add models

data/models/cereals_knn.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b4ce13b778031582a72b95d8ffc783e2754d08c639a73458a56f13db5a9bb0cf
+size 14461645

data/models/fresh_veg_et.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3c91439300ee6cc546fc25e588aa18d1fb0a23eeb60638fec4e7526cca539db6
+size 103676865

data/models/fruits&nuts_knn.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3ed6569eb296b5bd782a6dfc9c57d1be699c5e1e5427dbf341b67d2594c35c3e
+size 14346669

data/models/grapes_olives_et.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:816dfc0a50255dfaaa757b266b096ef0b640903e48fcc068ce91820252557d54
+size 15175359

data/models/industrial_crop_et.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6884fafeedaebfa2d3296fcccdb069aeb11e6c7cc2d79a6d270b8c2ba5346e97
+size 32917055

logs.log

@@ -0,0 +1,10 @@
+2022-11-08 15:59:38,643:WARNING:
+'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install.
+2022-11-08 15:59:38,643:WARNING:
+'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install.
+2022-11-08 15:59:38,643:WARNING:
+'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install.
+2022-11-08 15:59:38,644:WARNING:
+'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install.
+2022-11-08 15:59:39,757:WARNING:
+'prophet' is a soft dependency and not included in the pycaret installation. Please run: `pip install prophet` to install.

