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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+Crop_Yield_Prediction_doc.docx filter=lfs diff=lfs merge=lfs -text

Crop_Yield_Prediction_doc.docx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:fef4a7457a9406952a6060f43d6d6a2e8aa0551f220fa284309817add6144929
+size 1782316

app.py

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+import streamlit as st 
+import joblib
+
+html_temp = """
+    <div style="background-color:lightgreen;padding:10px">
+    <h2 style="color:white;text-align:center;">Crop Yeid Prediction </h2>
+    </div>
+    """
+st.markdown(html_temp, unsafe_allow_html=True)
+
+image_url="https://miro.medium.com/v2/resize:fit:1358/0*k-lYNf3gZ1M2u6AN"
+
+st.image(image_url, use_container_width=True)
+
+# Area
+options_Area = ['Albania', 'Algeria', 'Angola', 'Argentina', 'Armenia','Australia', 'Austria', 'Azerbaijan', 'Bahamas', 'Bahrain',
+                'Bangladesh', 'Belarus', 'Belgium', 'Botswana', 'Brazil','Bulgaria', 'Burkina Faso', 'Burundi', 'Cameroon', 'Canada',
+                'Central African Republic', 'Chile', 'Colombia', 'Croatia',
+                'Denmark', 'Dominican Republic', 'Ecuador', 'Egypt', 'El Salvador','Eritrea', 'Estonia', 'Finland', 'France', 'Germany', 'Ghana',
+                'Greece', 'Guatemala', 'Guinea', 'Guyana', 'Haiti', 'Honduras',
+                'Hungary', 'India', 'Indonesia', 'Iraq', 'Ireland', 'Italy',
+                'Jamaica', 'Japan', 'Kazakhstan', 'Kenya', 'Latvia', 'Lebanon',
+                'Lesotho', 'Libya', 'Lithuania', 'Madagascar', 'Malawi',
+                'Malaysia', 'Mali', 'Mauritania', 'Mauritius', 'Mexico',
+                'Montenegro', 'Morocco', 'Mozambique', 'Namibia', 'Nepal',
+                'Netherlands', 'New Zealand', 'Nicaragua', 'Niger', 'Norway',
+                'Pakistan', 'Papua New Guinea', 'Peru', 'Poland', 'Portugal',
+                'Qatar', 'Romania', 'Rwanda', 'Saudi Arabia', 'Senegal',
+                'Slovenia', 'South Africa', 'Spain', 'Sri Lanka', 'Sudan',
+                'Suriname', 'Sweden', 'Switzerland', 'Tajikistan', 'Thailand',
+                'Tunisia', 'Turkey', 'Uganda', 'Ukraine', 'United Kingdom',
+                'Uruguay', 'Zambia', 'Zimbabwe']
+Area= st.selectbox('Choose an Area:', options_Area)
+Area_value=options_Area.index(Area)
+
+# Item
+options_Item =['Maize','Potatoes', 'Rice, paddy', 'Sorghum', 'Soybeans',
+               'Wheat','Cassava', 'Sweet potatoes', 'Plantains and others', 'Yams']
+Item= st.selectbox('Choose a Item:', options_Item)
+Item_value=options_Item.index(Item)
+
+# average_rain_fall_mm_per_year
+avg_rainfall=st.slider('Slide The value to get Avg Rainfall',min_value=51,max_value=3240,value=51)
+
+# Pesticides_tonnes
+pes_tonnes=st.slider('Slide The value to get Pesticides in Tonnes',min_value=1,max_value=367778,value=1)
+
+# Avg Temp
+avg_temp=st.slider('Slide The value to get Avg Temperature',min_value=1,max_value=30,value=1)
+
+model=joblib.load("crop_yield_model_rf.joblib")
+
+if st.button("Enter"):
+    output=model.predict([[Area_value,Item_value,avg_rainfall,pes_tonnes,avg_temp]])
+    
+    st.write("The Predicted Value of Yield:",output)

crop_yield_model_rf.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b706ac59309765a28d368882be9dc32aada684680b613bff00243cb25e3e6e31
+size 118439330

requirements.txt

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+joblib==1.3.2
+matplotlib==3.8.3
+matplotlib-inline==0.1.6
+numpy==1.26.4
+pandas==2.2.0
+scikit-learn==1.4.1.post1
+seaborn==0.13.2
+streamlit==1.32.2
+streamlit-chat==0.1.1