'f', 'g'],
-    'cap-color': ['n', 'y', 'w', 'g', 'e', 'p', 'b', 'u', 'c', 'r'],
-    'bruises': ['t', 'f'],
-    'odor': ['p', 'a', 'l', 'n', 'f', 'c', 'y', 's', 'm'],
-    'gill-attachment': ['f', 'a'],
-    'gill-spacing': ['c', 'w'],
-    'gill-size': ['n', 'b'],
-    'gill-color': ['k', 'n', 'g', 'p', 'w', 'h', 'u', 'e', 'b', 'r', 'y', 'o'],
-    'stalk-shape': ['e', 't'],
-    'stalk-root': ['e', 'c', 'b', 'r', '?'],
-    'stalk-surface-above-ring': ['s', 'f', 'k', 'y'],
-    'stalk-surface-below-ring': ['s', 'f', 'y', 'k'],
-    'stalk-color-above-ring': ['w', 'g', 'p', 'n', 'b', 'e', 'o', 'c', 'y'],
-    'stalk-color-below-ring': ['w', 'p', 'g', 'b', 'n', 'e', 'y', 'o', 'c'],
-    'veil-color': ['w', 'n', 'o', 'y'],
-    'ring-number': ['o', 't', 'n'],
-    'ring-type': ['p', 'e', 'l', 'f', 'n'],
-    'spore-print-color': ['k', 'n', 'u', 'h', 'w', 'r', 'o', 'y', 'b'],
-    'population': ['s', 'n', 'a', 'v', 'y', 'c'],
-    'habitat': ['u', 'g', 'm', 'd', 'p', 'w', 'l']
-}
+input_features = {'cap-shape': ['bell', 'conical', 'convex', 'flat', 'knobbed', 'sunken'], 
+                  'cap-surface': ['fibrous', 'grooves', 'scaly', 'smooth'], 
+                  'cap-color': ['brown', 'buff', 'cinnamon', 'gray', 'green', 'pink', 'purple', 'red', 'white', 'yellow'], 
+                  'bruises': ['bruises', 'no'], 
+                  'odor': ['almond', 'anise', 'creosote', 'fishy', 'foul', 'musty', 'none', 'pungent', 'spicy'], 
+                  'gill-attachment': ['attached', 'free'], 
+                  'gill-spacing': ['close', 'crowded'],         
+                  'gill-size': ['broad', 'narrow'],                   
+                  'gill-color': ['black', 'brown', 'buff', 'chocolate', 'gray', 'green', 'orange', 'pink', 'purple', 'red', 'white', 'yellow'], 
+                  'stalk-shape': ['enlarging', 'tapering'], 
+                  'stalk-root': ['bulbous', 'club', 'equal', 'rooted', 'missing'], 
+                  'stalk-surface-above-ring': ['fibrous', 'scaly', 'silky', 'smooth'], 
+                  'stalk-surface-below-ring': ['fibrous', 'scaly', 'silky', 'smooth'], 
+                  'stalk-color-above-ring': ['brown', 'buff', 'cinnamon', 'gray', 'orange', 'pink', 'red', 'white', 'yellow'], 
+                  'stalk-color-below-ring': ['brown', 'buff', 'cinnamon', 'gray', 'orange', 'pink', 'red', 'white', 'yellow'], 
+                  'veil-color': ['brown', 'orange', 'white', 'yellow'], 
+                  'ring-number': ['none', 'one', 'two'], 
+                  'ring-type': [ 'evanescent', 'flaring', 'large', 'none', 'pendant'], 
+                  'spore-print-color': ['black', 'brown', 'buff', 'chocolate', 'green', 'orange', 'purple', 'white', 'yellow'], 
+                  'population': ['abundant', 'clustered', 'numerous', 'scattered', 'several', 'solitary'], 
+                  'habitat': ['grasses', 'leaves', 'meadows', 'paths', 'urban', 'waste', 'woods']}
 
 
-# Convert input features dictionary to a list of dictionaries
-print(len(input_features))
 # Define the output classes
 output_classes = ['p', 'e']