pages/demo.py

@@ -1,15 +1,344 @@
+
+from pycaret.regression import load_model, predict_model
 import streamlit as st
 import pandas as pd
-import geopandas as gpd
-from millify import millify
-import folium
+import numpy as np
+
 from PIL import Image
-from streamlit_folium import st_folium
+#image = Image.open('omdena_logo.png')
+#st.set_page_config(page_title='omdena-milan', page_icon=image)
+import pycaret
+
+    
+model1 = load_model('data/models/cereals_knn')
+model2= load_model('data/models/fruits&nuts_knn')
+model3 = load_model('data/models/grapes_olives_et')
+model4 = load_model('data/models/fresh_veg_et')
+model5 = load_model('data/models/industrial_crop_et')
+
+
+def predict1(model1, input_df1):
+    predictions_df1 = predict_model(estimator=model1, data=input_df1)
+    predictions1 = predictions_df1['prediction_label'][0]
+    return predictions1
+
+def predict2(model2, input_df2):
+    predictions_df2= predict_model(estimator=model2, data=input_df2)
+    predictions2 = predictions_df2['prediction_label'][0]
+    return predictions2
+
+def predict3(model3, input_df3):
+    predictions_df3 = predict_model(estimator=model3, data=input_df3)
+    predictions3 = predictions_df3['prediction_label'][0]
+    return predictions3
+
+def predict4(model4, input_df4):
+    predictions_df4= predict_model(estimator=model4, data=input_df4)
+    predictions4 = predictions_df4['prediction_label'][0]
+    return predictions4
+
+def predict5(model5, input_df5):
+    predictions_df5= predict_model(estimator=model5, data=input_df5)
+    predictions5 = predictions_df5['prediction_label'][0]
+    return predictions5
+
+
+def run():
+    
+    
+  
+    add_selectbox = st.sidebar.selectbox(
+    "Please choose your crop",
+    ("Cereal & Legumes", "Fruits & Nuts", "Grapes & Olives", "Fresh Vegetables","Industrial crops", ))
+    
+    st.sidebar.info('Omdena-Milan Agrifood')
+    st.sidebar.success('https://omdena.com/local-chapters/milan-italy-chapter/')
+    
+    st.title("Crop Prediction")
+        
+    if add_selectbox == 'Cereal & Legumes':
+
+        temperature_max = st.number_input('Temperature max (°C)', min_value= 20, max_value= 50)
+        
+        temperature_min = st.number_input('Temperature min (°C)', min_value= -5, max_value= 20)
+        
+        relative_humidity = st.number_input('Relative humidity (%)', min_value=0, max_value=100)
+       
+        root_moisture = st.number_input('Root moisture', max_value=1)
+        
+        total_area_ha = st.number_input('Total area(ha)', min_value=0, max_value=6150)
+        
+        fertilizer_tonnes = st.number_input('Fertilizer (tonnes)', min_value=0, max_value=3405)
+        
+        fertilizer = st.selectbox('Type of fertilizer', ['calcium cyanamide', 'nitrogen-potassium', 'peaty-amend',
+                                                 'organic-nitrogen', 'organic', 'ammonium sulphate',
+                                                 'nitrogen-phosphorous', 'phosphorus-potassium', 'urea'])
+        
+        crop = st.selectbox('Type of crop', ['barley', 'bro-bean', 'chick-peas', 'dry-k-bean', 'd-wheat',
+                                     'early potatoes', 'lentil', 'oats', 'potatoes', 'grain pea',
+                                     'oats mix', 'spring barley', 'winter barley', 'c-wheat', 'maize',
+                                     'protein pea', 'rice', 'sorghum', 'sugar beet', 'other cereals',
+                                     'rye', 'titicale', 'c-spr-wheat&spelt', 'c-wint-wheat&spelt',
+                                     'sweet potatoes', 'sweet lupin', 'rye mix', 'cereal mix',
+                                     'wint-cereal-mix'])
+                                     
+        city = st.selectbox('City', ['Agrigento', 'Alessandria', 'Ancona', 'Arezzo', 'Ascoli Piceno',
+                                     'Asti', 'Avellino', 'Bari', 'Barletta-Andria-Trani', 'Belluno',
+                                     'Benevento', 'Bergamo', 'Biella', 'Bologna', 'Bolzano / Bozen',
+                                     'Brescia', 'Brindisi', 'Cagliari', 'Caltanissetta', 'Campobasso',
+                                     'Carbonia-Iglesias', 'Caserta', 'Catania', 'Catanzaro', 'Chieti',
+                                     'Como', 'Cosenza', 'Cremona', 'Crotone', 'Cuneo', 'Enna', 'Fermo',
+                                     'Ferrara', 'Firenze', 'Foggia', 'Forlì-Cesena', 'Frosinone',
