Update app.py

app.py

@@ -1,6 +1,7 @@
 import numpy as np
 import pandas as pd
 import streamlit as st
+import pickle
 from PIL import Image
 
 st.set_page_config(
@@ -13,6 +14,45 @@ st.set_page_config(
     }
 )
 
+model = pickle.load(open('crop_model.pkl','rb'))
+
+check_crops = {1: 'rice',
+ 2: 'maize',
+ 3: 'jute',
+ 4: 'cotton',
+ 5: 'coconut',
+ 6: 'papaya',
+ 7: 'orange',
+ 8: 'apple',
+ 9: 'muskmelon',
+ 10: 'watermelon',
+ 11: 'grapes',
+ 12: 'mango',
+ 13: 'banana',
+ 14: 'pomegranate',
+ 15: 'lentil',
+ 16: 'blackgram',
+ 17: 'mungbean',
+ 18: 'mothbeans',
+ 19: 'pigeonpeas',
+ 20: 'kidneybeans',
+ 21: 'chickpea',
+ 22: 'coffee'}
+
+def recommend(N, P, K, temperature, humidity, ph, rainfall):
+    features = np.array([[N, P, K, temperature, humidity, ph, rainfall]]).reshape(1,-1)
+    features = ms.transform(features)
+    features = ss.transform(features)
+    prediction = rfc.predict(features)
+    return prediction[0]
+
+def output(N, P, K, temperature, humidity, ph, rainfall):
+    predict = recommend(N, P, K, temperature, humidity, ph, rainfall)
+    if predict in check_crops:
+        crop = check_crops[predict]
+        print("Our crop recommendation is {}".format(crop))
+    else:
+        print("No recommendation")
 
 image = Image.open('./title.jpg')
 st.image(image)
@@ -23,25 +63,30 @@ with st.sidebar:
     st.markdown("<h2 style='text-align: center; color: red;'>Settings Tab</h2>", unsafe_allow_html=True)
 
 
-    st.write("Model Settings:")
+    st.write("Input Settings:")
+
+    #define the N for the model
+    n_value = st.slider('N :', 0.0, 150.0, 20)
+
+    #define the P for the model
+    p_value = st.slider('P :', 0.0, 150.0, 20)
+
+    #define the K for the model
+    k_value = st.slider('K  :', 0.0, 200.0, 40)
 
-    #define the temeperature for the model
-    temperature_value = st.slider('Temperature :', 0.0, 1.0, 0.2)
-    st.session_state['temperature'] = temperature_value
+    #define the temperature for the model
+    temperature = st.slider('Temperature :', 0.0, 50.0, 10.0)
 
-    #define the temeperature for the model
-    token_limit_value = st.slider('Token limit :', 1, 1024, 256)
-    st.session_state['token_limit'] = token_limit_value
+    #define the humidity for the model
+    humidity = st.slider('Humidity  :', 0.0, 100.0, 40)
 
-    #define the temeperature for the model
-    top_k_value = st.slider('Top-K  :', 1,40,40)
-    st.session_state['top_k'] = top_k_value
+    #define the ph for the model
+    ph_value = st.slider('ph  :', 0.0, 10.0, 2.0)
 
-    #define the temeperature for the model
-    top_p_value = st.slider('Top-P :', 0.0, 1.0, 0.8)
-    st.session_state['top_p'] = top_p_value
+    #define the rainfall for the model
+    rainfall = st.slider('Rainfall  :', 10.0, 300.0, 40)
 
-    if st.button("Reset Session"):
-        reset_session()
+    if st.button("Recommend"):
+        output(n_value, p_value, k_value, temperature, humidity, ph_value, rainfall)