+                                     'Genova', 'Gorizia', 'Grosseto', 'Imperia', 'Isernia', "L'Aquila",
+                                     'La Spezia', 'Latina', 'Lecce', 'Lecco', 'Livorno', 'Lodi',
+                                     'Lucca', 'Macerata', 'Mantova', 'Massa-Carrara', 'Matera',
+                                     'Medio Campidano', 'Messina', 'Milano', 'Modena',
+                                     'Monza e della Brianza', 'Napoli', 'Novara', 'Nuoro', 'Ogliastra',
+                                     'Olbia-Tempio', 'Oristano', 'Padova', 'Palermo', 'Parma', 'Pavia',
+                                     'Perugia', 'Pesaro e Urbino', 'Pescara', 'Piacenza', 'Pisa',
+                                     'Pistoia', 'Pordenone', 'Potenza', 'Prato', 'Ragusa', 'Ravenna',
+                                     'Reggio di Calabria', "Reggio nell'Emilia", 'Rieti', 'Rimini',
+                                     'Roma', 'Rovigo', 'Salerno', 'Sassari', 'Savona', 'Siena',
+                                     'Siracusa', 'Sondrio', 'Sud Sardegna', 'Taranto', 'Teramo',
+                                     'Terni', 'Torino', 'Trapani', 'Trentino Alto Adige / Südtirol',
+                                     'Trento', 'Treviso', 'Trieste', 'Udine',"Valle d'Aosta / Vallée d'Aoste",
+                                     'Varese', 'Venezia', 'Verbano-Cusio-Ossola', 'Vercelli', 
+                                     'Verona', 'Vibo Valentia', 'Vicenza', 'Viterbo'])
+        output1=""
+    
+        input_dict1 = {'T2M_MAX': temperature_max, 'T2M_MIN':temperature_min,'RH2M' : relative_humidity, 'total_area_ha': total_area_ha,
+                      'GWETROOT' : root_moisture, 'Type_crop' : crop, 'Type_fertilizer': fertilizer, 'Fertilizers_tonnes': fertilizer_tonnes ,'City' : city}
+        input_df1 = pd.DataFrame([input_dict1])
+
+        if st.button("Predict Cereal & Legumes"):
+            output1 = predict1(model1=model1, input_df1=input_df1)
+            output1 = 'Tons ' + "{:.2f}".format(output1)
+        
+        st.success('The output is {}'.format(output1))
+        
+    if add_selectbox == 'Fruits & Nuts':
+
+        temperature_max = st.number_input('Temperature max (°C)', min_value= 20, max_value= 50)
+        
+        temperature_min = st.number_input('Temperature min (°C)', min_value= -5, max_value= 20)
+        
+        relative_humidity = st.number_input('Relative humidity (%)', min_value=0, max_value=100)
+       
+        root_moisture = st.number_input('Root moisture', max_value=1)
+        
+        total_area_ha = st.number_input('Total area(ha)', min_value=0, max_value=430)
+        
+        fertilizer_tonnes = st.number_input('Fertilizer (tonnes)', min_value=0, max_value=3477)
+        
+        fertilizer = st.selectbox('Type of fertilizer', ['calcium cyanamide', 'nitrogen-potassium', 'peaty-amend',
+                                                 'organic-nitrogen', 'organic', 'ammonium sulphate',
+                                                 'nitrogen-phosphorous', 'phosphorus-potassium', 'urea'])
+        
+        crop = st.selectbox('Type of crop', ['apple', 'apricot', 'cherry in complex', 'kiwi', 'nectarine',
+                                             'plum', 'hazelnut', 'pear', 'peach', 'almond'])
+                                     
+        city = st.selectbox('City', ['Agrigento', 'Alessandria', 'Ancona', 'Arezzo', 'Ascoli Piceno',
+                                     'Asti', 'Avellino', 'Bari', 'Belluno', 'Benevento', 'Bergamo',
+                                     'Biella', 'Bologna', 'Brescia', 'Brindisi', 'Caltanissetta',
+                                     'Campobasso', 'Caserta', 'Catania', 'Catanzaro', 'Chieti', 'Como',
+                                     'Cosenza', 'Cremona', 'Crotone', 'Enna', 'Ferrara', 'Firenze', 
+                                     'Foggia', 'Frosinone', 'Genova', 'Gorizia', 'Grosseto', 'Imperia', 
+                                     'Isernia', 'La Spezia', 'Latina', 'Lecce', 'Lecco', 'Livorno', 
+                                     'Lodi', 'Lucca', 'Macerata', 'Mantova', 'Matera', 'Messina', 
+                                     'Milano', 'Modena', 'Napoli', 'Novara', 'Nuoro', 'Oristano',
+                                     'Padova', 'Palermo', 'Parma', 'Pavia', 'Perugia', 
+                                     'Pesaro e Urbino', 'Pescara', 'Piacenza', 'Pisa', 'Pistoia', 
+                                     'Pordenone', 'Potenza', 'Prato', 'Ragusa', 'Ravenna', 
+                                     'Reggio di Calabria', "Reggio nell'Emilia", 'Rieti', 'Rimini', 
+                                     'Roma', 'Rovigo', 'Salerno', 'Sassari', 'Savona', 'Siena', 
+                                     'Siracusa', 'Taranto', 'Teramo', 'Terni', 'Torino', 'Trapani', 
+                                     'Treviso', 'Trieste', 'Udine', 'Varese', 'Venezia', 
+                                     'Verbano-Cusio-Ossola', 'Vercelli', 'Verona', 'Vibo Valentia', 
+                                     'Vicenza', 'Viterbo', 'Carbonia-Iglesias', 'Medio Campidano', 
+                                     'Ogliastra', 'Olbia-Tempio', 'Barletta-Andria-Trani', 'Fermo', 
+                                     'Monza e della Brianza'])
+        
+        
+        output2=""
+    
+        input_dict2 = {'T2M_MAX': temperature_max, 'T2M_MIN':temperature_min,'RH2M' : relative_humidity, 'total_area_ha': total_area_ha,
+                      'GWETROOT' : root_moisture, 'Type_crop' : crop, 'Type_fertilizer': fertilizer, 'Fertilizers_tonnes': fertilizer_tonnes ,'City' : city}
+        input_df2 = pd.DataFrame([input_dict2])
+
+        if st.button("Predict Fruits & Nuts"):
+            output2 = predict2(model2=model2, input_df2=input_df2)
+            output2 = 'Tons ' + "{:.2f}".format(output2)
+        
+        st.success('The output is {}'.format(output2))
+        
+        
+    if add_selectbox == 'Grapes & Olives':
+
+        temperature_max = st.number_input('Temperature max (°C)', min_value= 20, max_value= 50)
+        
+        temperature_min = st.number_input('Temperature min (°C)', min_value= -5, max_value= 20)
+        
+        relative_humidity = st.number_input('Relative humidity (%)', min_value=0, max_value=100)
+       
+        root_moisture = st.number_input('Root moisture', max_value=1)
+        
+        total_area_ha = st.number_input('Total area(ha)', min_value=0, max_value=5010)
+        
+        fertilizer_tonnes = st.number_input('Fertilizer (tonnes)', min_value=0, max_value=2852)
+        
+        fertilizer = st.selectbox('Type of fertilizer', ['calcium cyanamide', 'nitrogen-potassium', 'peaty-amend',
+                                                 'organic-nitrogen', 'organic', 'ammonium sulphate',
+                                                 'nitrogen-phosphorous', 'phosphorus-potassium', 'urea'])
+        
+        crop = st.selectbox('Type of crop', ['grapes-n.e.c', 'grapes-wines(N-pdo/pgi)', 'table olives',
+                                             'grapes-table', 'oil olives', 'other olives',
+                                             'grapes-wines(Y-pdo)', 'grapes-wines(Y-pgi)', 'grapes-raisins'])
+                                     
+        city = st.selectbox('City', ['Agrigento', 'Alessandria', 'Ancona', 'Arezzo', 'Ascoli Piceno',
+                                     'Asti', 'Avellino', 'Bari', 'Belluno', 'Benevento', 'Bergamo', 
+                                     'Biella', 'Bologna', 'Brescia', 'Brindisi', 'Caltanissetta', 
+                                     'Campobasso', 'Caserta', 'Catania', 'Catanzaro', 'Chieti', 
+                                     'Cosenza', 'Cremona', 'Crotone', 'Enna', 'Ferrara', 'Firenze',
+                                     'Foggia', 'Frosinone', 'Genova', 'Grosseto', 'Imperia', 'Isernia',
+                                     'La Spezia', 'Latina', 'Lecce', 'Livorno', 'Lodi', 'Lucca', 
+                                     'Macerata', 'Mantova', 'Matera', 'Messina', 'Milano', 'Modena', 
+                                     'Napoli', 'Novara', 'Nuoro', 'Oristano', 'Padova', 'Palermo', 
+                                     'Parma', 'Pavia', 'Perugia', 'Pesaro e Urbino', 'Pescara', 
+                                     'Piacenza', 'Pisa', 'Pistoia', 'Pordenone', 'Potenza', 'Prato', 
+                                     'Ragusa', 'Ravenna', 'Reggio di Calabria', "Reggio nell'Emilia", 
+                                     'Rieti', 'Rimini', 'Roma', 'Rovigo', 'Salerno', 'Sassari', 
+                                     'Savona', 'Siena', 'Siracusa', 'Taranto', 'Teramo', 'Terni', 
+                                     'Torino', 'Trapani', 'Treviso', 'Trieste', 'Udine', 'Varese', 
+                                     'Venezia', 'Verbano-Cusio-Ossola', 'Vercelli', 'Verona', 
+                                     'Vibo Valentia', 'Vicenza', 'Viterbo', 'Carbonia-Iglesias', 
+                                     'Medio Campidano', 'Ogliastra', 'Olbia-Tempio', 
+                                     'Barletta-Andria-Trani', 'Fermo', 'Monza e della Brianza'])
+        
+        
+        output3=""
+    
+        input_dict3 = {'T2M_MAX': temperature_max, 'T2M_MIN':temperature_min,'RH2M' : relative_humidity, 'total_area_ha': total_area_ha,
+                      'GWETROOT' : root_moisture, 'Type_crop' : crop, 'Type_fertilizer': fertilizer, 'Fertilizers_tonnes': fertilizer_tonnes ,'City' : city}
+        input_df3 = pd.DataFrame([input_dict3])
+
+        if st.button("Predict Grapes & Olives"):
+            output3 = predict3(model3=model3, input_df3=input_df3)
+            output3 = 'Tons ' + "{:.2f}".format(output3)
+        
+        st.success('The output is {}'.format(output3))
+        
+        
+        
+    if add_selectbox == 'Fresh Vegetables':
+
+        temperature_max = st.number_input('Temperature max (°C)', min_value= 20, max_value= 50)
+        
+        temperature_min = st.number_input('Temperature min (°C)', min_value= -5, max_value= 20)
+        
+        relative_humidity = st.number_input('Relative humidity (%)', min_value=0, max_value=100)
+       
+        root_moisture = st.number_input('Root moisture', max_value=1)
+        
+        total_area_ha = st.number_input('Total area(ha)', min_value=0, max_value=431)
+        
+        fertilizer_tonnes = st.number_input('Fertilizer (tonnes)', min_value=0, max_value=3473)
+        
+        fertilizer = st.selectbox('Type of fertilizer', ['calcium cyanamide', 'nitrogen-potassium', 'peaty-amend',
+                                                 'organic-nitrogen', 'organic', 'ammonium sulphate',
+                                                 'nitrogen-phosphorous', 'phosphorus-potassium', 'urea'])
+        
+        crop = st.selectbox('Type of crop', ['cauliflower&broccoli-field', 'courgette-field', 'egg-plant-field',
+                                             'fresh-beans-field', 'lettuce-field', 'onions-field', 
+                                             'red-pepper-field', 'chicory-field', 'melon-field', 'fresh-tomato'])
+                                     
+        city = st.selectbox('City', ['Agrigento', 'Alessandria', 'Ancona', 'Arezzo', 'Ascoli Piceno', 
+                                     'Asti', 'Avellino', 'Bari', 'Belluno', 'Benevento', 'Bergamo', 
+                                     'Biella', 'Bologna', 'Brescia', 'Brindisi', 'Caltanissetta', 
+                                     'Campobasso', 'Caserta', 'Catania', 'Catanzaro', 'Chieti', 
+                                     'Cosenza', 'Cremona', 'Crotone', 'Enna', 'Ferrara', 'Firenze', 
+                                     'Foggia', 'Frosinone', 'Genova', 'Gorizia', 'Grosseto', 'Imperia', 
+                                     'Isernia', 'La Spezia', 'Latina', 'Lecce', 'Livorno', 'Lodi', 
+                                     'Lucca', 'Macerata', 'Mantova', 'Matera', 'Messina', 'Milano',
+                                     'Modena', 'Napoli', 'Novara', 'Nuoro', 'Oristano', 'Padova', 
+                                     'Palermo', 'Parma', 'Pavia', 'Perugia', 'Pesaro e Urbino', 
+                                     'Pescara', 'Piacenza', 'Pisa', 'Pistoia', 'Pordenone', 'Potenza', 
+                                     'Prato', 'Ragusa', 'Ravenna', 'Reggio di Calabria', 
+                                     "Reggio nell'Emilia", 'Rimini', 'Roma', 'Rovigo', 'Salerno', 
+                                     'Sassari', 'Savona', 'Siena', 'Siracusa', 'Taranto', 'Teramo', 
+                                     'Terni', 'Torino', 'Trapani', 'Treviso', 'Trieste', 'Udine', 
+                                     'Varese', 'Venezia', 'Verbano-Cusio-Ossola', 'Vercelli', 'Verona',
+                                     'Vibo Valentia', 'Vicenza', 'Viterbo', 'Carbonia-Iglesias', 
+                                     'Medio Campidano', 'Ogliastra', 'Olbia-Tempio', 'Barletta-Andria-Trani', 
+                                     'Fermo', 'Monza e della Brianza'])
+        
+        
+        output4=""
+    
+        input_dict4 = {'T2M_MAX': temperature_max, 'T2M_MIN':temperature_min,'RH2M' : relative_humidity, 'total_area_ha': total_area_ha,
+                      'GWETROOT' : root_moisture, 'Type_crop' : crop, 'Type_fertilizer': fertilizer, 'Fertilizers_tonnes': fertilizer_tonnes ,'City' : city}
+        input_df4 = pd.DataFrame([input_dict4])
+
+        if st.button("Predict Fresh Vegetables"):
+            output4 = predict4(model4=model4, input_df4=input_df4)
+            output4 = 'Tons ' + "{:.2f}".format(output4)
+        
+        st.success('The output is {}'.format(output4))
+        
+        
+        
+    if add_selectbox == 'Industrial crops':
+
+        temperature_max = st.number_input('Temperature max (°C)', min_value= 20, max_value= 50)
+        
+        temperature_min = st.number_input('Temperature min (°C)', min_value= -5, max_value= 20)
+        
+        relative_humidity = st.number_input('Relative humidity (%)', min_value=0, max_value=100)
+       
+        root_moisture = st.number_input('Root moisture', max_value=1)
+        
+        total_area_ha = st.number_input('Total area(ha)', min_value=0, max_value=1440)
+        
+        fertilizer_tonnes = st.number_input('Fertilizer (tonnes)', min_value=0, max_value=4824)
+        
+        fertilizer = st.selectbox('Type of fertilizer', ['calcium cyanamide', 'nitrogen-potassium', 'peaty-amend',
+                                                 'organic-nitrogen', 'organic', 'ammonium sulphate',
+                                                 'nitrogen-phosphorous', 'phosphorus-potassium', 'urea'])
+        
+        crop = st.selectbox('Type of crop', ['hemp', 'rape', 'soya beans', 'tobacco', 'flax', 'parsley-field',
+                                             'sunflower'])
+                                     
+        city = st.selectbox('City', ['Alessandria', 'Ancona', 'Arezzo', 'Ascoli Piceno', 'Asti',
+                                     'Avellino', 'Bari', 'Belluno', 'Benevento', 'Bergamo', 'Biella',
+                                     'Bologna', 'Brescia', 'Caltanissetta', 'Campobasso', 'Caserta', 
+                                     'Catania', 'Catanzaro', 'Chieti', 'Como', 'Cosenza', 'Cremona', 
+                                     'Crotone', 'Ferrara', 'Firenze', 'Foggia', 'Frosinone', 'Genova', 
+                                     'Gorizia', 'Grosseto', 'Imperia', 'Isernia', 'Latina', 'Lecco', 
+                                     'Livorno', 'Lodi', 'Lucca', 'Macerata', 'Mantova', 'Matera', 
+                                     'Milano', 'Modena', 'Napoli', 'Novara', 'Nuoro', 'Oristano', 
+                                     'Padova', 'Parma', 'Pavia', 'Perugia', 'Pescara', 'Piacenza', 
+                                     'Pisa', 'Pistoia', 'Pordenone', 'Potenza', 'Prato', 'Ravenna', 
+                                     "Reggio nell'Emilia", 'Rieti', 'Rimini', 'Roma', 'Rovigo', 
+                                     'Salerno', 'Sassari', 'Savona', 'Siena', 'Taranto', 'Teramo', 
+                                     'Terni', 'Torino', 'Treviso', 'Trieste', 'Udine', 'Varese', 
+                                     'Venezia', 'Verbano-Cusio-Ossola', 'Vercelli', 'Verona', 'Vicenza', 
+                                     'Viterbo', 'Carbonia-Iglesias', 'Medio Campidano', 'Ogliastra', 
+                                     'Vibo Valentia', 'Barletta-Andria-Trani', 'Fermo', 
+                                     'Monza e della Brianza', 'La Spezia'])
+        
+        
+        output5=""
+    
+        input_dict5 = {'T2M_MAX': temperature_max, 'T2M_MIN':temperature_min,'RH2M' : relative_humidity, 'total_area_ha': total_area_ha,
+                      'GWETROOT' : root_moisture, 'Type_crop' : crop, 'Type_fertilizer': fertilizer, 'Fertilizers_tonnes': fertilizer_tonnes ,'City' : city}
+        input_df5 = pd.DataFrame([input_dict5])
 
-APP_TITLE = "Italy Agrifoods Data"
-APP_SUB_TITLE = "by Omdena Milan chapter 👇 (https://omdena.com/local-chapters/milan-italy-chapter/)"
-image = Image.open('data/logo.png')
-image=image.resize((100,100))
-#st.set_page_config(layout="wide")
+        if st.button("Predict Industrial crops"):
+            output5 = predict5(model5=model5, input_df5=input_df5)
+            output5 = 'Tons ' + "{:.2f}".format(output5)
+        
+        st.success('The output is {}'.format(output5))
 
-st.title(APP_TITLE)
+if __name__ == '__main__':
+    
+    run()
+    

requirements.txt

@@ -2,4 +2,5 @@ streamlit-option-menu
 geopandas
 millify
 folium
-streamlit_folium
+streamlit_folium
+pycaret==3.0.0rc2